From 412128324ad391ac7ccc59908d994dfb6d9a3fe2 Mon Sep 17 00:00:00 2001 From: Daniel Young Date: Tue, 20 Feb 2024 13:08:36 -0800 Subject: [PATCH 1/7] Reran all experiments using fixed dataset --- use_cases/eluc/.gitignore | 2 + use_cases/eluc/data/eluc_data.py | 9 +- .../experiments/predictor_experiments.ipynb | 146 +- .../experiments/prescriptor_experiments.ipynb | 1132 +- .../eluc/prescriptors/create_seeds.ipynb | 1241 +- .../prescriptors/train_prescriptors.ipynb | 66403 +++++++++++++++- 6 files changed, 67241 insertions(+), 1692 deletions(-) diff --git a/use_cases/eluc/.gitignore b/use_cases/eluc/.gitignore index 429efd3..d9c7151 100644 --- a/use_cases/eluc/.gitignore +++ b/use_cases/eluc/.gitignore @@ -3,6 +3,8 @@ predictors/*/trained_models/ # Ignores predictor significance results experiments/predictor_significance +# Ignores figures for paper +experiments/figures # Ignores trained prescriptors and seeds prescriptors/trained_prescriptors diff --git a/use_cases/eluc/data/eluc_data.py b/use_cases/eluc/data/eluc_data.py index 5ba13d8..3953ee4 100644 --- a/use_cases/eluc/data/eluc_data.py +++ b/use_cases/eluc/data/eluc_data.py @@ -152,8 +152,9 @@ def __init__(self, start_year=1851, test_year=2012, end_year=2022, countries=Non if countries: df = self.subset_countries(df, countries) - self.train_df = df.loc[start_year:test_year] - self.test_df = df.loc[test_year:end_year] + self.train_df = df.loc[start_year:test_year-1] + self.test_df = df.loc[test_year:end_year-1] + assert self.train_df['time'].max() == self.test_df["time"].min() - 1 self.encoder = ELUCEncoder(self.get_fields()) @@ -177,8 +178,8 @@ def __init__(self, path, update_path, start_year=1851, test_year=2012, end_year= raw = self.import_data(path, update_path) df = self.da_to_df(raw, start_year, end_year, countries) - self.train_df = df.loc[start_year:test_year] - self.test_df = df.loc[test_year:end_year] + self.train_df = df.loc[start_year:test_year-1] + self.test_df = df.loc[test_year:end_year-1] self.encoder = ELUCEncoder(self.get_fields()) diff --git a/use_cases/eluc/experiments/predictor_experiments.ipynb b/use_cases/eluc/experiments/predictor_experiments.ipynb index f1003fb..64448fd 100644 --- a/use_cases/eluc/experiments/predictor_experiments.ipynb +++ b/use_cases/eluc/experiments/predictor_experiments.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -29,6 +29,7 @@ "\n", "from data.eluc_data import ELUCData\n", "from data import constants\n", + "from data.conversion import construct_countries_df\n", "from predictors.predictor import Predictor\n", "from predictors.neural_network.neural_net_predictor import NeuralNetPredictor\n", "from predictors.sklearn.sklearn_predictor import LinearRegressionPredictor, RandomForestPredictor" @@ -66,7 +67,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -87,29 +88,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 19028/19028 [14:12<00:00, 22.32it/s]\n", + "100%|██████████| 19028/19028 [14:17<00:00, 22.18it/s]\n", + "100%|██████████| 19028/19028 [14:19<00:00, 22.14it/s]\n" + ] + } + ], "source": [ "results = nnp.fit(dataset.train_df[nn_config[\"features\"]], dataset.train_df[nn_config[\"label\"]], verbose=True)\n", - "nnp.save(\"predictors/neural_network/trained_models/experiment_nn\")" + "nnp.save(\"predictors/neural_network/trained_models/no_overlap_nn\")" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "MAE Neural Net: 0.04711493104696274\n" + "MAE Neural Net: 0.05021795630455017\n" ] } ], "source": [ - "nnp.load(\"predictors/neural_network/trained_models/experiment_nn\")\n", + "nnp.load(\"predictors/neural_network/trained_models/no_overlap_nn\")\n", "print(f\"MAE Neural Net: {mean_absolute_error(dataset.test_df[nn_config['label']], nnp.predict(dataset.test_df[nn_config['features']]))}\")" ] }, @@ -122,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -135,29 +146,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "linreg.fit(dataset.train_df[constants.DIFF_LAND_USE_COLS], dataset.train_df[\"ELUC\"])\n", - "linreg.save(\"predictors/sklearn/trained_models/experiment_linreg\")" + "linreg.save(\"predictors/sklearn/trained_models/no_overlap_linreg\")" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "MAE Linear Regression: 0.07567060738801956\n" + "MAE Linear Regression: 0.07429615408182144\n" ] } ], "source": [ - "linreg.load(\"predictors/sklearn/trained_models/experiment_linreg\")\n", + "linreg.load(\"predictors/sklearn/trained_models/no_overlap_linreg\")\n", "print(f\"MAE Linear Regression: {mean_absolute_error(dataset.test_df['ELUC'], linreg.predict(dataset.test_df[constants.DIFF_LAND_USE_COLS]))}\")" ] }, @@ -170,7 +181,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -184,14 +195,15 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# Note: The original paper trains from 1982 onwards but this is too slow and large for the\n", "# purpose of this example.\n", - "forest.fit(dataset.train_df.loc[2002:][constants.NN_FEATS], dataset.train_df.loc[2002:][\"ELUC\"])\n", - "forest.save(\"predictors/sklearn/trained_models/experiment_rf\")" + "forest_year = 1982\n", + "forest.fit(dataset.train_df.loc[forest_year:][constants.NN_FEATS], dataset.train_df.loc[forest_year:][\"ELUC\"])\n", + "forest.save(\"predictors/sklearn/trained_models/no_overlap_rf\")" ] }, { @@ -203,12 +215,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "MAE Random Forest: 0.037707034150731636\n" + "MAE Random Forest: 0.03978765055906081\n" ] } ], "source": [ - "forest.load(\"predictors/sklearn/trained_models/experiment_rf\")\n", + "# TODO: I don't think we can possibly load a model this big\n", + "# forest.load(\"predictors/sklearn/trained_models/no_overlap_rf\")\n", "print(f\"MAE Random Forest: {mean_absolute_error(dataset.test_df['ELUC'], forest.predict(dataset.test_df[constants.NN_FEATS]))}\")" ] }, @@ -221,7 +234,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -287,12 +300,19 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Neural Net\n" + ] + }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAEJCAYAAACKWmBmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAAesklEQVR4nO3df5QcVZ338fcnkyyIyC+BCAE2KIhCwBARRQEDoqDoIrsJQQVkwR0V0Md9ln2Eo0cF5Iiiu8oqPwbNCUo2CGgUkQUJyA+zSAgQIQECEQIJoIhGNuAmkJnv80fdkaaZqemZqerq7vm8zqnTVbdudX3vdDLfuXWrbisiMDMzG8y4qgMwM7PW5kRhZma5nCjMzCyXE4WZmeVyojAzs1xOFGZmlsuJwsyshUmaLekpSUtryr4k6XFJS9Lyvpp9p0taIWm5pEMLicHPUZiZtS5JBwLPAt+PiCmp7EvAsxHx9bq6uwPzgH2B7YEFwOsjonc0MYwfzcFtZdWqjsuI5yydW3UIpdhl212qDqEUSx5bUnUIhZsyaUrVIZTi6H2P1qjeQGr8901E7rki4hZJkxt8tyOAyyJiPfCIpBVkSeO2huMZgC89mZkVbdy4hhdJ3ZIW1yzdDZ7lFEn3pEtTW6ayScCqmjqrU9nomjPaNzAzszrDSBQR0RMR+9QsPQ2c4QLgdcBU4EngG2U2Z+xcejIzaxaN7srVUCLi9y+eShcDV6fNx4Eda6rukMpGxT0KM7OiDaNHMRKStqvZPBLovyPqKuBoSRtJ2hnYFVg0qrbgHoWZWfHGF/erVdI8YDqwtaTVwBeB6ZKmAgGsBD4OEBHLJF0O3AdsAE4e7R1P4ERhZla8EfYUBhIRHxqg+Hs59c8Gzi4sAJwozMyKV2CiaAVOFGZmRSt5MLvZnCjMzIrWYT2KylsjaY6kGVXHYWZWmJLvemq2SnsUktyjMbPOU+BdT62gtHQmaXLdbIenphkPb5L0TUmLgf+Tdh+SHl1/UNL7a46/VdJdaXl7Kp+e3uNKSQ9Imit12AVBM2tv7lEU4m8iYh/ILj0Bk8kmrnod8EtJuwBPAe+OiHWSdiWbEXGfdPzewB7AE8BC4B3Ar5rZADOzQbVJAmhUVa35Yd325RHRFxEPAQ8DbwAmABdLuhe4Ati9pv6iiFgdEX3AErJE8zK1k231zO3MmVbNrAW5R9GwDbw0EW1cs/5cXd36KXkD+Gfg98Cb0vusq9m/vma9l0HakSbXyibY6sBpxs2sRXXY1fAy09nvgW0lvVrSRsD7c+rOlDRO0uuA1wLLgc2BJ1Ov4Vigq8RYzcyKM35840sbKC3KiHhB0plkE1I9DjyQU/2xVG8z4BNpXOJ84EeSjgOu5eW9EDOz1tQml5QaVWo6i4jzgPOGqHP8IOUPAXvVFH02ld8E3FRT75RRhmlmViwnCjMzy9VhYxROFGZmRXOPwszMcjlRmJlZrja5m6lRndUaM7NW4B6FmZnlcqIwM7NcThRmZpbLicLMzHL5OYo2tdNOVUdQuNNuvbXqEEoRb35H1SGU4g2veUPVIRRuyiu2rzqE1uS7nszMLJcvPZmZWS4nCjMzy+UxCjMzy+UehZmZ5fJgtpmZ5XKPwszMcjlRmJlZrg5LFJW3RtKZkg6pOg4zs8KMG9f4MgRJsyU9JWlpTdlWkq6X9FB63TKVS9J5klZIukfStEKaU8SbjJSkroj4QkQsqDIOM7NCSY0vQ5sDHFZXdhpwQ0TsCtyQtgHeC+yalm7ggiKaU1qikDRZ0gOS5kq6X9KVkjaRtFLSVyXdBcyUNEfSjHTMSklfkbRE0mJJ0yRdJ+m3kj6R6kyXdFN6v/7376ybls2svY0f3/gyhIi4BfhTXfERwCVp/RLggzXl34/Mr4EtJG032uaU3aPYDTg/It4I/A9wUir/Y0RMi4jLBjjmsYiYCtxKlklnAG8DzqipszfwGWB34LVAZ04OZGbtaRiXniR1pz+M+5fuBs4wMSKeTOu/Ayam9UnAqpp6q1PZqJQ9mL0qIham9UuBT6f1H+Ycc1V6vRfYNCLWAmslrZe0Rdq3KCJWA0haAkwGflX/RukH3g1wUf+KmVnZhjGYHRE9QM9ITxURISlGenwjyk4U9cH3bz+Xc8z69NpXs96/Pb6uDkAvg7TjJR9AyT9IM7O/Kv+up99L2i4inkyXlp5K5Y8DO9bU2yGVjUrZrdlJ0n5p/cMM8Fe/mVnHKXYweyBXAR9N6x8FflpTfly6++ltwDM1l6hGrOxEsRw4WdL9wJYUNAJvZtbSir09dh5wG7CbpNWSTgTOAd4t6SHgkLQNcA3wMLACuJgXx4VHpexLTxsi4pi6ssm1GxFxfM365Jr1OWSD2fX7bkpLf/kpRQRqZlaYAud6iogPDbLrXQPUDeDkwk6e+MlsM7OiddiT2aUliohYCUwp6/3NzFqWE4WZmeVyojAzs1xOFGZmlqurq+oICuVEYWZWNPcozMwslxOFmZnlcqIwM7NcHfbNB2MnUbzylVVHULzD6r/LpDPoYx+rOoRSTPnQYA/YtrFbZ1cdQTlOPXV0x7tHYWZmuQqcwqMVdFZrzMxagXsUZmaWy4nCzMxyOVGYmVkuJwozM8vlRGFmZrk815OZmeXqsB5FS7VG0pmSDhnmMedKWibp3LLiMjMblgK/M7sVtEyPQlJXRHxhBId2A1tFRG/RMZmZjUibJIBGNaU1kiZLekDSXEn3S7pS0iaSVkr6qqS7gJmS5kiakY5ZKekrkpZIWixpmqTrJP1W0idSnauATYE7Jc1qRlvMzIYkNb60gWb2KHYDToyIhZJmAyel8j9GxDQASfWTFz0WEVMl/TswB3gHsDGwFLgwIv5O0rMRMbUpLTAza8SECVVHUKhm9o9WRcTCtH4psH9a/2HOMVel13uB2yNibUT8AVgvaYuhTiipO/VGFve88MJI4zYzGx73KEYsBtl+LueY9em1r2a9f3vI2COiB+gBYNNN689vZlYOj1GM2E6S9kvrHwZ+1cRzm5k1T4fd9dTMKJcDJ0u6H9gSuKCJ5zYza54OSxTNvPS0ISKOqSubXLsREcfXrE+uWZ9DNpg90L5NiwzSzGzU2iQBNKplnqMwM+sYnsJj+CJiJTClGecyM6ucexRmZpbLicLMzHIVnCgkrQTWAr1k4737SNqK7Dm0ycBK4KiIWFPoiZPOSntmZq2gnLueDoqIqRGxT9o+DbghInYFbkjbpXCiMDMrWnOezD4CuCStXwJ8cLRhD8aXnszMijaMuZ4kdZPNgt2vJ80qUSuAX0gK4KK0f2JEPJn2/w6YOIqIczlRmJkVbRg9hZdMNTS4/SPicUnbAtdLeqDuPSIlkVI4UZiZFa3gweyIeDy9PiVpPrAv8HtJ20XEk5K2A54q9KQ1xk6i+MJIvhOpxf3rv1YdgQ3Djct/WXUIhTvo1H+pOoRSjHpO1wIThaRXAuMiYm1afw9wJtns2h8FzkmvPy3spHXGTqIwM2uWYnsUE4H5yi5njQf+MyKulXQHcLmkE4FHgaOKPGktJwozs6IVOIVHRDwMvGmA8j8C7yrsRDmcKMzMiuYns83MLJcThZmZ5XKiMDOzXE4UZmaWy4nCzMxyje+sX61tk/YkzZE0o+o4zMyG1JxJAZums9KemVkr8KWnxqRHzS8HdgC6gLOAFcC/AZsCTwPHp3lKdgEuBLYh+2KOmcDDwH8A7wZWAc/XvPdKsml1PwBMAGZGxEsmyTIzq4wTRcMOA56IiMMBJG0O/BdwRET8QdIs4GzgBGAucE5EzJe0MdklsSOB3YDdyR5hvw+YXfP+T0fENEknAacCHyuxLWZmjeuwRFFma+4F3i3pq5IOAHYEppBNkbsE+Dywg6RXAZMiYj5ARKyLiL8ABwLzIqI3Ip4Abqx7/x+n1zvJvgrwZSR1S1osaXHP7bcX3Dwzs0GMH9/40gZKizIiHpQ0DXgf8GWyX/TLImK/2nopUYzE+vTayyDteMk871/7WmlztZuZvUSbDFI3qrQehaTtgb9ExKXAucBbgW0k7Zf2T5C0R0SsBVZL+mAq30jSJsAtwCxJXWmu9YPKitXMrFDlfGd2Zcrs9+wJnCupD3gB+CSwATgvjVeMB74JLAOOBS6SdGaqOxOYDxxMNjbxGHBbibGamRWnTRJAo8q89HQdcN0Auw4coO5DZEmh3imDvPfkmvXFwPQRBWlmVoaxmCgk7Qx8imzQ+K/HRMTflROWmVkbG4uJAvgJ8D3gZ0BfadGYmXWCNrmbqVGNtmZdRJxXaiRmZp1ijPYoviXpi8AvePG2VCLirlKiMjNrZx12e2yjiWJPsjuTDubFS0/BwAPQZmZj2xjtUcwEXhsRzw9Z08xsrBujiWIpsAXwVHmhmJl1iDGaKLYAHpB0By8do/DtsWZm9bq6qo6gUI0mii+WGoWZWScZiz2KiLhZ0kTgLaloUUS012WouXOrjqB4W29ddQTl2HvvqiMoxUF7d950ZVq6rOoQyjFlyuiO77BE0VBrJB0FLCIb1D4KuN1fS2pmNogxOing54C39PciJG0DLACuLCswM7O21SYJoFGNJopxdZea/ki5X3pkZta+xugUHtdKug6Yl7ZnAdeUE5KZWZsbaz0KSQLOIxvI3j8V9/R/damZmdUZa4kiIkLSNRGxJy9+T7WZmQ2m4LmeJB0GfAvoAr4bEecUeoIhNJr27pL0lqGrmZlZkXc9SeoCvgO8F9gd+JCk3UtuwUs0OkbxVuAYSSuB5wCRdTb2KiswM7O2Veylp32BFRHxMICky4AjyL4muilyE4WknSLiMeDQJsVjZtb2eqPx73cbP258N9BdU9QTET0125OAVTXbq8n+eG+aoXoUPwGmRcSjkn4UEf/QhJiGJGkOcHVEXCnpAOBC4AVgv4j430qDM7MxLyKGU7cH6BmyYoWGShS1IzKvLTOQUfgI8JWIuLTqQMzMAPqG0aNowOPAjjXbO6SyphnqQloMsj4skl4p6eeSfiNpqaRZkt4s6WZJd0q6TtJ2qe4ukhakundJep0y35a0XNICYNtU92NkU4qcJakDJ3Mys3bUF30NLw24A9hV0s6S/gY4Griq1AbUGapH8SZJ/0PWs3hFWocXB7M3a/A8hwFPRMThAJI2B/4LOCIi/iBpFnA2cAIwFzgnIuZL2pgsmR0J7EY24j+RbBBndkR8V9L+pMtQDcZiZlaqInsUEbFB0inAdWS3x86OiKbOxpibKCKiqEnV7wW+IemrwNXAGmAKcH32PB9dwJOSXgVM6n+YLyLWAUg6EJgXEb3AE5JubOSkkv46SHTRpEl0v/rVBTXHzGxwBV96IiKuocLZMJoyIUlEPChpGvA+4MvAjcCyiNivtl5KFEWe98VBoje9acSXzszMhmND34aqQyhUU54zl7Q98Jc04Hwu2a1d20jaL+2fIGmPiFgLrJb0wVS+kaRNgFuAWZK60lhG503sb2Ydo6+vr+GlHTRrisM9gXMl9ZHdxvpJYANwXhqvGA98E1gGHAtcJOnMVHcmMB84mGxs4jHgtibFbWY2bMO5PbYdNOvS03VkAzH1Dhyg7kNkSaHeKYO89/GjCs7MrGBFj1FUrbMmTTczawFOFGZmlqvTBrOdKMzMCtYug9SNcqIwMytYjHwii5bkRGFmVjD3KMzMLJcHs83MLJcThZmZ5fJdT+1qxoyqIyje4YdXHUEpYuK2VYdQiiWPLak6hMJNnTK16hBKoaGr5HKPwszMcnkw28zMcvn2WDMzy+UehZmZ5fIYhZmZ5fJdT2ZmlsvfR2FmZrl86cnMzHJ5MNvMzHL14URhZmY5NvR6MHtEJAlQRIddvDMzq9NpYxTjynxzSZMlLZf0fWAp8D1JiyUtk3RGTb2Vks6QdJekeyW9IZVvI+n6VP+7kh6VtHXad4ykRZKWSLpIUleZbTEza1Rf9DW8tINSE0WyK3B+ROwB/EtE7APsBbxT0l419Z6OiGnABcCpqeyLwI3p2CuBnQAkvRGYBbwjIqYCvcBHmtAWM7MhOVEM36MR8eu0fpSku4C7gT2A3Wvq/Ti93glMTuv7A5cBRMS1wJpU/i7gzcAdkpak7dfWn1hSd+rBLO5ZvLiwBpmZ5YmIhpd20IwxiucAJO1M1lN4S0SskTQH2Lim3vr02ttAXAIuiYjT8ypFRA/QA8BZZ7XHJ2Jmba/Tbo9tRo+i32ZkSeMZSROB9zZwzELgKABJ7wG2TOU3ADMkbZv2bSXpb4sP2cxs+Db0bWh4aQdNSxQR8RuyS04PAP9JlgSGcgbwHklLgZnA74C1EXEf8HngF5LuAa4HtislcDOzYWrWGIWkL0l6PN3Us0TS+2r2nS5pRbqh6NDRnKfUS08RsRKYUrN9/CD1JtesLwamp81ngEMjYoOk/cguW61P9X4I/LCMuM3MRqPJYw//HhFfry2QtDtwNNlY8PbAAkmvj4jekZyg1R+42wm4XNI44HngnyqOx8xsSC1wN9MRwGXpD+tHJK0A9gVuG8mbtXSiiIiHgL2rjsPMbDiGkygkdQPdNUU96UacRp0i6ThgMdkjCGuAScCva+qsTmUj0tKJwsysHQ1nCo+X3J05AEkLgNcMsOtzZM+dnQVEev0GcMJwYm2EE4WZWcGKvPQUEYc0Uk/SxcDVafNxYMea3TukshFp5u2xZmZjQhPveqq92/NIsqmSAK4Cjpa0UXqGbVdg0UjP4x6FmVnBmjiY/TVJU8kuPa0EPg4QEcskXQ7cB2wATh7pHU/gRGFmVrhm3R4bEcfm7DsbOLuI8zhRmJkVrAVujy3U2EkUEyZUHUHhYuK2VYdQiiWPLak6hFLMWzSv6hAKd9tvR3Rbfss76aCTRnV8u0zN0aixkyjMzJqk0yYFdKIwMyuYLz2ZmVmudvmeiUY5UZiZFcw9CjMzy9U78kcWWpIThZlZwXr7nCjMzCyHLz2ZmVku3x5rZma53KOokKTpwPMR8d8Vh2JmNijfHlut6cCzwMsShaTxEdFZz82bWVvyFB4jJGkycC1wJzANWAYcB5wKfAB4BVkC+HhEhKRPA58gmyL3PuC0tN0r6RjgU8CJwDqyr0tdCPzfZrXHzGwwvvQ0OrsBJ0bEQkmzgZOAb0fEmQCSfgC8H/gZWWLYOSLWS9oiIv4s6ULg2Yj4eqp/Itk3N719NHOtm5kVqdMSRbO/4W5VRCxM65cC+wMHSbpd0r3AwcAeaf89wNzUe8jrx10xWJKQ1C1psaTFPYtG/OVOZmbD0tfX1/DSDpqdKOpHeAI4H5gREXsCFwMbp32HA98hu0x1h6TBej/PDXqyiJ6I2Cci9uned9/RRW5m1qCIaHhpB81OFDtJ2i+tfxj4VVp/WtKmwAwASeOAHSPil8Bngc2BTYG1wKuaG7KZ2fD0Rm/DSzto9hjFcuDkND5xH3ABsCXZF4L/Drgj1esCLpW0OSDgvDRG8TPgSklHkA1mm5m1HE/hMTobIuKYurLPp6Xe/vUFEfEgsFdN0a0FxmZmVohOG8xut+cozMxanhPFCEXESmBKs85nZlYVJwozM8vVLre9NsqJwsysYO1y22ujnCjMzArmuZ7MzCyXxyjMzCyXE4WZmeXyGIWZmeVql6k5GjVmEkWc9tmqQyjcj+78UdUhlOLiWy+uOoRSPPL0I1WHULhXbdSZU6+ddNBJozq+t7ezEkWzJwU0M+t4fdHX8DIakmZKWiapT9I+dftOl7RC0nJJh9aUH5bKVkg6rZHzjJkehZlZszRxMHsp8PfARbWFknYHjib7fp/tgQWSXp92fwd4N7Ca7CscroqI+/JO4kRhZlawZiWKiLgfQFL9riOAyyJiPfCIpBVA/5fyrIiIh9Nxl6W6uYnCl57MzAo2nEtPtd/EmZbuAkKYBKyq2V6dygYrz+UehZlZwYZze2xE9AA9g+2XtAB4zQC7PhcRPx1+dMPnRGFmVrANvcVN4RERh4zgsMeBHWu2d0hl5JQPypeezMwK1qy7nnJcBRwtaSNJOwO7AovIvkV0V0k7S/obsgHvq4Z6M/cozMwK1qzBbElHAv8BbAP8XNKSiDg0IpZJupxskHoDcHJE9hSgpFOA68i+cnp2RCwb6jxOFGZmBWviXU/zgfmD7DsbOHuA8muAa4ZznpZNFJLGR0RnzdVrZmOCJwUskKTjgFOBAO4BeoF1wN7AQknfBy4ENgF+C5wQEWsk3QT8BngnWRtOiIhFzW+BmdnLOVEURNIewOeBt0fE05K2Av6NbBT+7RHRK+ke4FMRcbOkM4EvAp9Jb7FJREyVdCAwG38ft5m1iN4+z/VUlIOBKyLiaYCI+FMqvyIlic2BLSLi5lR+CXBgzfHz0nG3AJtJ2qL+BLUPsvT0DHqbsplZofr6+hpe2kErjlE812C9+idaXvaES+2DLEGHTRBvZi2r0y49VdmjuBGYKenVAOnS019FxDPAGkkHpKJjgZtrqsxKx+0PPJPqm5lVrgWeoyhUZT2KdJ/v2cDNknqBuweo9lHgQkmbAA8D/1izb52ku4EJwAmlB2xm1qB2SQCNqvTSU0RcQjb2MNj+JcDbBtl9aUR8poSwzMxGpdMGs1txjMLMrK25R9ECImJ61TGYmQ3GicLMzHK1y22vjXKiMDMrmHsUZmaWy4nCzMxy+a4nMzPL5R6FmZnlcqIwM7NcnZYoFJ4rr3CSutOEhB2jE9sEndmuTmwTdG672kGVkwJ2su6qAyhBJ7YJOrNdndgm6Nx2tTwnCjMzy+VEYWZmuZwoytGJ11E7sU3Qme3qxDZB57ar5Xkw28zMcrlHYWZmuZwozMwslxOFjZik6ZLeXnUc1jhJcyTNSOsHSFomaYmkV1Qd20jVtsnK4URREElj8Sn36cCAiaLKn4cy/rc9tI8AX4mIqRHxv1UHY63L/5mGQdJxku6R9BtJP0h/yVwo6Xbga5KmSvp1qjNf0pbpuJskfSv95bZU0r4VNwVJkyU9IGmupPslXSlpE0lfkHRHirNHklL9T0u6L7XtMkmTgU8A/5zadUD9z6OC9iyX9H1gKfA9SYvTX8xn1NRbKekMSXdJulfSG1L5NpKuT/W/K+lRSVunfcdIWpTaeZGkria265WSfp7+zS2VNEvSmyXdLOlOSddJ2i7V3UXSglT3LkmvS0nz2+lnswDYNtX9GHAUcJakuc1qT5ltSvUH/HxtlCLCSwMLsAfwILB12t4KmANcDXSlsnuAd6b1M4FvpvWbgIvT+oHA0hZoz2QggHek7dnAqcBWNXV+AHwgrT8BbJTWt0ivXwJOran/kp9HBe3pA97W//mk1670898rba8EPpXWTwK+m9a/DZye1g9LP5utgTcCPwMmpH3nA8c1sV3/0P9vJ21vDvw3sE3angXMTuu3A0em9Y2BTYC/B65PP4ftgT8DM2o+rxkVfFZltmnAz9fL6JaxeLlkpA4GroiIpwEi4k/pj+0rIqJX0uZkv0BvTvUvAa6oOX5eOu4WSZtJ2iIi/ty88Ae0KiIWpvVLgU8Dj0j6f2T/IbcClpH9orwHmCvpJ8BPct7zioioajL+RyPi12n9KEndZBNfbgfsTtYGgB+n1zvJfukA7A8cCRAR10pak8rfBbwZuCN93q8AniqzEXXuBb4h6atkSXgNMAW4PsXTBTwp6VXApIiYn9qwDkDSgcC89Jk8IenGJsY+mLLbNNDna6PgRDF6zzVYr/6BlVZ4gGWgmM4H9omIVZK+RPZXHMDhZL2hDwCfk7TnIO/Z6M+jDM8BSNqZrHf0lohYI2kOL7YDYH167WXo/wMCLomI0wuOtSER8aCkacD7gC8DNwLLImK/2nrpl2pbaEKbhvP5WgM8RtG4G4GZkl4NIGmr2p0R8QywRtIBqehY4OaaKrPScfsDz6T6VdtJUv9/zg8Dv0rrT0vaFOi/O2YcsGNE/BL4LNmlgk2BtUAr/oLajCxpPCNpIvDeBo5ZSHbNHknvAbZM5TcAMyT1X9vfStLfFh/ywCRtD/wlIi4FzgXeCmzT/7lJmiBpj4hYC6yW9MFUvpGkTYBbgFmSutJ1/4OaFftgOrFNnc7ZtkERsUzS2cDNknqBuweo9lHgwvSP+WHgH2v2rZN0NzABOKH0gBuzHDhZ0mzgPuACsl+QS4HfAXekel3ApenymoDzIuLPkn4GXCnpCOBTTY9+EBHxm/SzfgBYRZYEhnIGME/SscBtZO1fGxFPS/o88IuUMF8ATgYeLSf6l9kTOFdSXzr3J4ENwHnp8xgPfJPsEuGxwEWSzkx1ZwLzyS6b3gc8ltpWtU5sU0fzFB5NIOkmskHfxVXH0k/ZXUtXR8SUqmNpBZI2AnojYkP6y/aCiJhacVhmLcE9CrPMTsDlqdfwPPBPFcdj1jLcozAzs1wezDYzs1xOFGZmlsuJwszMcnkw28aM9AzMDWnzNWQPZP0hbe8bEc9XEphZi/Ngto1J6anzZyPi61XHYtbqfOnJxjRJ75J0d5ppdHZ6nsLMajhR2Fi2MdkMqrMiYk+yS7GfrDQisxbkRGFjWRfwSEQ8mLYvIZv40MxqOFGYmVkuJwoby3qByZJ2Sdv1M/6aGU4UNratI5vh9wpJ95J9Q96F1YZk1np8e6yZmeVyj8LMzHI5UZiZWS4nCjMzy+VEYWZmuZwozMwslxOFmZnlcqIwM7Nc/x9viObAr2CpZwAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -302,9 +322,16 @@ }, "output_type": "display_data" }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "LinReg\n" + ] + }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -314,9 +341,16 @@ }, "output_type": "display_data" }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Random Forest\n" + ] + }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -329,9 +363,13 @@ ], "source": [ "sample = dataset.test_df.sample(frac=0.01, random_state=100)\n", - "create_heatmap(nnp, sample, title=\"Neural Net\")\n", - "create_heatmap(linreg, sample, title=\"Linear Regression\")\n", - "create_heatmap(forest, sample, title=\"Random Forest\")" + "fig_dir = Path(\"experiments/figures/no-overlap\")\n", + "print(\"Neural Net\")\n", + "create_heatmap(nnp, sample, save_path=fig_dir / \"nn-heatmap.png\")\n", + "print(\"LinReg\")\n", + "create_heatmap(linreg, sample, save_path=fig_dir / \"lr-heatmap.png\")\n", + "print(\"Random Forest\")\n", + "create_heatmap(forest, sample, save_path=fig_dir / \"rf-heatmap.png\")" ] }, { @@ -344,7 +382,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -360,18 +398,21 @@ " :param override_start_year: If not None, overrides the start year of the test data on the ALL region.\n", " (This is currently only used for the random forest)\n", " \"\"\"\n", + " countries_df = construct_countries_df()\n", + "\n", " save_dir = Path(save_path).parent\n", " save_dir.mkdir(parents=True, exist_ok=True)\n", " if not Path(save_path).exists():\n", " with open(save_path, \"w\") as f:\n", " f.write(\"region,eval,mae,time\\n\")\n", + " \n", " with open(save_path, \"a\") as f:\n", " # Iterate over all regions\n", " for train_region in constants.COUNTRY_DICT.keys():\n", " print(train_region)\n", " if train_region != \"ALL\":\n", " countries = constants.COUNTRY_DICT[train_region]\n", - " idx = constants.COUNTRIES_DF[constants.COUNTRIES_DF[\"abbrevs\"].isin(countries)].index.values\n", + " idx = countries_df[countries_df[\"abbrevs\"].isin(countries)].index.values\n", " train_region_df = train_df[train_df[\"country\"].isin(idx)]\n", " else:\n", " train_region_df = train_df\n", @@ -386,7 +427,7 @@ " for test_region in constants.COUNTRY_DICT.keys():\n", " if test_region != \"ALL\":\n", " countries = constants.COUNTRY_DICT[test_region]\n", - " idx = constants.COUNTRIES_DF[constants.COUNTRIES_DF[\"abbrevs\"].isin(countries)].index.values\n", + " idx = countries_df[countries_df[\"abbrevs\"].isin(countries)].index.values\n", " test_region_df = test_df[test_df[\"country\"].isin(idx)]\n", " else:\n", " test_region_df = test_df\n", @@ -406,18 +447,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EU\n" + ] + }, + { + "ename": "type", + "evalue": "module 'data.constants' has no attribute 'COUNTRIES_DF'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Input \u001b[0;32mIn [13]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m model_name \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrandom_forest\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 7\u001b[0m override_start_year \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m2002\u001b[39m\n\u001b[0;32m----> 8\u001b[0m \u001b[43mtrain_and_test\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m30\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel_constructor\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_df\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtest_df\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mexperiments/predictor_significance/\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mmodel_name\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_eval.csv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moverride_start_year\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moverride_start_year\u001b[49m\u001b[43m)\u001b[49m\n", + "Input \u001b[0;32mIn [12]\u001b[0m, in \u001b[0;36mtrain_and_test\u001b[0;34m(n, model_constructor, config, train_df, test_df, save_path, override_start_year)\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m train_region \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mALL\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 23\u001b[0m countries \u001b[38;5;241m=\u001b[39m constants\u001b[38;5;241m.\u001b[39mCOUNTRY_DICT[train_region]\n\u001b[0;32m---> 24\u001b[0m idx \u001b[38;5;241m=\u001b[39m \u001b[43mconstants\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mCOUNTRIES_DF\u001b[49m[constants\u001b[38;5;241m.\u001b[39mCOUNTRIES_DF[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mabbrevs\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39misin(countries)]\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mvalues\n\u001b[1;32m 25\u001b[0m train_region_df \u001b[38;5;241m=\u001b[39m train_df[train_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcountry\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39misin(idx)]\n\u001b[1;32m 26\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", + "\u001b[0;31mAttributeError\u001b[0m: module 'data.constants' has no attribute 'COUNTRIES_DF'" + ] + } + ], "source": [ "model_constructors = [NeuralNetPredictor, LinearRegressionPredictor, RandomForestPredictor]\n", "configs = [nn_config, linreg_config, forest_config]\n", "model_names = [\"neural_network\", \"linear_regression\", \"random_forest\"]\n", + "significance_path = Path(\"experiments/predictor_significance/no-overlap\")\n", "for model_constructor, config, model_name in zip(model_constructors, configs, model_names):\n", " override_start_year = None\n", " if model_name == \"random_forest\":\n", - " override_start_year = 2002\n", - " train_and_test(30, model_constructor, config, dataset.train_df, dataset.test_df, f\"experiments/predictor_significance/{model_name}_eval.csv\", override_start_year=override_start_year)" + " override_start_year = 1982\n", + " train_and_test(30, model_constructor, config, dataset.train_df, dataset.test_df, model_names / f\"{model_name}_eval.csv\", override_start_year=override_start_year)" ] }, { @@ -429,18 +491,18 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "linreg_results = pd.read_csv(\"experiments/predictor/significance/linear_regression_eval.csv\")\n", - "nn_results = pd.read_csv(\"experiments/predictor/significance/neural_network_eval.csv\")\n", - "forest_results = pd.read_csv(\"experiments/predictor_significance/random_forest_eval.csv\")" + "linreg_results = pd.read_csv(significance_path / \"linear_regression_eval.csv\")\n", + "forest_results = pd.read_csv(significance_path / \"random_forest_eval.csv\")\n", + "nn_results = pd.read_csv(significance_path / \"neural_network_eval.csv\")" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -472,7 +534,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -538,7 +600,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, "outputs": [ { diff --git a/use_cases/eluc/experiments/prescriptor_experiments.ipynb b/use_cases/eluc/experiments/prescriptor_experiments.ipynb index 889fa0c..78f7159 100644 --- a/use_cases/eluc/experiments/prescriptor_experiments.ipynb +++ b/use_cases/eluc/experiments/prescriptor_experiments.ipynb @@ -1,8 +1,16 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prescriptor Experiments\n", + "#### This notebook is to replicate the process used in [Discovering Effective Policies for Land-Use Planning](https://doi.org/10.48550/arXiv.2311.12304)" + ] + }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -24,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -40,11 +48,11 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ - "experiment_results_dir = Path(\"prescriptors/trained_prescriptors/LocTimeCropNoSoft/first_try\")\n", + "experiment_results_dir = Path(\"prescriptors/trained_prescriptors/no-overlap/seeded\")\n", "stats_file = experiment_results_dir / \"experiment_stats.csv\"\n", "with open(stats_file) as csv_file:\n", " stats_df = pd.read_csv(csv_file, sep=',')\n", @@ -55,6 +63,23 @@ "pareto_df = pareto_df.sort_values(by='change', ascending=True)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Figure Save Dir" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "figure_dir = Path(\"experiments/figures/no-overlap\")\n", + "figure_dir.mkdir(parents=True, exist_ok=True)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -64,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -132,7 +157,7 @@ " return pd.DataFrame(filtered_pareto_list)\n", "\n", "\n", - "def plot_gens(dir, gens, save=False):\n", + "def plot_gens(dir, gens, save_path=None):\n", " \"\"\"\n", " Plots the pareto front for multiple generations.\n", " :param dir: The experiment results directory.\n", @@ -165,19 +190,19 @@ " # plt.legend([handles[idx] for idx in order], [curve_names[idx] for idx in order], loc=\"upper right\")\n", " plt.legend(prop={'size': 9})\n", " #plt.title(\"Pareto Fronts Across Generations\")\n", - " if save:\n", - " plt.savefig(\"figures/pareto.png\", format=\"png\", dpi=300)\n", + " if save_path:\n", + " plt.savefig(save_path, format=\"png\", dpi=300)\n", " plt.show()" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 46, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -189,12 +214,12 @@ } ], "source": [ - "plot_gens(experiment_results_dir, [1, 3, 10, 25, 100], save=False)" + "plot_gens(experiment_results_dir, [1, 3, 10, 25, 100], save_path=figure_dir / \"pareto.png\")" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -216,11 +241,11 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ - "def plot_all_gens(dir, gens, save=False):\n", + "def plot_all_gens(dir, gens, save_path=None):\n", " all_gens_df = get_all_gens_df(gens)\n", " fig, ax = plt.subplots()\n", "\n", @@ -236,19 +261,19 @@ " plt.grid()\n", " #plt.title(\"All Generations All Prescriptor Performance\")\n", " plt.legend(loc=\"upper left\")\n", - " if save:\n", - " plt.savefig(\"figures/allgens.png\", format=\"png\", dpi=300) \n", + " if save_path:\n", + " plt.savefig(save_path, format=\"png\", dpi=300) \n", " plt.show()" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 45, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -260,12 +285,12 @@ } ], "source": [ - "plot_all_gens(experiment_results_dir, [a + 1 for a in range(100)], save=False)" + "plot_all_gens(experiment_results_dir, [a + 1 for a in range(100)], save_path=figure_dir/\"nn-global-allprescriptors.png\")" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -281,7 +306,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -324,7 +349,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -383,7 +408,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -412,22 +437,22 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 100/100 [29:18<00:00, 17.59s/it]" + "100%|██████████| 100/100 [26:41<00:00, 16.01s/it]" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "[-0.48221816699758446, -0.9394669421294041, -1.3743253790420253, -1.8001423494717983, -2.219820666832692, -2.635428801315339, -3.046544256552684, -3.4453552896636666, -3.82791888512053, -4.196727289448885, -4.55433987895778, -4.902874757589118, -5.243942582762411, -5.578078914458431, -5.906627517283578, -6.2302686359310675, -6.550814176207898, -6.868715558159256, -7.183615656936949, -7.4963909966997315, -7.807610002559771, -8.117324481332808, -8.426058085525238, -8.7335642521454, -9.039738755231769, -9.343899411829538, -9.64522472187804, -9.944320966657152, -10.241306116076517, -10.536105109432059, -10.828803332643037, -11.119465025419073, -11.407833084806235, -11.694504659960593, -11.979461674864682, -12.262013770975342, -12.542404426319623, -12.820567301295045, -13.096352615726905, -13.369904867955116, -13.64132677345688, -13.910494931220928, -14.177422679716337, -14.441737382444007, -14.703954113069376, -14.964176562482285, -15.222181254368392, -15.477992034299701, -15.731758301528789, -15.983276147184561, -16.23273259600758, -16.47924434349504, -16.722371179101927, -16.962171200140855, -17.200095484120173, -17.435927269133693, -17.668892931826313, -17.89970041046894, -18.12820123052949, -18.354461888576346, -18.578378394348718, -18.79925048885866, -19.01717139417806, -19.233018387793734, -19.446172192741642, -19.656466333419075, -19.86421081817296, -20.06916924117795, -20.272066719310278, -20.47270300931511, -20.670473122601745, -20.865345781162695, -21.057573021657827, -21.247157410136058, -21.434146531046753, -21.618444130177995, -21.80011113288847, -21.979056868057043, -22.15494144157595, -22.328029774724534, -22.497778640661128, -22.664110789693023, -22.826858258613267, -22.986273316813875, -23.141986489779164, -23.29354342700017, -23.440961427372834, -23.58397891345988, -23.721378651200965, -23.85180478388532, -23.97366705806352, -24.08938065227174, -24.197259233202956, -24.29915463448412, -24.395514889821364, -24.48518397044264, -24.56656818740624, -24.639182727743254, -24.70160654826107, -24.746922997717128]\n", - "[0.007039382013117479, 0.013738195629669386, 0.020255090788504605, 0.026644329773877366, 0.03293530051179128, 0.03914507494087962, 0.045282456710135095, 0.05135231693504686, 0.057355295106022344, 0.06330293888505625, 0.06919359285051917, 0.07502775531618423, 0.08081258173163539, 0.0865554553923633, 0.09225820280258258, 0.09792052113716546, 0.10354067848720808, 0.10911590671086832, 0.1146451889446625, 0.12013316731197575, 0.12558110625888835, 0.13098880597175494, 0.13636294213793396, 0.141701101483341, 0.14700434787194483, 0.15226762067081095, 0.15748613692235502, 0.16266823550164453, 0.16781390387511974, 0.17292193872862185, 0.17799472588991974, 0.183033075921016, 0.18803097932069415, 0.19299800521323265, 0.19793502238705463, 0.20283480799407835, 0.20770018592647876, 0.21253174647171916, 0.21732716700379973, 0.22209111038427318, 0.2268208983952696, 0.23151701555907597, 0.23617939023249518, 0.24080549699963325, 0.24540009165481821, 0.24996430326951188, 0.2544963903781835, 0.25899852641817517, 0.2634695667064151, 0.267905491669135, 0.2723106612523663, 0.27666646725451083, 0.2809560139892163, 0.2851832126519589, 0.2893783306906223, 0.2935414837540206, 0.2976635277727828, 0.30175375056656845, 0.30580862783355434, 0.30982649604590573, 0.3138052367857386, 0.3177288723917812, 0.32160115938025297, 0.32543665387938875, 0.32922422049575073, 0.33296581777069806, 0.33666462477313097, 0.3403165850208479, 0.3439354140681607, 0.34751687945142695, 0.35104779067629294, 0.3545353848313124, 0.3579813126955544, 0.36138295842099244, 0.3647451756081992, 0.36806708989940207, 0.37135267348825396, 0.37459925978036557, 0.3777998314184168, 0.3809593483008611, 0.38407060072695554, 0.3871338860287719, 0.3901448143419057, 0.39310439281021853, 0.39600944658041576, 0.39885263035145485, 0.4016321157222161, 0.4043415697831954, 0.40694800359365585, 0.40942011856810867, 0.41171604671193024, 0.41390642764793684, 0.41593728476489833, 0.4178645851374178, 0.41969668105904334, 0.42140647849239476, 0.42295111901898746, 0.4243219880326627, 0.42550818215941727, 0.42639864542863887]\n" + "[-0.48206266482358584, -0.9409444042635355, -1.3782062351394395, -1.806878662807132, -2.228964491783662, -2.6477243354361617, -3.063758621160394, -3.468247603129058, -3.8549186788172713, -4.227334377309296, -4.588455068508305, -4.940413895711438, -5.2854243526863, -5.623555500638125, -5.955634135326137, -6.282408771168965, -6.605644263041287, -6.926054640532445, -7.244047171054413, -7.56029148977495, -7.874781483013237, -8.187616254720032, -8.499246159073774, -8.809814010391106, -9.118811512406282, -9.426523617994404, -9.731939745165946, -10.035247772736911, -10.336511359906076, -10.635682694136825, -10.933138220921766, -11.228412533709943, -11.521391799497689, -11.811911954535114, -12.100224066031352, -12.386502958351523, -12.670342927452346, -12.952195723519091, -13.231905712936184, -13.5084952268275, -13.78277475854876, -14.054610024240683, -14.323917579499941, -14.590623459472614, -14.854971392157472, -15.116756362779912, -15.37610315062493, -15.633269682979725, -15.888222418798156, -16.14116422252196, -16.39209179623309, -16.640483466413066, -16.885642103747433, -17.128232407988055, -17.368746234059422, -17.60683767667953, -17.84272068554614, -18.076357123873123, -18.30774742932021, -18.536876418399565, -18.763519133972935, -18.98729755010484, -19.208494201014425, -19.42681453339456, -19.642093545254113, -19.854619350953566, -20.064313246664636, -20.27117985106269, -20.475566283735237, -20.67773088028986, -20.877146438094176, -21.073530386443238, -21.266882622612368, -21.457075370833667, -21.644326681618747, -21.82868508981037, -22.010580563728464, -22.190192037905547, -22.366683924947782, -22.540536164661198, -22.710962852526865, -22.878027369317664, -23.041237709357667, -23.200776954807164, -23.356787959146057, -23.509495950165316, -23.65839975235031, -23.80272672313677, -23.940996949218814, -24.072607311389227, -24.195923724764164, -24.312994900227125, -24.421622720671554, -24.524271627567657, -24.62091631461149, -24.710601390230636, -24.792010628774232, -24.86445641684605, -24.92635300868782, -24.97054456511505]\n", + "[0.007082472804506057, 0.013836349642834313, 0.020412460633914806, 0.026866756362000862, 0.03322311661959733, 0.03950105212258436, 0.04571565003895061, 0.05186551860340576, 0.05794207661604094, 0.06396448144266076, 0.06993344446559499, 0.07585414885243615, 0.08173084229251447, 0.08756786932235067, 0.09336101085218448, 0.09910826760132094, 0.10480589682549325, 0.11045860516606096, 0.11607427250325232, 0.12165281867888075, 0.12718840167923254, 0.13268407417499756, 0.13814175762545686, 0.14356328936494192, 0.14894457499845912, 0.15429340729476967, 0.15960257982107806, 0.16487591272322502, 0.17011266524359933, 0.17531225099440512, 0.18048276951156658, 0.1856147830926341, 0.19070792058642141, 0.1957610512954444, 0.2007746871618255, 0.20575676595665213, 0.2107020949600054, 0.21561706403586617, 0.22049675976731486, 0.22532780872604177, 0.2301231383463925, 0.2348840464467835, 0.23960948249270686, 0.24429928576905832, 0.24895375660955518, 0.25357213946344115, 0.25815541308951717, 0.26270697458139075, 0.2672272528951123, 0.27171696820353775, 0.2761785996371571, 0.28059437683463184, 0.28494294138376425, 0.28923867106858864, 0.2935002069780788, 0.29772506646931507, 0.30191638202002063, 0.3060728003974012, 0.3101930039997584, 0.3142749020592196, 0.3183148877849075, 0.3223036770900657, 0.3262459960808205, 0.33013962629175175, 0.3339823090529701, 0.3377811754633095, 0.34153443778063886, 0.3452408311421955, 0.3489074530737168, 0.3525348565948521, 0.3561124383806993, 0.35964193019791696, 0.36312461383273786, 0.36655862714270715, 0.36994954632755017, 0.3732990750947913, 0.3766135830072825, 0.37989292797843, 0.38312634254313066, 0.38632015816018705, 0.38946653280897026, 0.3925652922165837, 0.39560715658716133, 0.3985924176312011, 0.401526026891919, 0.4044088235271854, 0.40723183373471483, 0.40998153076153826, 0.4126217020715975, 0.41513341316156893, 0.4174697806035794, 0.419699310329914, 0.4217590576143633, 0.42371057105723914, 0.4255572907767793, 0.4272741673048171, 0.428826166376667, 0.4302034463195455, 0.43139587761592435, 0.43227518547135796]\n" ] }, { @@ -464,15 +489,15 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[110.70173 59.01831 -56.613754 22.683641 28.28591 -17.186794\n", - " 27.15772 70.575554]\n" + "[110.33926 58.705685 -56.392277 22.260334 27.738625 -16.832415\n", + " 26.697311 72.008316]\n" ] } ], @@ -484,29 +509,22 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/100 [00:00" ] @@ -810,26 +871,12 @@ } ], "source": [ - "print(even_elucs)\n", - "print(even_changes)\n", - "print(perfect_elucs)\n", - "print(perfect_changes)\n", - "print(trained_elucs)\n", - "print(trained_changes)\n", - "print(dict(zip(constants.DIFF_LAND_USE_COLS, coefs)))\n", - "plt.scatter(even_changes, even_elucs, color=\"green\", label=\"Even Heuristic\")\n", - "plt.scatter(perfect_changes, perfect_elucs, color=\"lightgreen\", label=\"Perfect Heuristic\")\n", - "plt.scatter(trained_changes, trained_elucs, color=\"red\", label=\"Evolved Prescriptors\")\n", - "plt.legend()\n", - "plt.xlabel(\"change\")\n", - "plt.ylabel(\"ELUC\")\n", - "#plt.savefig(\"figures/heuristics.png\", format=\"png\", dpi=300)\n", - "plt.show()" + "plot_result_pareto((even_changes, even_elucs), (perfect_changes, perfect_elucs), (trained_changes, trained_elucs), figure_dir / \"heuristics.png\")" ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -894,21 +941,48 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_result_pareto_hypervolume(even_results, perfect_results, trained_results_sorted, save_path=None):\n", + " even_changes, even_elucs = even_results\n", + " perfect_changes, perfect_elucs = perfect_results\n", + " trained_changes_sorted, trained_elucs_sorted = trained_results_sorted\n", + "\n", + " plt.scatter([0] + even_changes, [0] + even_elucs, color=\"green\", label=\"even heuristic forest\")\n", + " plt.scatter([0] + perfect_changes, [0] + perfect_elucs, color=\"lightgreen\", label=\"linreg \\\"perfect\\\" heuristic forest\")\n", + " plt.scatter([0] + trained_changes_sorted, [0] + trained_elucs_sorted, color=\"red\", label=\"trained\")\n", + " plt.legend()\n", + " plt.xlabel(\"change\")\n", + " plt.ylabel(\"ELUC\")\n", + " plt.xlim([0, 1])\n", + "\n", + " plt.axhline(0, color=\"black\", linestyle=\"--\")\n", + " plt.axhline(min([min(even_elucs), min(perfect_elucs), min(trained_elucs)]), color=\"black\", linestyle=\"--\")\n", + " plt.axvline(1, color=\"black\", linestyle=\"--\")\n", + " if save_path:\n", + " plt.savefig(save_path, format=\"png\", dpi=300)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "19.57749551115567\n", - "20.176138133868754\n", - "20.447397969763387\n" + "Even hypervolume: 19.68455968958801\n", + "Perfect hypervolume: 20.297778217752448\n", + "Trained hypervolume: 20.519663724794466\n" ] }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY8AAAEGCAYAAACdJRn3AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAA5I0lEQVR4nO3deXxU9b34/9ebsIZdwH4tS4IWCBIgGECBi6AgoCCKgEsDBTc2rdIrWBFQKqLeireg17D4A7FAKwJVQfBioUJVsG1QCoqAVQkEexXCIjEBsrx/f8zCJLNnkkwyeT8fj3kwc875nPnMyZB3zmd5f0RVMcYYY8JRI9oVMMYYU/VY8DDGGBM2Cx7GGGPCZsHDGGNM2Cx4GGOMCVvNaFegLDRv3lwTExOjXQ1jjKkyDh48SE5OzglVbVGa8jERPBITE8nIyIh2NYwxpsro378/O3bsyCxteWu2MsYYEzYLHsYYUw3NmjUrovIWPIwxphoaOHBgROUteBhjTDW0Z8+eiMpb8DDGmGpo6tSpEZWvtMFDRIaIyEER+ZeIPBbw4N27+bFpPHmXNIQaNSAxEVavrpiKGmNMNVQph+qKSBzwMnADkAX8Q0Q2qOp+f2Xqn867+CIzEyZMcDxPSyvPqhpjTLUklTElu4j0Auao6mDn6xkAqvqsr+MbimhqiW23A1MSEsjdv5+bbrrJq8z48eMZP348J06cYNSoUV77J0+ezB133MHRo0cZO3as1/5HHnmEm2++mYMHDzJx4kSv/bNmzWLgwIHs2bPH5+3hM888Q+/evdm5cyePP/641/4FCxaQkpLC1q1befrpp732L1myhA4dOrBx40ZeeOEFr/0rV66kdevWrFmzhkWLFnntX7duHc2bN2fFihWsWLHCa//mzZuJj48nPT2dN954w2v/9u3bAZg/fz7vvPNOsX316tXj3XffBWDu3Lls27at2P5mzZqxfv16AGbMmMGuXbuK7W/VqhWrVq0CHLfWJdtm27dvz9KlSwGYMGEChw4dKrY/JSWFBQsWADBmzBiysrKK7e/VqxfPPuv4Ko0cOZLs7Oxi+wcMGMDs2bMBuPHGG8nLyyu2f9iwYUybNg1wjJUv6fbbb2fKlCnk5ubad8++e8X2V6bv3s9+9jPOnDmzW1W7ex0YgsrabNUSOOrxOsu5zU1EJohIhohk5Ps7y5Ej5VQ9Y4yp3irrnccoYIiq3ud8PRa4WlUf9HV8dxH1Ob88IQEOHy63ehpjTFW1c+dO+vTpE3N3HseA1h6vWzm3hSyvdg0+nOR922aMMQZ69+4dUfnKGjz+AbQTkbYiUhu4E9gQqEBu03jyLqmPCvzQqilbF9zOh99/4Bh5ZSOwjDGmmJ07d0ZUvlKOtlLVAhF5ENgCxAHLVfVzf8d/2/kyXtnx62Lb2q/N4D8XH4Q8Z4+IjcAyxhg3X4MlwlFZ7zxQ1c2q2l5Vr1DVeYGOjasR57Wtz9xN1M4r0ZWemwvjxtmdiDHGRKhS3nmESxCvbQ2PnfJ9cGGh41+7EzHGmFKrtHce4WgU1wiKim8727Jp8IK5uTBzZvlUyhhjYlhMBI+6UpfBDQaTk5uDa+jxR7OHkl+vVvDCmaVeC8UYY6qtmAgeAEl1kigqKkLE0YR1aHR3ti64gx9aNUUF/M5mifPuLzHGmFjnmglfWjHR5+HSqH6jYq8Pje7OodHdUVUeavYrHz0jXOwDMcaYaiQlJSWi8jFz5wHQMK6hz+1FWsT/NffThJWQUI41MsaYymnr1q0RlY+p4NG7bm9q+riZiqsRx+6nRpJXu8THjY+HeQFHARtjTEzylfQyHDEVPJLqJDEgfoDPDo6v77yGTb+9hSNNBBUcdxxLl9owXWOMKYWYCh7gCCC+Ozcga+y1PHa9cqxJnCPj7syZNlHQGGNKIeaCB0DDGr77Ptqt/QfL3hFanSoEVccw3bFjYcqUCq6hMcZUbTEZPPz1ffR9+l3qXSjRpqUKixfbHYgxxoQhJoOHv74PvylLVG2muTGmWlmyZElE5WMyeIDvvo+AKUts1UFjTDXSoUOHiMrHbPAA776Pj2YPdYy08qFIxLLtGmOqjY0bN0ZUPqaDR8m+j0Oju/PPu/t4BRAFahQVXexEnzDBAogxJqa98MILEZWP6eDh6vvwTNm+Y/5o/nfxGHfOqwLxMbLXsu0aY0xAMR08wBFAtETP+aHR3Xl175MsPPE7avjLmGh9IMYY41fMBw/wP+8D4IeWjX3vaNOmnGpjjDFVX7UIHv7mfYgIu5642XvdD8t5ZYwxAVWL4OHq+/B1B+Ja9+N0y8YUAZmN4cPZ4yznlTEmpq1cuTKi8tUieIAjgNzT+B6f+w6N7s6KvXOImwOJv4LBRa/x4XNTHMN2bfiuMSYGtW7dOqLy1SZ4uPjr/yjSIq5qfxUAt+zO5aonFjuG7drwXWNMDFqzZk1E5atd8Ai05sedA+7kqvZX8cw2iM8vMQzLhu8aY2LIokWLIipf7YKHr7kfLrVr1WZY72G0OeOnsA3fNcYYoBoGD/A998OlacOmHPEzeteG7xpjjEO1DB4QuO/jlbQEfiy55LkN3zXGGLdqGzwC9X00efIBnrk/gcONoQg40kRs+K4xxnjw/u1ZTSTVSQLgvdz3vJqwateqTc1Hx9H20qecW5SEups5XLFVNMaYcrNu3TpatGhR6vLV9s4Dgvd93LUXvvkdFM6B7XMyHXM/jDEmBjRv3jyi8tU6eEDw9c4TzzguUuIZ6PbEIgsgxpiYsGLFiojKV/vgEc565/XzofVzi1i9zyYLGmOqtpgLHiIyR0SOicge5+Om8nw/f/M+/K133voMTNg4wQKIMaZaq3TBw+l3qprifGwu7zfz1ffhb73zI40hNz+XmdtstrkxpvqqrMGjwvla77xkqvYfa8HjAxzPM89k2t2HMabaqqzB40ER2Ssiy0XE5y2AiEwQkQwRyTh+/HjEb+hrvfOtC+5wL1d7umVj7r8Z/tjlYhlrvjLGVFei6m8d1nJ8U5GtwP/zsWsm8DFwAlBgLnCZqvrOpe7UvXt3zcjIiLheB84fYEvuFp/7VJVfvfQrr+0JjRM4PPVwxO9tjDEVKTc3l/r16+9W1e6lKR+VSYKqOjCU40TkFeCdcq6OW1KdJHae28nZorPube3XZtBn7iYaHjvF7c1qMe3a/GJ3H67mq7TONvvcGFN1xMfHR1S+0jVbichlHi9HAJ9V5Pt7Nl+1X5vBwKlraJR1ClH46Yl8lr0j3LW3eBlrvjLGVDXp6ekRla90wQP4rYjsE5G9wHWAd1tROfIcuttn7iZq5eUX21/vgvLMtuJlcvNzGffmOAsgxpgq44033oiofKXLbaWqY6Ndh6Q6SWzJ3eJ3rkebH7y3FWohEzZOALAmLGNMzKuMdx6VQsMaDf3O9Tjbsol7yVpPNv/DGFNdWPDwo3fd3nw8e7jXXI/8erXYOXsYw3oP81nO5n8YY6oDCx5+JNVJos24x4rN9fihVVO2LriDQ6O707RhU593H2Ad6MaY2BeVeR5lrazmefiy/MzyYkN3PV3Iv8Dr217nk0OfeO2z+R/GmMpOREo9z8PuPILwl3UXHItGBWq+MsaYWGXBIwjX0F1/mjb03akuiDVdGWMqrfnz50dU3oJHCJLqJPldNEoQUtunem1X1OZ+GGMqrXfeiSx5hwWPEPltvhK4Y8AdPjvPXXM/LIAYY2KNBY8Q+Vs0CgL3fdjcD2NMLLLgEQZfi0a5BBq6a3M/jDGxptKlJ6nsGtZoyNmis8Wy7Z5t2ZSPZg/lzlvvBPA5dNdSlxhjKpN69epFVN7uPMLUu25vOq79tFi23UZZpxg4dQ3Jb+3l5j43+yxnyRONMZXJu+++G1F5Cx5hSqqTxHXz/uyVbbdWXj595m6iaQP/zVfWgW6MiRUWPEqh1tF/+9zeMOsUCNw18C6/AcQ60I0xlcHcuXMjKm/BozTatPG9XRwLSNWqWctv8xVYB7oxJvq2bdsW/KAALHiUxrx5IN5DdkWhz9xNADRt0JQ4ifN7Cmu+MsZUZRY8SiMtDfwklHQvICWw5OdLiK/le51g60A3xlRlFjxKKyHB52bPBaSkhbD05qV+T2Ed6MaYqsqCR2nNmwfxxe8q8uvV4qPZQ92vzxadJbV9KgmNfQcasA50Y0x0NGvWLKLyFjxKKy0Nli6FhASvhaI8bcvdxuxhs/02X4F1oBtjKt769esjKm+LQZWBA+cPsC13GwUU+NzfsEZD6hypw7g3x1GohT6Pia8Vz9Kbl9oMdGNMhbHFoKIs2Jofruar10a8FrAD/eF3Hy6vKhpjTDEzZsyIqLwFjzISaM0PcDRfpbZPDdiBnp2Xbc1XxpgKsWvXrojKW/AoQ4GWrC2ggJ3ndpLWOS1gB7oN3zXGVAUWPMpQKM1XB84fYN6AeX6PseG7xpiqwIJHGQu1+apZPf/D5Gz4rjGmsrPgUQ78NV+1X5vB2C6z6VCvI4cXwPjPa/k9hw3fNcaUp1atWkVU3oJHOfDVfNV+bUaxNUAa/DubVzYKaXu9c2S5WPOVMaa8rFq1KqLyFjzKScnmqz5zN3mtAVLz3AUW77rE8l8ZY6ocW4a2HPWu29s9edCdMLGEBv93kqU3r2TMn8b43O/qQAdbwrYs5Ofnk5WVxblz56JdFWMqTN26dWnVqhW1al1sKp86dWpE54xK8BCR0cAcoCPQU1UzPPbNAO4FCoGHVHVLNOpYFpLqJAGwJXcLZ1s2pVGWdwDJb30ZaZ3TmLltJplnMn2ex9WBbsEjcllZWTRs2JDExETER1p9Y2KNqpKdnU1WVhZt27Z1b9+zZ09E541Ws9VnwG3AXz03isiVwJ1AJ2AIkC4SYFGMKsDVfPXR7KHk1yveQZ5frxbvz7zBPXzX8l+Vv3PnztGsWTMLHKbaEBGaNWtW5nfbUQkeqvqFqh70sesW4HVVPa+q3wD/AnpWbO3KXu+6vfl69DVsXXAHuU3jUUCBmnn53DDxNRJ/2oO0vbD05qW2gFQFsMBhqpvy+M5Xtg7zlsBRj9dZzm1eRGSCiGSISMbx48crpHKl5Tn6qnbOOQSKPeqezKHonrtJ24vlvzLGVAnlFjxEZKuIfObjcUtZnF9Vl6pqd1Xt3qJFi7I4ZblKqpNE36ffpWZ+kc/9NS7kk//4o6R1TrP8V6bMzJkzh/nz55fLuTds2MBzzz3nd/+ePXvYvHlzyMeXtHbtWjp27Mh1110XUT39OX36NOnp6eVy7qqgffv2EZUvt+ChqgNVNdnH4+0AxY4BrT1et3Juiwn1s04G3F/z6LcAlv+qElm9bzWJCxKp8ZsaJC5ItOvuVFBQwPDhw3nsscf8HlMyeAQ7vqRly5bxyiuv8P7774dcp3BU9+CxdKn/P1JDUdmarTYAd4pIHRFpC7QD/h7lOpUZadMm4P6zLZty4PwBAMt/VQms3reaCRsnkHkmE0XJPJNZJtd91apV9OzZk5SUFCZOnEhhYSGLFy9m+vTp7mNWrFjBgw8+6Pd4gAYNGjBz5ky6du3KNddcw3fffefz/fbv30///v25/PLLefHFFwPWw3Vel3Xr1jF+/HgAxo8fz6RJk7j66qt59NFHi9Vx7dq1JCcn07VrV6699louXLjAE088wZo1a0hJSWHNmjXFjv/uu+8YMWIEXbt2pWvXruzcubNYnZ966ik+/PBD7r33XqZPn865c+e4++676dy5M926dXMHlBUrVjB8+HCuv/56BgwYwI8//sg999xDz5496datG2+/7fhb9fPPP3d/1i5duvDll1/y2GOP8dVXX5GSklLs2psQqWqFP4AROPozzgPfAVs89s0EvgIOAjeGcr7U1FStElatUq1VSxW8Hvm143TzkjG67PQy9+HN/quZMge/j4TfJUTvs1RR+/fvD/nYhN8llPl1379/vw4bNkwvXLigqqqTJ0/W1157Tb///nu94oor3McNGTJEP/jgA7/Hq6oCumHDBlVVnT59us6dO9fr/Z588knt1auXnjt3To8fP66XXHKJXrhwIeB569ev7y6/du1aHTdunKqqjhs3TocOHaoFBQWqqvrqq6/qAw88oKqqycnJmpWVpaqqp06d8tpf8vXtt9+uv/vd71RVtaCgQE+fPu1V9379+uk//vEPVVWdP3++3n333aqq+sUXX2jr1q01Ly9PX331VW3ZsqVmZ2erquqMGTN05cqV7nq0a9dOc3Jy9MEHH9RVq1apqur58+c1NzdXv/nmG+3UqZPvH1QMKvndv//++xXI0FL+Ho/KPA9VfRN408++eYD/P7ursjTHPI2Chx4k7uRp9+Zzl9Rn+7MjHEvYOjPvJtVJYuGNC5mwcQK5+bk+T+cavmvzP8rHkTNHwtoeim3btrF792569OgBQF5eHpdeeiktWrTg8ssv5+OPP6Zdu3YcOHCAPn368PLLL/s8HqB27doMGzYMgNTUVP785z/7fM+hQ4dSp04d6tSpw6WXXsp3333ntx7BjB49mrg47xGBffr0Yfz48dx+++3cdtttQc/zl7/8hd///vcAxMXF0bhx44DHf/jhh/zyl78EICkpiYSEBA4dOgTADTfcwCWXXALAe++9x4YNG9z9POfOnePIkSP06tWLefPmkZWVxW233Ua7du2C1jHWua5fadkM84qWlkbNtDSWnF7COfU97npb7jbHoc6gEGj5Wpt9Xn7aNG7jc+Jmm8aBmx8DUVXGjRvHs88+67Xvzjvv5I033iApKYkRI0YgIgGPr1WrlnsIZlxcnN82/zp16rifu44LdF7PYZ0l5wbUr1/f53ssXryYv/3tb2zatInU1FR2797t87jy4FknVWX9+vV06NCh2DEdO3bk6quvZtOmTdx0000sWbKEyy+/vMLqGIsqW59HtdGvXr+gC0eBIyjY8N3o8DVxM75WfMD+qGAGDBjAunXr+P777wE4efIkmZmOADVixAjefvtt/vjHP3LnnXcGPT4Sgc77k5/8hC+++IKioiLefNNnA4GXr776iquvvpqnnnqKFi1acPToURo2bMjZs2f9vv+iRYsAKCws5MyZMwHP37dvX1avdvQ1HTp0iCNHjngFCIDBgwfz0ksvuZrA+fTTTwH4+uuvufzyy3nooYe45ZZb2Lt3b8D6meAseERJqAtHATZ8N0pc1z2hcQKCkNA4gaU3L43oLu/KK6/k6aefZtCgQXTp0oUbbriBf//73wA0bdqUjh07kpmZSc+ePYMeH4lA533uuecYNmwYvXv35rLLLgvpfNOnT6dz584kJyfTu3dvunbtynXXXcf+/fvdHeaeFi5cyPvvv0/nzp1JTU1l//79Ac8/ZcoUioqK6Ny5M3fccQcrVqwodkflMnv2bPLz8+nSpQudOnVi9uzZALzxxhskJyeTkpLCZ599xi9+8QuaNWtGnz59SE5Otg7zUhBXhK7KunfvrhkZGcEPrISWn1nO2SLff/3UpCYD4ge4c2QlLkj0m/8qTuJ4bcRr1nwVxBdffEHHjh2jXQ1jKlzJ7/7UqVNZuHDhblXtXprz2Z1HlIWy7rmLDd81xpSVBQsWRFQ+YPAQkedFZKKP7RNFJPSposavcJuvbPlaY0xlEOzO43rAV2P7K8Cwsq9O9RTKuueuALLwxoWWfdcYE7ExY3yvIRSqYMGjjvroFFHVIhw5/UwZCdZ89V7uexw4f8DdiWvZd40xkcjKyoqofLB5Hnki0k5Vv/TcKCLtgLyI3tkU47lwlC+Kes3/8DeB0LV8reexxhhTloLdeTwBvCsi40Wks/NxN7DJuc+UoWDNVyXnfwQavmsd6MaY8hQweKjqu8CtwHXACufjOmCkqm72W9CEZvVqSEyEGjUc/65eHbD5Cig2rDdY9l2bQFg5uRIPfvvtt4waNapC33vFihXMmTOHOXPmsGLFijI77/Tp0+nUqVOp5ks888wzxV4nJiZy+PBh+vfv73Xs9u3b3SlZylqwn0fJLLzh/vwOHDhASkoK3bp146uvvoqorv4sWLCA3Fzf6YzKWtChuqr6maqOU9VU5+MXqrqvIioX01avhgkTIDPTkRoxMxMmTCBp3W4GxA9AAnQpuTrPwfcsaE82gTAyB84fYPmZ5Sw8tZDlZ5YXu/aR+ulPf8q6devCKuPKfFtZuFKiLF26lL179/L888+HfY6SwSMaCgoKgv48SgaPcH9+b731FqNGjeLTTz/liiuuCHq8qlJU5Hv9H3/CCR69evUK69wlBRuqu1FENng83haRZSISWTe9gZkzoeQPOTcXZs4kqU4Sg+IH+S3q6jwHQupAt+G7pXPg/AG25W5z3+2dLTpbbORbpA4fPkxycjLguCO47bbbGDJkCO3atePRRx91H9egQQMeeeQRunbtyq5du/ymUl+2bBnt27enZ8+e3H///e70557q1atHgwYNaNCgAfXq1QOgf//+PPzww6SkpJCcnMzf/+5YBcFfevOSadCHDx9OTk4OqamprFmzhuPHjzNy5Eh69OhBjx49+OijjwDIyclxp1Xv0qUL69ev57HHHiMvL4+UlBTSnIlDW7RoQVxcnDvZYUk5OTmMGjWKpKQk0tLS3KlIdu/eTb9+/UhNTWXw4MHuGfP9+/fHNYn4xIkTJCYm+vwcnj+PUFK4ex5fWFjItGnTSE5OpkuXLrz00kvF6rx582YWLFjAokWL3Itb/fd//zfJyckkJye751wcPnyYDh068Itf/ILk5GSOHj3K888/T48ePejSpQtPPvmk+2czdOhQunbtSnJyMmvWrOHFF1/k22+/5brrrgtpAS1fec3CEijlLtDPx2MEsB54rrSpfMv6UWVSsnsS8ZmaXUXchyw4ucDv439O/o9+ce4L97Gr9q4KmL591d5V0fiUlU44KdmXnV7m89p7ps0vDVfKc8+U4K+++qq2bdtWT58+rXl5edqmTRs9cuSIqjpSr69Zs8Zdf1+p1I8dO6YJCQmanZ2tFy5c0P/4j/8olg49kH79+ul9992nqqo7duxw18lfevOSadA9P5Oq6l133aUffPCBqqpmZmZqUlKSqqo++uij+vDDD7uPO3nypFfZYN5//31t1KiRHj16VAsLC/Waa67RDz74QC9cuKC9evXS77//XlVVX3/9dXcKd8/U7sePH9eEhARVVa/P4fnzCCWFu+fr9PR0HTlypObn56uqFrs2Lk8++aQ+//zzqqqakZGhycnJmpOTo2fPntUrr7xSP/nkE/3mm29URHTXrl2qqrplyxa9//77taioSAsLC3Xo0KG6Y8cOXbdunftnpqrulPYJCQl6/Phxn9fO13ef8krJrqo7fG0XkQ3AbiD0ZcFMcW3aOJqqfG13alijod/UJa7Oc9corbTOaTz87sNk52X7PN6y74bP37X3tz1SAwYMcKcmv/LKK8nMzKR169bExcUxcuRIwH9K97///e/069fP/df66NGjw0q5fddddwFw7bXX8sMPP3D69Gm/6c2heBr0krZu3VosV9UPP/xATk4OW7du5fXXX3dvb9q0acj189SzZ09atWoFQEpKCocPH6ZJkyZ89tln3HDDDYDjTiCUvFz+Pke4Kdy3bt3KpEmTqFnT8SvV37Vx+fDDDxkxYoQ7I/Btt93GBx98wPDhw0lISOCaa64BHCnm33vvPbp16wY47rq+/PJL+vbtyyOPPMKvf/1rhg0bRt++fYN+1pJc36nSKlVKdlUt9EzbbEph3jxHn4dn01V8vGP76tUwcyZ3HznC2ZZN+Gj2UMdaHyWc9Vj7Awi4/ocN3w2fv+AdaERcJHylTgeoW7euew0N9ZNK/a233orovUv+f3alg/eV3vxvf/ub39TsAEVFRXz88cfUrVs3ojr54y/FfKdOndi1a5fX8TVr1nT3HYSaYv7nP/951FK4l0wxP2PGDCZO9Er0wSeffMLmzZuZNWsWAwYM4IknwhsAm53t+w/NUAXr87jEx+MKEfkN8HlE71zdpaXB0qWQkAAijn9dawo7O9JFlUZZpxg4dQ3t1/pO/OjZBm/Dd8uWr5FvNalJ77q9o1Qj/6nUe/TowY4dOzh16hQFBQWsX78+rPO6st5++OGHNG7cmMaNG/tNbx7MoEGDirX579mzB3D8lf/yyy+7t586dQpwrEuSn58fVn1L6tChA8ePH3cHj/z8fD7/3PErKjEx0b2+SKgd3OGmcL/hhhtYsmSJO+CfPHky4Pn79u3LW2+9RW5uLj/++CNvvvmmz7uHwYMHs3z5cnJycgA4duwY33//Pd9++y3x8fGMGTOG6dOn88knnwBUaJr5YKOtdgMZzn9dz/8I1AMmlW/VqoG0NDh8GIqKHP+mpfnsSK+Vl0+fuZt8nqKAArbnbr94Shu+W2ZcecdcdxoNazQsluU4GvylUm/ZsiWPP/44PXv2pE+fPiQmJgZdnc9T3bp16datG5MmTWLZsmWA//Tmwbz44otkZGTQpUsXrrzyShYvXgzArFmzOHXqlHutc9c65BMmTKBLly7uDvPSqF27NuvWrePXv/41Xbt2JSUlxb0u+rRp01i0aBHdunXjxIkTIZ0v3BTu9913H23atKFLly507dqVP/zhDwHPf9VVVzF+/Hh69uzJ1VdfzX333edumvI0aNAgfv7zn9OrVy86d+7MqFGjOHv2LPv27XN36P/mN79h1qxZgONaDhkyJKQO80iVOiW7iKxR1TvKuD6lUpVTsnupUcPRdV6CivBi9u/8FhscP9j9S231vtUBl68FWHXbqmrZfBXLKdlzcnJo0KABBQUFjBgxgnvuuYcRI0YELde/f3/mz59P9+6lysxtqoiS3/3+/fuzY8eOqKRkj2yQsPGtje8lTqVNm4Bt7Z6p20MZvjvuzXHWfBVj5syZ4x5u27ZtW2699dZoV8lUYgMG+M/mHYpI7jyOqGrpF3MuQzF15+GaPFhyDkizZhx74desG17bb1HPuw9w3IGM+ZP/KTnxteIjXhmvqonlOw9jAvH13ReR8rnzEJGr/DxSgVqleUMThKsjvVmJdTuys2k5ZQ6d1v3Tb9GSE9hCWf/D+j+MMaURrNnqBT+P+UDZ5WkwxaWlgTP/UTG5ufR7ektIqdtdgq3/YelLjKmebrzxxojKB5skWP5d9sY352Sskmod/TcD4geElLo9qU6Su0lq3JvjKFTfeZFmbptZrZqujDGOCaaRCNZs9ajH89El9kU/m1ks89NxTps2YaVuB0fz1WsjXvN7vK0+aIwJV7Bmqzs9ns8osW9IGdfFeJo3zzHj3JNrBjqBVx6E4mufQ/D+D5s8WDFKZmYN1U033cTp06fLpA4NfDWJGhOmYMFD/Dz39dqUpbQ0GDcOnGkpiItzvHZOpHJNYAuUur1kB3qg/g9X+hILICX4WHMlEv6Ch2tmsj+bN2+mSZMmEb23MWUpWPBQP899vTZlafVqeO01cK3fUFjoeO3xy8uVuj1QB3rJ2eeWviQMftZciSSAeKb17tGjB3379mX48OFceeWVANx6662kpqbSqVMnli69+LNKTEzkxIkTHD58mI4dO3L//ffTqVMnBg0a5G67/uqrrxgyZAipqan07duXAwccfzh888037hnKrpnIxkS6qFaw4NFVRH4QkbNAF+dz1+vOEb2zCSzAeh+eXHcg/pznvFfzlaUvCVGIP4NwPPfcc1xxxRXs2bOH559/nk8++YSFCxe6M+AuX76c3bt3k5GRwYsvvugzed2XX37JAw88wOeff06TJk3ceawmTJjASy+9xO7du5k/fz5TpkwB4OGHH2by5Mns27cvpEyzpnqYNm1aROWDLUMbp6qNVLWhqtZ0Pne9tnke5cnPaCsyM73+8g3WgV5y+K6tPhgifz8Df9tLoWfPnrRt29b9+sUXX6Rr165cc801HD16lC+//NKrTNu2bUlJSQEgNTWVw4cPk5OTw86dOxk9erR7kSjXYkgfffSRO+X62LFjy6zupnorVUp2UwH8rfcBMHYsfPQReLSd967bu0yH71r6dkJacyVSnum3t2/fztatW9m1axfx8fH079/fK4U4eKckz8vLo6ioiCZNmrgz2JZkSyiYknytER+OSHJblZqIjBaRz0WkSES6e2xPFJE8EdnjfCyORv0qBV+jrVxUYfFir/6PuuJ//YRwh+9a/wdBR7yVRqCU2WfOnKFp06bEx8dz4MABPv7445DP26hRI9q2bcvatWsBxzoQ//ynIxtBnz593IswrY6ww98Yl6gED+Az4Dbgrz72faWqKc5H9U377kpT4o+qV9t7v3r9ynT4brXv//C35koEqcMDpfUeMmQIBQUFdOzYkccee8y9mlyoVq9ezbJly+jatSudOnVyrzm+cOFCXn75ZTp37syxY8dKXXdjPJU6MWKZvLnIdmCaqmY4XycC76hqcjjnianEiCUlJvpvvhJxrAXi4cD5A7yX+x7qZzBcTWoWW5OiuqVvt8SIprqqTCnZy0tbEflURHaIiN+FeUVkgohkiEjG8ePHK7J+FWvePEeQ8MVH23tph+9a+nZjTDjKLXiIyFYR+czH45YAxf4NtFHVbsB/An8QkUa+DlTVparaXVW7t2jRojw+QuWQlgaTJnkHkABt76UZvmv9H8ZUL7fffntE5csteKjqQFVN9vF4O0CZ86qa7Xy+G/gKaF9edawy0tNh5cqw2t7DHb5bnfo/otlUa0w0+PrOu+YBlValarYSkRYijvYTEbkcaAd8Hd1aVRKu9c5XrnS8Hjs2aLqM3nV7+93nGr5b3dK3161bl+zsbAsgptpQVbKzs6lbt/hozNySE2DDFJV5HiIyAngJaAFsEpE9qjoYuBZ4SkTygSJgkqqejEYdK6WSqwy60mWAz7uQpDpJ7MjbwTn1nisAF/s/XJ3n1WH+R6tWrcjKyiKm+8mMKaFu3bq0atWq2LabbroponNGdbRVWYnp0Vae/I28Skhw3JX4cOD8AbblbqMA/4n3bPlaY6qfWBxtZfwpRbqMULLvek4ehOrV/2GMKR0LHlVJgAWiAnEN3/Wn5ORBqB79H8aY0rPgUZX4Spch4mjKCtJ5Hix9ScnOc5v/YYwJxIJHVeKZLgMcgcPVZxXCWhOB0pcUUOBz+K7N/zAmNo0fPz6i8tZhXlWVovMcHB3o/rLvgnf6EoDmv21Odp73uhIuzeo148SjJ0KptTGmEhER6zCvdkq51kSwyYMl05eA9X8YE4tOnIjsDz4LHlVVKTvPwTF5MFD2XV/pS6z/w5jYMmrUqIjKW/CoqiJYayKU4bvW/2GMCcSCR1UVaK2J1asdfSI1avgdhRVs+K6v9CU2/8MY42LBoypz5bsqKnL86wocEyY4OtNVA47CCmX1Qev/MMb4YsEj1syceTH3lUturteqgy7BVh+0/g9jjC8WPGKNv9FWmZl+7z6s/8OY6mfy5MkRlbfgEWsCjbYK0Hxl/R/GVC933HFHROUteMQaX6OwXHJz4WHfv9DLq/9jyqbIFpwxxpSPo0ePRlTegkescY3C8ic7228Kk/Lo/1icsdiar4yphMaOHRtReQsesSgtDeL8/0Jn3LgK6/9Q1DrQjYlBFjxiVaHvlQDd+yLo/9iSu4W/5PzFvS1Y/4d1oBsTeyx4xCpX5l1/AgzfDdb/AbAvf5/X+ueB7lisA92Y2GLBI1bNmwe1agU+JjMTGjSA5s29ZqMH6/+A4k1YaZ3TmNR9UsAAYhMIjYkdFjxiVVoavPoqNPPfnATAjz86OtFLzEYPpf+j5BDe9KHprLxtpU0gNKYKeOSRRyIqb+t5VAfiPwD45LEmSLD1PwDqUIdJTSe5X6/et5oxfxrj9/j4WvEsvXkpaZ3TwquXMaZM2XoeJrBg/R8lecxST6qTROdanQMe7msIr00gNKZyO3jwYETlLXhUB4EmDvpyySXFXl7f4HoGxw8OawivJVA0pnKbOHFiROUteFQHromDwfo/XM6e9RrGG24Kk1AmENrdhzFVlwWP6iItDU6cgFWrigcRX/0hFy74nEgYbgqTYBMIs/Oyaf7b5nYHYkwVZMGjunEFEVXHw5/CQhg7FqYUz00VSgqTJaeXFLsDCdT/kZ2XbRMIjamCLHhUd4Gy8KrCokWOeSDOu5BQhvCe03PFmrAW3rgwYBWsA92YqseCR3UXSmd6djbcfbd7MmFShyGM3HA+YBHPJqxgdx9gHejGVLRZs2ZFVN6CR3Xn6kwPlEgRID+/2GTCllPm0GndPwMW8RzCG2z0FVgHujEVaeDAgRGVt+BhHAHktdfCm0yYm0u/p7cETWHiefex9OalQfs/bP0PYyrGnj17IiofleAhIs+LyAER2Ssib4pIE499M0TkXyJyUEQGR6N+1VJaGkyaFFYAqXXkW27dkEsd6vg9xrMDPa1zGicePREwgNj6H8ZUjKlTp0ZUPlp3Hn8GklW1C3AImAEgIlcCdwKdgCFAukiAiQKmbKWnw8qVoc8HAVqOf5RJM/cGHMIbTge6rf9hTNUQleChqu+paoHz5cdAK+fzW4DXVfW8qn4D/AvoGY06Vlue80ESEhx3Is2aQe3a/sssWsS9P3uM9mv95xcLpwPd1v8wpvKrDH0e9wDvOp+3BDwX1s1ybjMVLS3NkRyxqMgRTJYvD3h4zezTDJm4igcum+Y3iHg2Ydn6H8ZUbeUWPERkq4h85uNxi8cxM4ECIOw/MUVkgohkiEjG8ePHy7Lqxpe04BlwBah5voDBU/7gN4C4mrBS26eGtP6HdaAbUzmVW/BQ1YGqmuzj8TaAiIwHhgFpejEv/DGgtcdpWjm3+Tr/UlXtrqrdW7RoUV4fw3gKsS+kRmERQyauot+0tT73u5qwQln/wzrQjSkfzzzzTETlozXaagjwKDBcVXM9dm0A7hSROiLSFmgH/D0adTQ+LFwYfD6IkwBdl3/EQ5dM5e4uv/G6EznPef6S85eg+a8UteYrY8pB7969IyofrT6P/wEaAn8WkT0ishhAVT8H3gD2A/8LPKCqhVGqoynJNR8kxDsQcT4aZZ1iyMRVXoHEtQ56KPmv7O7DmLK1c+fOiMrbSoKm9AYOhG3bwi6mQGa/drz95gMIwqD4Qew+tJuxfxqL4vv7GCdxvDbiNVt90Jgy0r9/f3bs2GErCZoo2LoVJk8Oe5lbARJ2fEm/aWtRlC25W7is7WVM6j7Jb5lCLWTsn8ZaB7oxlYQFDxOZ9HTHcN7Jk8MqJkCX13a5X+/L38dDAx8K2HylqHWgG1NJWPAwZSM9HQYMCKuIFBYV60jfnrs9aAJF60A3pnKw4GHKztat3isVBiDAoCmr3QHkPOe5rO1lQZevtfkfxkSfBQ9Ttvwtd+tHXKHS77E/uV/vy99HTusclvx8ScAJhNZ8ZUxkFixYEFF5Cx6mfIS63C1Q71Rusdfn9Bznmp1j+pDpfstY85UxkUlJSYmovAUPUzESEgLufqhZ8TkgBRTQtn1bW//DmHKydevWiMrbPA9TMVavhjFjgh6mAiicbdWUj2YPJXNIH6a8OsXv/A+Ayd0nkz40vQwra0zss3kepmpISwtpOK/oxVnpA6euIeF/P+KJ0U8ELGP9H8ZUPAsepuKkpxdfJySIWnn5DJm0iqs//Ip598/jqvZX+TzOFpAypuJZ8DAVy3OdkCD9IOC4Exk85Q90e+cLxg4ey239bvN5nM1AN6ZiWfAw0TNvHsT7nxDoUqOwiMFT/kCHdbvp26Wv3wBiM9CNqTjWYW6ia/VqmDkTMjNRCDCzA3eX+dlWTfmv4Y145tJMn8c1q9eME4+eKOuaGhNTDh48SFJSknWYmyrK1YylitQI/HX0TPH+m1eOctde38fZEF5jguvQoUNE5S14mMpj4sSQD62ZX8SirbX87l+UscgCiDEBbNy4MaLyFjxM5ZGeHlaK90Y/5LPp07Z+91v/hzH+vfDCCxGVt+BhKhdXivdVq4IGEQFufPsbzs+r4bMJy1KYGFN+LHiYyiktDSZNCimA1M4v4vcb43j8e++hv9b/YUz5sOBhKq/0dFi5koJLmgRITuJQM7+Qp9Mz+WRDc6991v9hTNmz4GEqt7Q0amafYv+yGUEDiAApn5zg9OKGXrPRLYAYU7YseJgqodM9z5B13/CQAkij/zvL/z51zGsyoXWgG3PRypUrIypvkwRNlZJ9XSqXbP8k4GRCuDih8PhP6jG1Tx5/7OJ4bRMIjblIRGySoKkemr2/m29X/Ja8pvUD3oW4JhRe+l0ev38T92gs60A3xmHNmjURlbfgYaqcluOmU+9kDif7XxW0GQugpsLqP10MIIsyFlnzlan2Fi1aFFF5Cx6mymr2/m7O/bRZSAFEcASQNR86ViacuDH02ezGGG8WPEyVVu/YCc53vCLkADJ6azabPm3Lj/k/WvOVMRGw4GGqvLr7/4VMnkxRXI2QRmPd+PY37Fxb34bvGhMBCx4mNqSnU6OgMOThvNd8/iNFc+CWXy5i4O8HVkAFjYktFjxMTGn9ytvkdEwIKYAIMOgbmPvbjy2AmGpn3bp1EZW34GFiTsP9h0MeieW6C/nTlO02AstUK82be6fyCYcFDxOTXPNBzsfXCukupOGPhdzVZUxFVM2YSmHFihURlY9K8BCR50XkgIjsFZE3RaSJc3uiiOSJyB7nY3E06mdiQ8tx0/nm5F4y+7ULuRmrKMS1RIyp6qpk8AD+DCSrahfgEDDDY99XqprifEyKTvVMrEiqk8TX7yy2AGJMGasZjTdV1fc8Xn4MjIrkfAcPHqR///7Ftt1+++1MmTKF3NxcbrrpJq8y48ePZ/z48Zw4cYJRo7zffvLkydxxxx0cPXqUsWPHeu1/5JFHuPnmmzl48CATfSyfOmvWLAYOHMiePXuYOnWq1/5nnnmG3r17s3PnTh5//HGv/QsWLCAlJYWtW7fy9NNPe+1fsmQJHTp0YOPGjT5XBFu5ciWtW7dmzZo1PmeSrlu3jubNm7NixQqff4Fs3ryZ+Ph40tPTeeONN7z2b9++HYD58+fzzjvvFNtXr1493n33XQDmzp3Ltm3biu1v1qwZ69evB2DGjBns2rWr2P5WrVqxatUqAKZOncqePXuK7W/fvj1Lly4FYMKECRw6dKjY/pSUFBYsWADAmDFjyMrKIreoCTUa16PumTx6Ac86jx0JZJf4bNcDTzif33jjjeTl5RXbP2zYMKZNmwbg9b0D++7Zd28BcPG756lXr148+6zj2zdy5Eiys4t/+wYMGMDs2bOB8v/ulfxs4aoMfR73AO96vG4rIp+KyA4R6euvkIhMEJEMEcnIz88v/1qaKi2+Rjx1U3qS37hBSB3pxpjAyi2rrohsBf6fj10zVfVt5zEzge7AbaqqIlIHaKCq2SKSCrwFdFLVHwK9l2XVNeH4fPnjdLz3WXczVUkKSAxkmzYmkP79+7Njx45SZ9WNWkp2ERkPTAQGqGqun2O2A9NUNWBksOBhwnXg/AHa1+3oFUDU+ahhwcPEuNzcXOrXr1+1UrKLyBDgUWC4Z+AQkRYiEud8fjnQDvg6GnU0sS2pThI1VN3BwvNhgcNUB/Hx8RGVj0qHOfA/QB3gz+IY2fKxc2TVtcBTIpIPFAGTVPVklOpoqoGSgcLGWZnqIj09PaLy0Rpt9TM/29cD6yu4OsYYU+34GskWjsow2soYY0wVY8HDGGNM2Cx4GGOMCZsFD2OMMWGL2jyPsiQiZ4GD0a5HJdEcOBHtSlQSdi0usmtxkV2LizqoasPSFIzWUN2ydrC0E11ijYhk2LVwsGtxkV2Li+xaXCQipZ5dbc1WxhhjwmbBwxhjTNhiJXgsjXYFKhG7FhfZtbjIrsVFdi0uKvW1iIkOc2OMMRUrVu48jDHGVCALHsYYY8JWpYKHiAwRkYMi8i8ReczH/joissa5/28ikhiFalaIEK7Ff4rIfhHZKyLbRCQhGvWsCMGuhcdxI0VERSRmh2mGci1E5Hbnd+NzEflDRdexooTwf6SNiLzvXLl0r4h4r9saA0RkuYh8LyKf+dkvIvKi8zrtFZGrQjqxqlaJBxAHfAVcDtQG/glcWeKYKcBi5/M7gTXRrncUr8V1QLzz+eTqfC2cxzUE/gp8DHSPdr2j+L1oB3wKNHW+vjTa9Y7itVgKTHY+vxI4HO16l9O1uBa4CvjMz/6bcCwFLsA1wN9COW9VuvPoCfxLVb9W1QvA68AtJY65BXjN+XwdMECcC4bEmKDXQlXf14sLbX0MtKrgOlaUUL4XAHOB/wLOVWTlKlgo1+J+4GVVPQWgqt9XcB0rSijXQoFGzueNgW8rsH4VRlX/CgRaF+kW4Pfq8DHQREQuC3beqhQ8WgJHPV5nObf5PEZVC4AzQLMKqV3FCuVaeLoXx18WsSjotXDehrdW1U0VWbEoCOV70R5oLyIficjHzlU9Y1Eo12IOMEZEsoDNwC8rpmqVTri/T4DYSU9i/BCRMUB3oF+06xINIlID+G9gfJSrUlnUxNF01R/H3ehfRaSzqp6OZqWi5C5ghaq+ICK9gJUikqyqRdGuWFVQle48jgGtPV63cm7zeYyI1MRxK5pdIbWrWKFcC0RkIDATx1rx5yuobhUt2LVoCCQD20XkMI423Q0x2mkeyvciC9igqvmq+g1wCEcwiTWhXIt7gTcAVHUXUBdH0sTqJqTfJyVVpeDxD6CdiLQVkdo4OsQ3lDhmAzDO+XwU8Bd19gjFmKDXQkS6AUtwBI5YbdeGINdCVc+oanNVTVTVRBz9P8NVtdQJ4SqxUP6PvIXjrgMRaY6jGevrCqxjRQnlWhwBBgCISEccweN4hdayctgA/MI56uoa4Iyq/jtYoSrTbKWqBSLyILAFx0iK5ar6uYg8BWSo6gZgGY5bz3/h6CC6M3o1Lj8hXovngQbAWueYgSOqOjxqlS4nIV6LaiHEa7EFGCQi+4FCYLqqxtzdeYjX4hHgFRH5FY7O8/Gx+MemiPwRxx8MzZ39O08CtQBUdTGO/p6bgH8BucDdIZ03Bq+VMcaYclaVmq2MMcZUEhY8jDHGhM2ChzHGmLBZ8DDGGBM2Cx7GGGPCZsHDmDCIyAoRGRXtehgTbRY8jDHGhM2ChzEBiMgvnGsc/FNEVjo3XysiO0Xka9ddiIg0cK6b8omI7BORW5zbE0XkCxF5xbl+xnsiUs+5r4fz3HtE5HnXegsiEud8/Q/n/olR+fDGBGDBwxg/RKQTMAu4XlW7Ag87d10G/AcwDHjOue0cMEJVr8KxlsoLHssBtMORBr0TcBoY6dz+KjBRVVNwzPZ2uRdHiogeQA/gfhFpW/af0JjSqzLpSYyJguuBtap6AkBVTzrjwVvOzKv7ReQnzmMFeEZErgWKcKS0du37RlX3OJ/vBhJFpAnQ0JmQD+APOIIRwCCgi0ffSmMcAeibsv+IxpSOBQ9jwueZodh1d5EGtABSVTXfmcG3ro/jC4F6Qc4vwC9VdUsZ1NWYcmHNVsb49xdgtIg0AxCRSwIc2xj43hk4rgMCrhnvXD/jrIhc7dzkmcRzCzBZRGo537e9iNQv5WcwplzYnYcxfjizsM4DdohIIY61v/1ZDWwUkX1ABnAghLe4F0dW1yJgB46VLwH+PyAR+MTZb3IcuLVUH8KYcmJZdY2JEhFpoKo5zuePAZep6sNBihlTKdidhzHRM1REZuD4f5iJLZVrqhC78zDGGBM26zA3xhgTNgsexhhjwmbBwxhjTNgseBhjjAmbBQ9jjDFh+/8Be3+A+2egH78AAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -925,25 +999,17 @@ "trained_changes_filtered = [trained_changes[i] for i in idxs]\n", "trained_elucs_filtered = [trained_elucs[i] for i in idxs]\n", "\n", - "print(two_dim_decreasing_neg_hypervolume(even_changes, even_elucs))\n", - "print(two_dim_decreasing_neg_hypervolume(perfect_changes, perfect_elucs))\n", - "print(two_dim_decreasing_neg_hypervolume(trained_changes_filtered, trained_elucs_filtered))\n", + "print(f\"Even hypervolume: {two_dim_decreasing_neg_hypervolume(even_changes, even_elucs)}\")\n", + "print(f\"Perfect hypervolume: {two_dim_decreasing_neg_hypervolume(perfect_changes, perfect_elucs)}\")\n", + "print(f\"Trained hypervolume: {two_dim_decreasing_neg_hypervolume(trained_changes_filtered, trained_elucs_filtered)}\")\n", "\n", + "# Sort filtered points\n", "trained_changes_sorted = sorted(trained_changes_filtered)\n", "trained_elucs_sorted = [trained_elucs_filtered[trained_changes_filtered.index(change)] for change in trained_changes_sorted]\n", "\n", - "plt.scatter([0] + even_changes, [0] + even_elucs, color=\"green\", label=\"even heuristic forest\")\n", - "plt.scatter([0] + perfect_changes, [0] + perfect_elucs, color=\"lightgreen\", label=\"linreg \\\"perfect\\\" heuristic forest\")\n", - "plt.scatter([0] + trained_changes_sorted, [0] + trained_elucs_sorted, color=\"red\", label=\"trained\")\n", - "plt.legend()\n", - "plt.xlabel(\"change\")\n", - "plt.ylabel(\"ELUC\")\n", - "plt.xlim([0, 1])\n", - "\n", - "plt.axhline(0, color=\"black\", linestyle=\"--\")\n", - "plt.axhline(min([min(even_elucs), min(perfect_elucs), min(trained_elucs)]), color=\"black\", linestyle=\"--\")\n", - "plt.axvline(1, color=\"black\", linestyle=\"--\")\n", - "plt.show()" + "plot_result_pareto_hypervolume((even_changes, even_elucs), \n", + " (perfect_changes, perfect_elucs), \n", + " (trained_changes_sorted, trained_elucs_sorted))" ] }, { @@ -955,21 +1021,62 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "def get_idx_close(change, changes):\n", + " diff = [abs(c - change) for c in changes]\n", + " idx = diff.index(min(diff))\n", + " return idx\n", + "\n", + "def plot_selected_points(pct, even_results, perfect_results, trained_results_sorted, save_path=None):\n", + " even_changes, even_elucs = even_results\n", + " perfect_changes, perfect_elucs = perfect_results\n", + " trained_changes_sorted, trained_elucs_sorted = trained_results_sorted\n", + "\n", + " even_idx = get_idx_close(pct, even_changes)\n", + " perfect_idx = get_idx_close(pct, perfect_changes)\n", + " # Subtract 1 so that we get a dominating point\n", + " trained_idx = get_idx_close(pct, trained_changes_sorted) - 1\n", + "\n", + " print(f\"Even {even_idx}: {even_changes[even_idx]}, {even_elucs[even_idx]}\")\n", + " print(f\"Perfect {perfect_idx}: {perfect_changes[perfect_idx]}, {perfect_elucs[perfect_idx]}\")\n", + " print(f\"Trained {trained_idx}: {trained_changes_sorted[trained_idx]}, {trained_elucs_sorted[trained_idx]}\")\n", + "\n", + " plt.scatter([even_changes[even_idx]], [even_elucs[even_idx]], color=\"green\", label=\"Even Heuristic\")\n", + " plt.scatter([perfect_changes[perfect_idx]], [perfect_elucs[perfect_idx]], color=\"lightgreen\", label=\"Perfect Heuristic\")\n", + " plt.scatter([trained_changes_sorted[trained_idx]], [trained_elucs_sorted[trained_idx]], color=\"red\", label=\"Evolved Prescriptor\")\n", + " plt.legend()\n", + " plt.xlabel(\"change\")\n", + " plt.ylabel(\"ELUC\")\n", + " plt.xlim([0, 0.4])\n", + " plt.ylim([-25, 0])\n", + " #plt.title(\"Average Change vs. ELUC for ~20% change prescriptors\")\n", + " if save_path:\n", + " plt.savefig(save_path, format=\"png\", dpi=300)\n", + " plt.show()\n", + "\n", + " return even_idx, perfect_idx, trained_idx" + ] + }, + { + "cell_type": "code", + "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "34 0.19793502238705463 -11.979461674864682\n", - "34 0.19793502238705463 -14.05574760275695\n", - "25 0.1894858919523161 -16.040059821432553\n" + "Even 34: 0.2007746871618255, -12.100224066031352\n", + "Perfect 34: 0.2007746871618255, -14.209159078539777\n", + "Trained 23: 0.19161835834498558, -16.42003604121471\n" ] }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZIAAAEKCAYAAAA4t9PUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAAhUElEQVR4nO3de3RU9d3v8fc3BEnBHAVlnaKACX0UJFcgoKCAiAitPKJcltTY1kuNtNbbqVY4abV9aloUW7VFq+iinKNRsFgrlKIWVOgpUhsohXCriIigfQiIGK6G5Hv+mMk4hNx3JjOBz2utWez57ds3GyYf9v7N/m1zd0RERJorKd4FiIhI26YgERGRQBQkIiISiIJEREQCUZCIiEggChIREQkkYYPEzMaY2WYz22JmU+Ndj4iI1M4S8T4SM2sH/AsYBewA/g583d03xLUwERE5TqKekQwCtrj7Vnf/HJgLjItzTSIiUovkeBdQh7OBD6Pe7wAuiF7AzAqAAoBOnToN6NOnT+tVJyJyAli1atVud+8adDuJGiQNcvdZwCyAvLw8LykpiXNFIiJti5l90BLbSdRLWzuBHlHvu4fbREQkwSRqkPwdONfM0s3sFGAysCDONYmISC0S8tKWux81s+8BrwHtgNnuvj7OZYmISC0SMkgA3P1PwJ/iXYdIW1VRUcGOHTs4fPhwvEuROEtJSaF79+60b98+JttP2CARkWB27NhBamoqaWlpmFm8y5E4cXf27NnDjh07SE9Pj8k+ErWPREQCOnz4MGeccYZC5CRnZpxxxhkxPTNVkIicwBQiArH/d6AgERGRQBQkIhIz7dq1Izc3N/KaPn16zPb11ltvMXbs2GParr/+eubPn98i2//oo4+YOHFinfM//fRTnnjiiUYvfyJRZ7uIxMyXvvQl1qxZE+8yAjt69ChnnXVWvaFUHSTf/e53ARpc/kSiMxIRAaB4XTFpj6aR9JMk0h5No3hdcUz28+qrrzJp0qTI++gziddff53BgwfTv39/Jk2axP79+wFIS0vj/vvvp3///mRlZbFp06Ym73fVqlUMHz6cAQMGMHr0aD7++GMALrnkEqqHWNq9ezdpaWkAzJkzhyuvvJJLL72UkSNHsm3bNjIzMwFYv349gwYNIjc3l+zsbN59912mTp3Ke++9R25uLvfcc88xy1dWVnL33XeTmZlJdnY2v/71r5t38BKUzkhEhOJ1xRQsLOBgxUEAPtj3AQULCwDIz8pv9nYPHTpEbm5u5P20adOYMGECBQUFHDhwgE6dOjFv3jwmT57M7t27eeCBB1iyZAmdOnXiwQcf5Je//CX33XcfAGeeeSarV6/miSee4OGHH+aZZ545bn9/+ctfjtnf9u3bGTt2LBUVFdx222288sordO3alXnz5lFYWMjs2bPrrX/16tWsXbuWLl26sG3btkj7k08+yR133EF+fj6ff/45lZWVTJ8+ndLS0sgZWPTys2bNYtu2baxZs4bk5GQ++eSTJh/LRKYgEREKlxZGQqTawYqDFC4tDBQkdV3aGjNmDAsXLmTixIksWrSIhx56iGXLlrFhwwYuuugiAD7//HMGDx4cWWf8+PEADBgwgN///ve17m/o0KH88Y9/jLy//vrrAdi8eTOlpaWMGjUKCJ0hdOvWrcH6R40aRZcuXY5rHzx4MEVFRezYsYPx48dz7rnn1rudJUuWMGXKFJKTQ79ya9tmW6YgERG279vepPagJk+ezMyZM+nSpQt5eXmkpqbi7owaNYoXXnih1nU6dOgAhDrwjx492qT9uTsZGRm8/fbbx81LTk6mqqoK4Lh7LTp16lTr9q699louuOACFi1axNe+9jWeeuopevXq1aSaTiTqIxERep7Ws0ntQQ0fPpzVq1fz9NNPM3nyZAAuvPBC/vrXv7JlyxYADhw4wL/+9a8W2V/v3r0pKyuLBElFRQXr14eG70tLS2PVqlUAje4c37p1K7169eL2229n3LhxrF27ltTUVMrLy2tdftSoUTz11FORADzRLm0pSESEopFFdGzf8Zi2ju07UjSyKNB2q/tIql9Tp04FQmcVY8eOZfHixZGO9q5duzJnzhy+/vWvk52dzeDBg5vVqV6bU045hfnz53PvvfeSk5NDbm4uK1asAODuu+/mN7/5Df369WP37t2N2t6LL75IZmYmubm5lJaW8s1vfpMzzjiDiy66iMzMTO65555jlv/2t79Nz549yc7OJicnh+eff75Ffq5EkZDPbG8qPdhK5HgbN27k/PPPb/TyxeuKKVxayPZ92+l5Wk+KRhYF6h+RxFLbvwczW+XueUG3rT4SEQFC385ScEhz6NKWiIgEoiAREZFAFCQiIhKIgkRERAJRkIiISCAKEhGJmeph5DMzM5k0aRIHDx5seKUo99xzDxkZGcfdl9EYP/vZz+qcl5aWdsw9I7UNQR/Et7/9bTZs2FDn/Dlz5vDRRx81evlEpyARkZipHmurtLSUU045hSeffLJR61XfAT5r1izWrl3LjBkzmrzv+oIkliorK3nmmWfo27dvncvUDJKGlk90ChIRAWDTkU3M3jebx/Y+xux9s9l0pGXuKq82dOhQtmzZwoEDB7jxxhsZNGgQ/fr145VXXgGOH7b9yiuvZP/+/QwYMIB58+ZRVlbGhAkTGDhwIAMHDuSvf/0rAPv37+eGG24gKyuL7OxsXnrpJaZOnRq5qz4/v2n3xtRX3/e+973IcmPHjuWtt94C4NRTT+X73/8+OTk5vP3225Gh6SsrK7n++uvJzMwkKyuLRx55hPnz51NSUkJ+fj65ubkcOnTomKHsX331Vfr3709OTg4jR44MethbhW5IFBE2HdnE0oNLOUroTKC8qpylB5cC0KdDn8DbP3r0KIsXL2bMmDEUFRVx6aWXMnv2bD799FMGDRrEZZddBhw7bDuEfkFXjx587bXXctddd3HxxRezfft2Ro8ezcaNG/npT3/Kaaedxrp16wDYu3cvEyZMYObMmfU+VGvEiBG0a9cOCIVRnz6hn7O++upy4MABLrjgAn7xi18c075mzRp27txJaWkpEHr41emnn87MmTN5+OGHycs79qbysrIybr75ZpYvX056enqbGZNLQSIirDi8IhIi1Y5ylBWHVwQKkujnkQwdOpSbbrqJIUOGsGDBAh5++GEgNOLu9u2hUYbrGrYdQkOxR/cjfPbZZ+zfv58lS5Ywd+7cSHvnzp0bVdubb77JmWeeCYT6SKrref311+usry7t2rVjwoQJx7X36tWLrVu3ctttt3HFFVdw+eWX17udlStXMmzYMNLT04G2M9y8gkREKK+qfdTautobq7bnkbg7L730Er179z6m/W9/+1udw7YDVFVVsXLlSlJSUgLV1JC66lu1alVkuHk4dsj5lJSUyNlNtM6dO/PPf/6T1157jSeffJIXX3yxwYdptUXqIxERUpNSm9QexOjRo/n1r39N9YCx//jHPxq13uWXX37MI2qrA2rUqFE8/vjjkfa9e/cC0L59eyoqKlqsvrS0NNasWUNVVRUffvgh77zzToPb2r17N1VVVUyYMIEHHniA1atXA9Q55PyFF17I8uXLef/994G2M9y8gkREGJIyhOQaFyiSSWZIypAW39ePfvQjKioqyM7OJiMjgx/96EeNWu9Xv/oVJSUlZGdn07dv38g3wH74wx+yd+9eMjMzycnJ4c033wSgoKCA7OzsJne211XfRRddRHp6On379uX222+nf//+DW5r586dXHLJJeTm5nLdddfx85//HAg9uXHKlCmRzvZqXbt2ZdasWYwfP56cnByuueaaJtUeLxpGXuQE1dRh5Dcd2cSKwysoryonNSmVISlDWqSjXRKDhpEXkZjr06GPgkOaRZe2REQkEAWJiIgEoiAREZFAFCQiIhKIgkRERAJRkIhIzFQPI1/9mj59erO2U3PY9+b68Y9/HBn6pGb72WefHRnyfsGCBYH31ViNGUK+5mjBiSbhvv5rZj8GbgbKwk3/293/FL+KRKS5ahsiJVHddddd3H333WzcuJGhQ4eya9cukpK++L/20aNHSU5u2V+Z1UPON2TOnDlkZmZy1llnNWnbtQ3bEguJekbyiLvnhl8KEZHWUFwMaWmQlBT6s7g4Jrt59dVXmTRpUuR99EOlXnjhBbKyssjMzOTee+89bt2pU6ceMxxK9BnGjBkzGDhwINnZ2dx///2RZYqKijjvvPO4+OKL2bx5c4P1nX/++SQnJ7N7924uueQS7rzzTvLy8njsscdYtWoVw4cPZ8CAAYwePZqPP/4YCN1137dvX7Kzs5k8eTJQ+/D2UPeQ89Xz7rrrLjIyMhg5ciRlZWW1Dju/dOlS+vXrR1ZWFjfeeCNHjhwBQmdu9957L/379+d3v/td4/9SgnL3hHoBPwbubso6AwYMcBE51oYNGxq/8HPPuXfs6A5fvDp2DLUHkJSU5Dk5OZHX3LlzvaKiwnv06OH79+93d/cpU6b4s88+6zt37vQePXr4rl27vKKiwkeMGOEvv/yyu7ufc845XlZW5qtXr/Zhw4ZFtn/++ef79u3b/bXXXvObb77Zq6qqvLKy0q+44gpftmyZl5SUeGZmph84cMD37dvnX/nKV3zGjBnH1Xn//fdH2leuXOndunXzqqoqHz58uH/nO99xd/fPP//cBw8e7Lt27XJ397lz5/oNN9zg7u7dunXzw4cPu7v73r173d39Bz/4gd9xxx2RfXzyySfu7g74vHnzIu3Dhw/3v//975F5z4WP+U9+8hO/9dZbj1vm0KFD3r17d9+8ebO7u3/jG9/wRx55JHKcHnzwwVr/Lmr79wCUeAv83k64S1th3zOzbwIlwPfdfW/NBcysACgA6NmzZyuXJ3KCKSyEmo/BPXgw1N7Esaqi1XVpa8yYMSxcuJCJEyeyaNEiHnroId544w0uueQSunbtCkB+fj7Lly/nqquuiqzXr18/du3axUcffURZWRmdO3emR48ePPbYY7z++uv069cPCJ0NvPvuu5SXl3P11VfTsWNHAK688so6a33kkUd47rnnSE1NZd68eZgZQGS8q82bN1NaWsqoUaOA0KWjbt26AUTG9Lrqqqsi9dY1vH1dQ84DJCUlRfZ33XXXMX78+OOW2bx5M+np6Zx33nkAfOtb3+Lxxx/nzjvvPKbe1hSXIDGzJcCXa5lVCPwG+Cng4T9/AdxYc0F3nwXMgtBYWzErVuRkUNfzNhp4DkdzTZ48mZkzZ9KlSxfy8vJITW38KMOTJk1i/vz5/Pvf/4780nR3pk2bxi233HLMso8++mijt1vdR1JT9dD27k5GRgZvv/32ccssWrSI5cuXs3DhQoqKiiIP2apNXUPO16Y6zJqivqH4YyUufSTufpm7Z9byesXd/9vdK929CngaGBSPGkVOKnWd1cfobH/48OGsXr2ap59+OtKnMGjQIJYtW8bu3buprKzkhRdeYPjw4cete8011zB37lzmz58f6WsZPXo0s2fPZv/+/UBo1N1du3YxbNgw/vCHP3Do0CHKy8tZuHBhs2vu3bs3ZWVlkSCpqKhg/fr1kWHlR4wYwYMPPsi+ffvYv39/ncPb16eqqor58+cD8Pzzz3PxxRcDxw4737t3b7Zt28aWLVsAePbZZ2s9Tq0p4Trbzaxb1NurgdJ41SJy0igqgvDln4iOHUPtAVQ/IbH6NXXqVCB0eWfs2LEsXrw40tHerVs3pk+fzogRI8jJyWHAgAGMGzfuuG1mZGRQXl7O2WefHbm0dPnll3PttdcyePBgsrKymDhxIuXl5fTv359rrrmGnJwcvvrVrzJw4MBm/yynnHIK8+fP59577yUnJ4fc3FxWrFhBZWUl1113HVlZWfTr14/bb7+d008/vc7h7evTqVMn3nnnHTIzM3njjTe47777gGOHnXd3fvvb3zJp0iSysrJISkpiypQpzf65WkLCDSNvZs8CuYQubW0DbnH3j+tbR8PIixyvqcPIU1wc6hPZvj10JlJUFKh/RJru1FNPjZxVtbSTahh5d/9GvGsQOSnl5ys4pFkS7tKWiMjJKlZnI7GmIBE5gSXapWuJj1j/O1CQiJygUlJS2LNnj8LkJOfu7Nmzh5SUlJjtI+H6SESkZXTv3p0dO3ZQVlbW8MJyQktJSaF79+4x276CROQE1b59e9LT0+NdhpwEdGlLREQCUZCIiEggChIREQlEQSIiIoEoSEREJBAFiYiIBKIgERGRQBQkIiISiIJEREQCUZCIiEggChIREQlEQSIiIoEoSEREJBAFiYiIBKIgERGRQBQkIiISiIJEREQCUZCIiEggChIREQlEQSIiIoEoSEREJBAFiYiIBKIgERGRQBQkIiISiIJEREQCUZCIiEggChIREQlEQSIiIoEoSEREJJC4BImZTTKz9WZWZWZ5NeZNM7MtZrbZzEbHoz4REWm85DjttxQYDzwV3WhmfYHJQAZwFrDEzM5z98rWL1FERBojLmck7r7R3TfXMmscMNfdj7j7+8AWYFDrViciIk2RaH0kZwMfRr3fEW47jpkVmFmJmZWUlZW1SnEiInK8mF3aMrMlwJdrmVXo7q8E3b67zwJmAeTl5XnQ7YmISPPELEjc/bJmrLYT6BH1vnu4TUREElSiXdpaAEw2sw5mlg6cC7wT55pERKQe8fr679VmtgMYDCwys9cA3H098CKwAXgVuFXf2BIRSWxx+fqvu78MvFzHvCKgqHUrEhGR5kq0S1siItLGKEhERCQQBYmIiASiIBERkUAUJCIiEoiCREREAlGQiIhIIPUGiZnNMLNbamm/xcymx64sERFpKxo6I7mU8MCINTwNjG35ckREpK1pKEg6uPtxI+u6exVgsSlJRETakoaC5JCZnVuzMdx2KDYliZwYitcVk/ZoGkk/SSLt0TSK1xXHuySRmGhorK37gMVm9gCwKtyWB0wD7oxhXSJtWvG6YgoWFnCw4iAAH+z7gIKFBQDkZ+XHszSRFlfvGYm7LwauAkYAc8KvEcAEd/9TjGsTabMKlxZGQqTawYqDFC4tjFNFIrHT4Oi/7l4KfKsVahE5YWzft71J7SJtWb1BYmYLgejOdgd2A2+6+3OxLEykLet5Wk8+2PdBre0iJ5qGzkgerqWtC3CdmWW6+9QY1CTS5hWNLDqmjwSgY/uOFI3Uo3bkxFNvkLj7strazWwBoc53BYlILao71AuXFrJ933Z6ntaTopFF6miXE1KznpDo7pVmuo1EpD75WfkKDjkpNNRH0qWW5s7AN4H1MalIRETalIbOSFYR6mCvPv2o7mx/C5gSu7JERKStaKiPJL2ueWY2D7imxSsSEZE2Jcgw8oNbrAoREWmz9DwSEREJpKHO9v51zQLat3w5IiLS1jTU2f6LeuZtaslCRESkbWqos31EaxUiIiJtU0OP2v1B1PSkGvN+FquiRESk7Wios31y1PS0GvPGtHAtIiLSBjXUR2J1TNf2XkSibDqyiRWHV1BeVU5qUipDUobQp0OfeJcl0uIaCpKaQ8jXNU9Eomw6somlB5dylKMAlFeVs/TgUgCFiZxwGgqSHDP7jNDZx5fC04Tfp8S0MpE2bMXhFZEQqXaUo6w4vEJBIiechr611a61ChE5kZRXlTepXaQt053tIjGQmpTapHaRtkxBIhIDQ1KGkFzjhD+ZZIakDIlTRSKx06wHW4lI/ar7QfStLTkZxCVIwjc3/hg4Hxjk7iXh9jRgI7A5vOhKd9dzT6RN6tOhj4JDTgrxOiMpBcYDT9Uy7z13z23dckREpLniEiTuvhFAz30XEWn7ErGzPd3M/mFmy8xsaF0LmVmBmZWYWUlZWVlr1iciIlFidkZiZkuAL9cyq9DdX6ljtY+Bnu6+x8wGAH8wswx3/6zmgu4+C5gFkJeXp7vsRUTiJGZB4u6XNWOdI8CR8PQqM3sPOA8oaeHyRESkhSTUpS0z62pm7cLTvYBzga3xrUpEROoTlyAxs6vNbAcwGFhkZq+FZw0D1prZGmA+MMXdP4lHjSIi0jjx+tbWy8DLtbS/BLzU+hWJiEhzJdSlLRERaXsUJCIiEoiCREREAlGQiARRXAxpaZCUFPqzuDjeFYm0Oo3+K9JcxcVQUAAHD4bef/BB6D1Afn786hJpZTojEWmuwsIvQqTawYOhdpGTiIJEpLm2b29au8gJSkEi0lw9ezatXeQEpSARaa6iIujY8di2jh1D7SInEQWJSHPl58OsWXDOOWAW+nPWLHW0y0lH39oSCSI/X8EhJz2dkYiISCAKEhERCURBIiIigShIREQkEAWJiIgEoiAREZFAFCQiIhKIgkRERAJRkIiISCAKEhERCURBIiIigShIREQkEAWJiIgEoiAREZFAFCQiIhKIgkRERAJRkIiISCAKEhERCURBIiIigShIREQkEAWJiIgEoiAREZFAFCQiIhJIXILEzGaY2SYzW2tmL5vZ6VHzppnZFjPbbGaj41GfiIg0XrzOSP4MZLp7NvAvYBqAmfUFJgMZwBjgCTNrF6caRUSkEeISJO7+ursfDb9dCXQPT48D5rr7EXd/H9gCDIpHjSIi0jiJ0EdyI7A4PH028GHUvB3htuOYWYGZlZhZSVlZWYxLFBGRuiTHasNmtgT4ci2zCt39lfAyhcBRoLip23f3WcAsgLy8PA9QqoiIBBCzIHH3y+qbb2bXA2OBke5eHQQ7gR5Ri3UPt4mISIKK17e2xgA/AK5094NRsxYAk82sg5mlA+cC78SjRhERaZyYnZE0YCbQAfizmQGsdPcp7r7ezF4ENhC65HWru1fGqUYREWmEuASJu/9HPfOKgKJWLEdERAJIhG9tiYhIG6YgERGRQBQkIiISiIJEREQCUZCIiEggChIREQlEQSIiIoEoSEREJBAFiYiIBKIgERGRQBQkIiISiIJEREQCUZCIiEggChIREQlEQSIiIoEoSEREJBAFiYiIBKIgERGRQBQkIiISiIJEREQCUZCIiEggChIREQlEQSIiIoEoSEREJBAFiYiIBKIgERGRQBQkIiISiIJEREQCUZCIiEggChIREQlEQSIiIoEoSEREJBAFiYiIBKIgERGRQBQkIiISSFyCxMxmmNkmM1trZi+b2enh9jQzO2Rma8KvJ+NRn4iINF68zkj+DGS6ezbwL2Ba1Lz33D03/JoSn/JERKSx4hIk7v66ux8Nv10JdI9HHSIiElxyvAsAbgTmRb1PN7N/AJ8BP3T3v9S2kpkVAAXht0fMrDS2ZbaIM4Hd8S6iEVRny1KdLact1Ahtp87eLbERc/eW2M7xGzZbAny5llmF7v5KeJlCIA8Y7+5uZh2AU919j5kNAP4AZLj7Zw3sq8Td81r2J2h5qrNlqc6W1RbqbAs1wslXZ8zOSNz9svrmm9n1wFhgpIfTzN2PAEfC06vM7D3gPKAkVnWKiEgw8frW1hjgB8CV7n4wqr2rmbULT/cCzgW2xqNGERFpnHj1kcwEOgB/NjOAleFvaA0D/svMKoAqYIq7f9KI7c2KWaUtS3W2LNXZstpCnW2hRjjJ6oxZH4mIiJwcdGe7iIgEoiAREZFAEj5IzGyMmW02sy1mNrWW+R3MbF54/t/MLC1q3rRw+2YzG52Idbb2sDCNqHOYma02s6NmNrHGvG+Z2bvh17cStMbKqGO5IFY1NrLO/2VmG8JDAS01s3Oi5rXKsWyBOhPpeE4xs3XhWv6fmfWNmpdIn/Va60y0z3rUchPMzM0sL6qtacfT3RP2BbQD3gN6AacA/wT61ljmu8CT4enJwLzwdN/w8h2A9PB22iVgnWlAaQIdzzQgG/i/wMSo9i6EvkHXBegcnu6cSDWG5+1PoGM5AugYnv5O1N95qxzLoHUm4PH8H1HTVwKvhqcT7bNeV50J9VkPL5cKLCc0wkhec49nop+RDAK2uPtWd/8cmAuMq7HMOOD/hKfnAyMt9FWwccBcdz/i7u8DW8LbS7Q6W1ODdbr7NndfS+hbc9FGA39290/cfS+h8dLGJFiNrakxdb7pX3y9PXoooNY6lkHrbE2NqTP6xuROQPU3hRLqs15Pna2pMb+TAH4KPAgcjmpr8vFM9CA5G/gw6v2OcFuty3ho/K59wBmNXDcR6oTwsDBmtszMhsaoxsbWGYt1myLoflLMrMTMVprZVS1a2bGaWudNwOJmrhtEkDohwY6nmd1qoRuVHwJub8q6CVAnJNBn3cz6Az3cfVFT160pEcbaOtl9DPT0qGFhzKzBYWGkTue4+04L3dD6hpmtc/f34lmQmV1HaCig4fGsoyF11JlQx9PdHwceN7NrgR8CMe1faq466kyYz7qZJQG/BK5vie0l+hnJTqBH1Pvu4bZalzGzZOA0YE8j1417neHTxz0QGhaG0PXI8+JYZyzWbYpA+3H3neE/twJvAf1asrgojarTzC4DCgmN4nCkKesmQJ0JdzyjzAWuaua6QTS7zgT7rKcCmcBbZrYNuBBYEO5wb/rxbI2OnwAdRsmEOiLT+aLDKKPGMrdybCf2i+HpDI7tMNpK7DrggtTZtbouQh1jO4Eu8aozatk5HN/Z/j6hzuHO4ekWrzNgjZ2BDuHpM4F3qaWDsRX/zvsR+mVxbo32VjmWLVBnoh3Pc6Om/xMoCU8n2me9rjoT8rMeXv4tvuhsb/LxbPEfIAYH5GuEHn71HqGRgwH+i9D/nABSgN8R6hB6B+gVtW5heL3NwFcTsU5gArAeWAOsBv4zznUOJHRN9AChM7v1UeveGK5/C3BDotUIDAHWhT8E64Cb4nwslwD/Hf67XQMsaO1jGaTOBDyej0V9Vt4k6hdjgn3Wa60z0T7rNZZ9i3CQNOd4aogUEREJJNH7SEREJMEpSEREJBAFiYiIBKIgERGRQBQkIiISiIJEpAnMbE7NEYdFTnYKEhERCURBIlIPM/tm+Dkd/zSzZ8PNw8xshZltrT47MbNTw8/yWB1+FsW4cHuamW00s6fNbL2ZvW5mXwrPGxje9hozm2FmpeH2duH3fw/PvyUuP7xIIylIROpgZhmEBty71N1zgDvCs7oBFwNjgenhtsPA1e7en9DzPX4R9ZiAc4HH3T0D+JTQHc4AvwVucfdcoDJq1zcB+9x9IKG7+G82s/SW/wlFWoZG/xWp26XA79x9N4C7fxLOhj+4exWwwcz+Z3hZA35mZsMIPSflbKB63vvuviY8vQpIM7PTgVR3fzvc/jyhYAK4HMiO6os5jVAYvd/yP6JIcAoSkaY7EjVdfdaRT2hQvgHuXhEeUTWlluUrgS81sH0DbnP311qgVpGY06Utkbq9AUwyszMAzKxLPcueBuwKh8gI4Jz6NuzunwLlZnZBuGly1OzXgO+YWfvwfs8zs07N/BlEYk5nJCJ1cPf1ZlYELDOzSuAf9SxeDCw0s3VACbCpEbu4CXjazKqAZYSemgnwDKHne68O97OU8cWzN0QSjkb/FYkTMzvV3feHp6cC3dz9jgZWE0k4OiMRiZ8rzGwaoc/hB7TQY09FWpvOSEREJBB1touISCAKEhERCURBIiIigShIREQkEAWJiIgE8v8B4M6pxnmibBkAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -981,43 +1088,23 @@ } ], "source": [ - "def get_idx_close(change, changes):\n", - " diff = [abs(c - change) for c in changes]\n", - " idx = diff.index(min(diff))\n", - " return idx\n", - "\n", - "pct = 0.2\n", - "trained_idx = get_idx_close(pct, trained_changes_sorted) - 1\n", - "even_idx = get_idx_close(pct, even_changes)\n", - "perfect_idx = get_idx_close(pct, perfect_changes)\n", - "\n", - "print(even_idx, even_changes[even_idx], even_elucs[even_idx])\n", - "print(perfect_idx, perfect_changes[perfect_idx], perfect_elucs[perfect_idx])\n", - "print(trained_idx, trained_changes_sorted[trained_idx], trained_elucs_sorted[trained_idx])\n", - "\n", - "plt.scatter([even_changes[even_idx]], [even_elucs[even_idx]], color=\"green\", label=\"Even Heuristic\")\n", - "plt.scatter([perfect_changes[perfect_idx]], [perfect_elucs[perfect_idx]], color=\"lightgreen\", label=\"Perfect Heuristic\")\n", - "plt.scatter([trained_changes_sorted[trained_idx]], [trained_elucs_sorted[trained_idx]], color=\"red\", label=\"Evolved Prescriptor\")\n", - "plt.legend()\n", - "plt.xlabel(\"change\")\n", - "plt.ylabel(\"ELUC\")\n", - "plt.xlim([0, 0.4])\n", - "plt.ylim([-25, 0])\n", - "#plt.title(\"Average Change vs. ELUC for ~20% change prescriptors\")\n", - "#plt.savefig(\"figures/prescmeans.png\", format=\"png\", dpi=300)\n", - "plt.show()" + "even_idx, perfect_idx, trained_idx = plot_selected_points(0.2, \n", + " (even_changes, even_elucs), \n", + " (perfect_changes, perfect_elucs), \n", + " (trained_changes_sorted, trained_elucs_sorted), \n", + " figure_dir / \"prescmeans.png\")" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "832/832 [==============================] - 3s 4ms/step\n" + "757/757 [==============================] - 3s 4ms/step\n" ] } ], @@ -1032,12 +1119,42 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_expanded(even_sample, perfect_sample, trained_sample, save_path=None):\n", + " # Evolved first so that it is on the bottom\n", + " plt.scatter(trained_sample[\"change\"], trained_sample[\"ELUC\"], color=\"red\", label=\"Evolved Prescriptor\")\n", + " plt.scatter(even_sample[\"change\"], even_sample[\"ELUC\"], color=\"green\", label=\"Even Heuristic\")\n", + " plt.scatter(perfect_sample[\"change\"], perfect_sample[\"ELUC\"], color=\"lightgreen\", label=\"Perfect Heuristic\")\n", + " # Rearrange legend (from stackoverflow)\n", + " handles, labels = plt.gca().get_legend_handles_labels()\n", + " order = [1, 2, 0]\n", + " plt.legend([handles[idx] for idx in order], [labels[idx] for idx in order])\n", + " plt.xlabel(\"change\")\n", + " plt.ylabel(\"ELUC\")\n", + " #plt.title(\"Expanded view of ~20% change prescriptors (subsampled)\")\n", + " if save_path:\n", + " plt.savefig(save_path, format=\"png\", dpi=300)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 55, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Heuristic threshold: 0.3500000439438788\n" + ] + }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAEGCAYAAACZ0MnKAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAA2KElEQVR4nO3deXxV1bnw8d+TQBgTIICtiBB8K1SBACFQccIJocortyIXaqwCqWi1It7qRS91KqYXq1W0Vi0axGpULO11KE7FWulVUQMCgkOlyhj7GgiEMGZa7x97n5Mz7H2mnDF5vp/P+XDO2vvsszaE82RNzxJjDEoppVQkslJdAaWUUplDg4ZSSqmIadBQSikVMQ0aSimlIqZBQymlVMQ6pLoCidanTx9TUFCQ6moopVTGWLt27W5jTF+nY20+aBQUFFBZWZnqaiilVMYQkW1ux7R7SimlVMQ0aCillIqYBg2llFIRa/NjGkopfw0NDezcuZMjR46kuioqxTp37kz//v3p2LFjxO/RoKFUO7Nz505yc3MpKChARFJdHZUixhj27NnDzp07GTRoUMTvy7igISKTgAeAbOBxY8yieH/G/Xvu9/vPZIzhht43xPtjlEqJI0eOaMBQiAi9e/emuro6qvdl1JiGiGQDvwW+D5wM/FBETo7nZ3gCRuBjcc1ifrmrLJ4f1eKaa6BDBxCBrCzIzbWeZ2dbf3oeffpARUVi6qDaFQ0YCmL7Oci0lsZYYIsx5ksAEXkOmAJ8Eq8P8ASJwDKArl26cf+e+8lb8y9Kr10O27dTPn8cVXPOI7dHL+r276Xf5iMwZDBVnarI7ZZL3cE6+h3tR+l3Sp0/8Jpr4JFHWl4bAwcOWM+bm/3P3bMHLrsMZs6EHj2gpgYGDICyMigpidPfgFJKucuolgZwHLDD5/VOu8yPiMwRkUoRqYy26RWKiJCVlUXduGP55TtXcsezP6Dmhn8jr2c+IkJej3z2jT2GfT32kdc9zyrrnkdNXg3lW8r9L1ZRAQUF/gEjUo2NVgAxBrZtg1mzrFZIVpZ1TW2NqDSXnZ3NyJEjvY9Fi+Ley+z1t7/9jcmTJ/uVzZw5kxUrVsTl+lVVVVxyySWux/ft28fDDz8c8fnpLtNaGhExxiwBlgAUFxfHfZcpEaFb1+50nXBGUKukQ4fgv9KcjjlUdapqKaiogDlz4NCh+FSoocEKImAFkTlzWo4tWADbt2uLRKWVLl26sH79+lRXo9UaGxvp169fyADkCRrXXHMNQNjz012mtTR2Acf7vO5vl8VNNDsZRtMfmNst1+qKAuuLPF4Bw8mhQ3D99Vbw2LatpUUyZ45/K8TT2tEWigqh4uMKChYXkHVnFgWLC6j4ODE/J6+99hrTpk3zvvZtIbzxxhuMGzeOoqIipk2bxgG7C7egoIDbb7+doqIihg8fzmeffRb1565du5bx48czevRoJk6cyNdffw3AWWed5U1BtHv3bjw57JYtW8ZFF13EOeecw7nnnsvWrVsZNmwYAJs3b2bs2LGMHDmSwsJCvvjiC26++Wb++c9/MnLkSG666Sa/85uamrjxxhsZNmwYhYWF/OY3v4ntLy+JMq2l8SFwoogMwgoWM4BL4/kBeXvz2N9rP1lZ8Y2ndbV7W7qitvmndSmfV0TV3MnWuEjtXvo9+GdKF69r3Qd6Wh6+Dh2yAlZJSXBrx7eFoq0RZav4uII5L8/hUIP1c7KtdhtzXrZ+TkqGx/5zcvjwYUaOHOl9fcsttzB16lTmzJnDwYMH6datG8uXL2fGjBns3r2bu+66i1WrVtGtWzfuvvtu7rvvPm677TYA+vTpw7p163j44Ye59957efzxx4M+7+9//7vf523fvp3JkyfT0NDAddddx4svvkjfvn1Zvnw5CxYsYOnSpSHrv27dOjZu3Eh+fj5bt271lj/66KNcf/31lJSUUF9fT1NTE4sWLWLTpk3elpXv+UuWLGHr1q2sX7+eDh06UFNTE/XfZbJlVNAwxjSKyE+B17Gm3C41xmyO52eUfqeU8pXzqf3et8jKyorLLJP6hnr6Pfhn68Wjj/odK59XRM0tM8jrmANAXs98am6ZQTm0PnA42b7d+tOpteMbVJQCFry5wBswPA41HGLBmwtaFTTcuqcmTZrEyy+/zCWXXMLKlSv51a9+xdtvv80nn3zCaaedBkB9fT3jxo3zvufiiy8GYPTo0fzpT39y/LwzzjiDP//5z97XM2fOBODzzz9n06ZNTJgwAbB+8z/22GPD1n/ChAnk5+cHlY8bN46ysjJ27tzJxRdfzIknnhjyOqtWreLqq6/2dms7XTPdZFTQADDGvAK8ksjPKL3wbqio4LZRG8j/dr9WBQ5jDAffWsNNngAQ0P1VNXeyN2B45HTMoWruZHhwffAMqkh16gRHjwaXDxhg/ekJHoHcylW7tL3W+efBrby1ZsyYwUMPPUR+fj7FxcXk5uZijGHChAk8++yzju/p1KkTYA2uNzY2RvV5xhiGDh3Ke++9F3SsQ4cONNv//wJXz3fr1s3xepdeeinf+973WLlyJRdccAG/+93vOOGEE6KqU7rLtDGN5Ckp4Rcn/4rc975mf20NxhiOHD0S1ZgH2IPmZ59C+bwix+O5PXq5l//+91aQMQaefjq6+jsFjK5drcFwaAkegdzK09Adn9zBfXvuY3HNYu7bcx93fHJHqqvU5gzo4fzz4FbeWuPHj2fdunU89thjzJgxA4BTTjmFd955hy1btgBw8OBB/vGPf8Tl84YMGUJ1dbU3aDQ0NLB5s9V5UVBQwNq1awEiHrj+8ssvOeGEE5g7dy5Tpkxh48aN5ObmUldX53j+hAkT+N3vfucNdpnQPaVBI4zSC+/m1oI7mZc/j/nfnk/ue19HHThyOubw/2682PFYXe1e9/IFC1oKSkqgc+eIPq98XhELv7yNxXvuZ+GXt1kBq3dvWLKkpeuprMwKIn4VzYHduzNiMeEdn9xBz2/3JDsrGxEhOyubnt/uqYEjzsrOLaNrR/+fk64du1J2busWunrGNDyPm2++GbBaC5MnT+bVV1/1DoL37duXZcuW8cMf/pDCwkLGjRsX04C3k5ycHFasWMH8+fMZMWIEI0eO5N133wXgxhtv5JFHHmHUqFHs3r07ous9//zzDBs2jJEjR7Jp0yYuv/xyevfuzWmnncawYcO46aab/M7/8Y9/zIABAygsLGTEiBE888wzcbmvRJJovwAzTXFxsYn3JkwLt95OXo/o+h6NMeQufCponMIzppHj00VV31BP/n8/R+kDH7V0T1VUWOsxGhpCfo7r9R76M6W/eNv/5IqKlim5+fmwd29wd1hODixdmnbjHItrFjt2GxpjmJc/L/kVyiCffvopJ510UsTnV3xcwYI3F7C9djsDegyg7NyyVo1nqPTi9PMgImuNMcVO52fcmEY66Lf5CDVj6v2+mI0xIcc+RITan5cEDXCXLl5HOTjPnurd25oKu327NS22qSls3VzHSGadFXxySUlLMOjTx3n8pL5eB8fbuZLhJRoklJcGjRiUXng35SvnUzW0M7l5VvqQ7I45dOvaPeT7srOy/WdGDRwI27ZZLQqnmVI1NS1TZyMIGBBmjMRNRYXzFF2PgCnCSqn2S4NGjEovvLvlRT6Ur5xPzZgcv9aHE+/MqP/ZA/Z87fIt5VR13EFubk//lka0XYe9e1NXu5e8nsFdZ3V1tfCq3R21bZuVDLGpyQpcoQIGWOMbFRXa2lBK6UB4vJReeDf5H+72zrQKNVaU26OXdxZT+ZZyavJqyMvrZeWq8qzTcJltFdLu3fT75Aj1DfV+xfUN9fTbdKhlhTi0tFy2bWtJkOjGGP9BeaVUu6UtjTjybX2Ur5xP7SnfIjsrO+i8utq9UDIPgKpOVeR1zPM77m2NRLC4z281+Y6F9BsymPz9+GfZ3XiA0im/jriLy5Gu31BKoUEjYTzjHjVj+gTNZGraUsVCuZ3cvF5WTioHIccgbEGrybvnUdOphvz9+dx6/K3WST+/JqJMumFTmWTQ+g2lVOJo91QCBXZZ7a+t4eCGf9BtxGDyeuQ77t3h4bZ+w1fV3MlBYyh+GXUrKiIOGPv+69KWFO8989n3X5e2dJH5Lgp0ev+WchbuWMjimsUs3LEwOA28UgE8qdGHDRvGtGnTOBRlAs+bbrqJoUOHBq17iMQvf/lL12MFBQV+azKc0qq3xo9//GM++cR9+59ly5ZRVVUV8fmpoEEjwXwXB95acCfZJ/YLO1he31BPvyf+Bj/5iTVQDdbANViD0jbXmVLdcq2pupddFlEd/9+NFweldO/QoYO1IHHgQP9FgQG8YzLh9g+JM4PzmJFbuUovntxTmzZtIicnh0cDcrK58aycXrJkCRs3buSee+6J+rNDBY1Eampq4vHHH+fkk903Gw0MGuHOTwUNGkmWm+fe7WSMYf+B/eTvz7cW4j38sDXDyhhr4yVj4KmnrC9yEer2h1hNHuk02d696drFOY9O1y7drM8PMWuqqlNV6NZOggjOLTS3chW7z45+xtLapTyw9wGW1i7ls6PxWY3tccYZZ7BlyxYOHjzI7NmzGTt2LKNGjeLFF18EglORX3TRRRw4cIDRo0ezfPlyqqurmTp1KmPGjGHMmDG88847ABw4cIBZs2YxfPhwCgsL+eMf/8jNN9/sXY1eEuVswFD1++lPf+o9b/Lkyfztb38DoHv37vzsZz9jxIgRvPfee950601NTcycOZNhw4YxfPhw7r//flasWEFlZSUlJSWMHDmSw4cP+6Vnf+211ygqKmLEiBGce+65rf1rj5mOaSRZ3f69IVeT99t4gKqh21lcs9i7fazf9F6fBXn9tpRT01ATNGbizagbicOHo74HX65jMi7lKrN8dvQz3jz0Jo1Yv+HXNdfx5qE3Afhup++2+vqNjY28+uqrTJo0ibKyMs455xyWLl3Kvn37GDt2LOeddx7gn4ocrC9jT5bcSy+9lBtuuIHTTz+d7du3M3HiRD799FMWLlxIjx49+PjjjwHYu3cvU6dO5aGHHgq5AdTZZ59Ntt2yP3DgAN/9rnWfoern5uDBg3zve9/j17/+tV/5+vXr2bVrF5s2bQKsjZp69uzJQw89xL333ktxsf9i7Orqaq688kpWr17NoEGDUpqjSoNGkvXbfIS6cc6rxw8dPkjDmD4tA9s98qkZU0/5yvn+gcNW+p1Sa42H70yp+16ILqX6oUMcOnzQcWHioSPh+5nrDtaR1z3PsZw4ZHkOur9Q+62ruHv3yLvegOHRSCPvHnm3VUHDdz+NM844g9LSUk499VReeukl7r33XsDKLLvdnrXnloocrPTivv3++/fv58CBA6xatYrnnnvOW96rV/jJJQBvvfUWffr0AawxDU993njjDdf6ucnOzmbq1KlB5SeccAJffvkl1113HRdeeCHnn39+yOusWbOGM888k0GDBgGpTaGuQSPJSi+8mzv+ciU9Rw/1CxyetRWOXT1D3RMV+n6Blr83n6q5k1l864+i2szpW/f+iX0LLqVDdsuPQ2NTI9869K2w7+13tB81nRxaO0f7BZ0bbQDwjpfYU5I9s8PKt5THJSCp8OqanbOzupVHymk/DWMMf/zjHxkyZIhf+fvvv++aihygubmZNWvW0DnChJ6xcqvf2rVrvSnUwT+NeufOnb2tFl+9evViw4YNvP766zz66KM8//zzYTd+Shc6ppECd0x4zC/l+v7aGvI/3O06tpCb18uambT1dspXznc8xzO913cGVKSLBEv/Zw899/Vk/4H93nGVnvt6RvQbfel3Ssnfn+/33vz9+UHvjWXAPFXjJapFbpZL96NLeWtMnDiR3/zmN96FsR999FFE7zv//PP9tkn1BKMJEybw29/+1lu+d681BtixY0cawiT+jKZ+BQUFrF+/nubmZnbs2MEHH3wQ9lq7d++mubmZqVOnctddd7FunfXLnVsa9VNOOYXVq1fz1VdfAalNoa4tjRQJTENCgXv2XE+LJFR3VdXQzu6bOT3+j9Crvg8coPT9zlBya0t9orkX3wAR+F47k27VW1eQ19H/YLgAoOMlqXdq51P9xjQAOtCBUzufGvfPuvXWW5k3bx6FhYU0NzczaNAgv9323Dz44INce+21FBYW0tjYyJlnnsmjjz7Kz3/+c6699lqGDRtGdnY2t99+OxdffDFz5syhsLCQoqIiKqJI/e9Wv9NOO41BgwZx8sknc9JJJ1FUFP4XtV27djFr1ixvC+W///u/AWtHwauvvpouXbr4bQzVt29flixZwsUXX0xzczPHHHMMf/nLXyKuezxpavQ04rQY0Mn+2hpuLbjTryxkqvA+/xE+j1XXriGn1sbEZx/yxXvujzqV+cIdCx3HS/Yf2E9ut1xNjR6jaFOjf3b0M9498i51zXXkZuVyaudT4zIIrtJDtKnRtXsqjUSav8pp2q7r9Nv9eyNbze3ZH9yjosJa65GVZf3p+Y3MrdyJzz7krptNHXTvG+93tJ9zHi2H8RKVON/t9F1m95jN9b2uZ3aP2Row2jkNGmnGdzFgyEAQoN9ml0SFm48479LnxDMTpKKC8vUPsvCtK1i8+z4WvnUF5esfhGuuaUl6aIz155w57oHDZ2ZJvwf/HHUAiHS8RCmVPDqmkcacNnvyBoIC/3Od9vgIWuNxxRWhkxbaLZLyz5dQc9MlLVN/e+ZTc9MllC9aTmlgugdPC8WpW2vAAO8iw6DNpiKcPhtyvEQplXQaNNJYRIEg4Hwve3Ddy/Olbo8xBPHJL1U16yznQfXrLoT71wa/122uelmZ3+eVLl4HSz6zx07mWef4bjk7YID1ntaOq+jeH0oljAaNNBcyEETL80UauBFTdrbfmEbu96Pc/c9tzMT385yCgs9AOdDS3eX73gC+az2cGEzYayilYqdjGu1NSUlLPqsnn7RaGL4bMs2ZQ13dPse3Og5mh8mA6/285ubgPFY+A+VegQPyPgLXejhpbmoOeQ2lVOto0GjPXL60+5W/5Txo7ZvTSiRsBtyw3Lq1XMqdFvsF8q6+1U2j0ponNbrnsWjRopiuE5jKPFZ33HGHNz1IYPlxxx3nTeP+0ksvtfqzIhVJWvTArLjJkHbdUyJyD/B/gXrgn8AsY8w++9gtQCnQBMw1xryeqnq2CS5frKV3/Z3yyy+nqsN2aywlMCVJdrbVcmgtn4HyoHIHUS3q002j0ppTGpF0dcMNN3DjjTfy6aefcsYZZ/DNN9+QldXy+3ZjY2PQ1gKt5UmjHs6yZcsYNmwY/fpFPg29qanJMbVJpNKxpfEXYJgxphD4B3ALgIicDMwAhgKTgIdFJPY7V+5frAMGUPqdUm59ZzDzjl/ArSf8wj+HVVNTy5Tbyy4Dl0yfYTdncpoKHKK7K9SajkivoWIQzdqcVnjttdeYNm2a97XvBkjPPvssw4cPZ9iwYcyfH5xK5+abb/ZLGeLbcrjnnnsYM2YMhYWF3H777d5zysrKGDx4MKeffjqff/552PqddNJJdOjQgd27d3PWWWcxb948iouLeeCBB1i7di3jx49n9OjRTJw4ka+//hqwVquffPLJFBYWMmPGDMA5ZTu4p1H3HLvhhhsYOnQo5557LtXV1Y6p1N98801GjRrF8OHDmT17NkePHgWsFtn8+fMpKiriD3/4Q+T/KA7SLmgYY94wxnhyFqwB+tvPpwDPGWOOGmO+ArYAY1NRxzYj3Jd2SYnV/WTv34Hbbydvvmmt4fARUa6pwOuH6e5yWuznKN4r29szz2SFSNfmRMiT5dbzWL58Oeeddx7vv/8+Bw8eBGD58uXMmDGDqqoq5s+fz1//+lfWr1/Phx9+yAsvvOB3venTp/P88897Xz///PNMnz6dN954gy+++IIPPviA9evXs3btWlavXs3atWt57rnnWL9+Pa+88goffvhh2Dq///77ZGVl0bdvXwDq6+uprKxk7ty5XHfddaxYsYK1a9cye/ZsFthjaosWLeKjjz5i48aN3o2mfFO2b9y4kXPOOQdoSaO+YcMGTj/9dL/PPnjwIMXFxWzevJnx48dz5513cskll1BcXExFRQXr169HRJg5cybLly/n448/prGxkUd8du7s3bs369at8wavWKVd0AgwG3jVfn4csMPn2E67LIiIzBGRShGprK6uTnAVM1gkX9q+A9mhuqSWLPF76ZpssMN2/y+cUAPlAQIX+zkxxmjAiKcoJytEytM95XlMnz6dDh06MGnSJF5++WUaGxtZuXIlU6ZM4cMPP+Sss86ib9++dOjQgZKSElavXu13vVGjRvHNN99QVVXFhg0b6NWrF8cffzxvvPEGb7zxBqNGjaKoqIjPPvuML774gr///e/84Ac/oGvXruTl5XHRRRe51vX+++9n5MiR3HjjjSxfvtw7CWP69OkAfP7552zatIkJEyYwcuRI7rrrLnbu3AlAYWEhJSUlPP30094urFWrVnHttdd6r+9J2e6WRh0gKyvL+3mXXXYZ//u//xt0zueff86gQYMYPHgwAFdccYXf35Pn/a2VkjENEVkFfNvh0AJjzIv2OQuARiDqX2mMMUuAJWDlnmpFVds+n02dwnIbg4CgRYOuyQbzerVqSqxnsd/imsWOx91mVakYRTlZobVmzJjBQw89RH5+PsXFxeTmRj6ONW3aNFasWMG//vUv7xekMYZbbrmFq666yu/cxYsXR3xdz5hGIE+6dmMMQ4cO9Usw6LFy5UpWr17Nyy+/TFlZmXdDKCduadSdxPJzHiq9fDRS0tIwxpxnjBnm8PAEjJnAZKDEtPxKuQs43ucy/e0ylSyhxgkCftjdxh/qavfG5TfVg4cPRlWuYhRi3CsRxo8fz7p163jssce83Shjx47l7bffZvfu3TQ1NfHss88yfvz4oPdOnz6d5557jhUrVnjHRiZOnMjSpUs5YGd53rVrF9988w1nnnkmL7zwAocPH6auro6XX3455joPGTKE6upqb9BoaGhg8+bN3lTpZ599NnfffTe1tbUcOHDANWV7KM3NzaxYsQKAZ555xtt95ZtKfciQIWzdupUtW7YA8NRTTzn+PbVWOs6emgT8JzDeGOPbLn4JeEZE7gP6AScC4RPXqyDRrDL3U1ICTzxhjWEE8rQebK6bM3mm7bbyN9WcHOept27lKkYBq/qBuEw08N25D2DSpEksWrSI7OxsJk+ezLJly3jyyScBOPbYY1m0aBFnn302xhguvPBCpkyZEnTNoUOHUldXx3HHHcexxx4LWHttfPrpp4wbNw6wBpSffvppioqKmD59OiNGjOCYY45hzJgxMd9LTk4OK1asYO7cudTW1tLY2Mi8efMYPHgwl112GbW1tRhjmDt3Lj179nRN2R5Kt27d+OCDD7jrrrs45phjWL58ORCcSv2JJ55g2rRpNDY2MmbMGK6++uqY78tN2qVGF5EtQCdgj120xhhztX1sAdY4RyMwzxjzqvNVWmRSavRkcEq/Xt9QT/6Hu4MDh1OKD4CrrgJ7sJKsLOv1ww8Hf9aWcvdpuwMHWmMYMQqZCv7VvjquEUK0qdETkupFRaV79+7e1lK8RZsaPe1aGsaY74Q4VgboXMpWcN2sKXBLWacUH7NnWzNofHc969wZTjvN8bNKv1MafB1I/JTYwASK+qXXOtGMe6k2L91nT6k4c9qLw7HcadZMfb1/wIDw4xNRTquNC9+urwRNGVUqmRLVyohF2rU0VGLV7d/ruKVs3f69/qnHoxlzCHdusn9T9R2kDTVltB3/9myMcZ+Bs2cP7Npl/ZKQkwPHHQe9eye3giopYhme0KDRzoTao6N8s88A+T9v9R+DCCXdUnb4dn0lecpoJujcuTN79uyhd+/ewYFjzx6rNeZZk1Nf3zLNWgNHm2KMYc+ePXTu3Dn8yT40aLQzbnt0ANSM6eO/8dItMyiHlsCRkxM8ppGOKTt8WxBR5rdqD/r378/OnTtxXPi6c6fzRl179kD//sHlKqN17tyZ/lH+u2rQaIec9uhYuPV25wHyuZPhgY/8Z0/FOqgcxwFpt+6VoOZ2gqaMZrKOHTsyaNAg54NDh1q/GAQSiU+SSpXxNGgoIMQAeY9ewV8WsXzRx7DhUtD7fQJO/Zqf0LlTcLM6KDdVuI2glD9tmakwdPaUAuyBcBcLt95O+crgzKJRCRiQLp9XxMJNN7L4+9Xhr19RAbNm+c2A6pTTyfFUx/JI8lslKZNr2osy87BqfzRoKMAaIHfKICsi5PXIp2ZMn9YFDp+B5/J5RdTcMoO8nvmRXf/664Om+jY0NTie6lYekk7LbZGKKdIqo6TdivB40xXhkfMdIHcaL9hfW8OtBXfGdvGCAm+3x8IvbyOvZ/C034OHDtDUUB+c3sShLov33O++Ijx/Xsx189PKVetKZaqMWhGuUsczQO6WQdZp3MM30ByykwV27dItOKeVz4B0bg/n8ZOuXbohXbsD2K2PespXzqe0lfcVVrhpubqiXCkv7Z5SQdzGNwLLPXms8npY3UzdunanW9fuzl1OPt0edbXO1w9sOXjTmyR6fUCoTK7adaWUHw0aKojT+IZnAaCvqqGdgzZa8hWU08oekO73SfD13bpJc/N6wQMPWGtEEiXU4G+CNiFSKlNp0FBBSi+8m/wPd7O/tgZjDPtraxyz4LpN0w13jtP1D7nsg1G3f68VbJYutcYYEiHU4K+uKFfKj45pKEdOCwADueWxCjwHh1MCr291deU4pjehgJb8VVlZzovPWsstP5auW1DKj7Y0VMzcpul6OHVpuYm0dZP0L2tdt6CUH21pqJgF5rEKOXsqwut5ubRuvLOwksVpRfkFF1ivf/QjnU2l2h1dp6EyT0UFi79fHb91GlF8LtdfbyXv89W1qy6AU21KqHUa2j2lMk8qvpw9U28DAwbobCrVrmjQUCoSTlNvfQXuFqh5rFQbpUFDtT+xfKmHm2LrGaDXxYCqjdOgodoXpy/1yy6DPn1Cf7GHmrXlO5tKFwOqNk6DhspIB484LwZ0K/dy62basyd0i8Bp6i1YKU58B8HdWiROaz2UykAaNFRG2vHNjqDUI8YYdnyzw3rh1gUVqpspVIvAadX400/D7t3B28s6EdEuKtUm6DoNlZGGHD8kaMqtiDDk+CFWV5PvLCffXQLdVnh7hAoqbqvGfZWVWes3AqeyG2MFJJ2WqzJc2rY0RORnImJEpI/9WkTkQRHZIiIbRaQo1XVUqeO0RsNbHmparFs3k0drV5yXlLinOYkkX5XOvFJpLi2DhogcD5wP+P4v+z5wov2YAzySgqqpTLZtmxU4rrjCOd16vNKDuCVWDBeQdOaVygBpGTSA+4H/BHx/ZZsC/N5Y1gA9ReTYlNROZa5t2+DJJ610608/nZhtTWPNV6Uzr1QGSLsxDRGZAuwyxmwI6II4Dtjh83qnXfa1wzXmYLVGGKDZSDOab26rWPJZOfJ8EW/dmpgxBqd8VZHkp9I07CoDpCRoiMgq4NsOhxYA/4XVNRUzY8wSYAlYuadacy2VOt6dAe106b5bwDKulY3MRH8RRzJoHkjTsKsMkJLuKWPMecaYYYEP4EtgELBBRLYC/YF1IvJtYBdwvM9l+ttlqo1y2hnQsxtgQ1OD43samhr8u5zctopNxy9iTcOuMkBajWkYYz42xhxjjCkwxhRgdUEVGWP+BbwEXG7PojoFqDXGBHVNqbbDbWfAsDsGbt0Kzc3Wnw88AB07+h/v2DH4izgdZi2F2kFQqTSRdmMaIbwCXABsAQ4Bs1JbHZVobjsD1u3f6xo4OmZ3DC4MnJ4b+Noza8kzCO27riPZX9ixdGsplURp1dIIZLc4dtvPjTHmWmPM/zHGDDfG6CYZbZzTzoDR7AYIWIPR9QG7C9bX+89I0llLSkUsrYOGat8i3gI2lFC5oDzdUOFmLaVD15VSaSKTuqdUOxTRFrChhEob4umGys93XkU+YEB6dV0plQa0paHatnBpQzzBwG3WUqK6rrT1ojKUBg3VtvnOSHJTU+M+aykRC+40XYjKYBo0VNtXUmJNvw2VE8pzjmeqLlgtALfkg61Z56ED7yqDadBQ7Ueki+d8WwJOWrvgTtOFqAymQUO1H5EunnPb3Q/is+DOrZWSjqvUlQqgs6dU+xLJ4jm33/hFWrquWqOszH9GFmi6EJUxtKWhMlK+5Dtu95ovwSvIo5bolkBgi6d3b+jSxdrxzzOTSmdXqTSlQUNlpMt7XR4UIPIln8t7Xd76iycjcaBn4P2pp+DwYWudiGcm1ezZMGuWzq5SaUkCf1tra4qLi01lpWYcUQEqKkLvdxHueLwUFITes9zXwIHx6R5TKgwRWWuMKXY8pkFDtTuBq7zBakmkIqNsVpb7tN5AItaUYKUSLFTQ0O4p1f6k0zqJaMZJdHaVSgMaNFT709p1EvEcpHYaP8nJCd4DRGdXqTShQUO1P62ZHRXvFCBOa0eWLoUnntDNmFRa0jEN1f60ZkzDbeBaB6lVG6JjGkr5as22qpmUAkTXeqgECBk0ROQeEbnKofwqEVmUuGoplWCBCQoj7fppbddWsr7ENZOuSpBwLY1zgCUO5Y8Bk+NfHaXSXKwL/5L9Je42Q+z66xPzeardCBc0OhmHQQ9jTDMgiamSUmks1q6tZE/zdesu27NHWxuqVcIFjcMicmJgoV12ODFVUirNxdK1leyxkFDdZbpvh2qFcEHjNuBVEZkpIsPtxyxgpX1MKRWJZI+FhOouS8dBe5UxQgYNY8yrwL8BZwPL7MfZwFRjzCsJrptSbUeyx0JKSqzsuU50ZblqhbBTbo0xm4wxVxhjRtuPy40xHyejckplJKeWQSrGQh54IPHZelW7E3ITJhF5GfAdCDfAbuAtY8zTiaqUiFwHXAs0ASuNMf9pl98ClNrlc40xryeqDkrFJHDhoKdlAJFtABWoNWMhns9KRrZe1W6EXBEuIuMdivOBy4AvjDE3x71CImcDC4ALjTFHReQYY8w3InIy8CwwFugHrAIGG2OaQl1PV4SrpIr3inFdga5SIOYV4caYtx0e/wP8OzApEZUFfgIsMsYctevwjV0+BXjOGHPUGPMVsAUrgCiVPuI9SyoZG0IpFYWY0oiE++2+lQYDZ4jI+yLytoiMscuPA3b4nLfTLlMqfcR7q9jWpDxRKgHCpRHJd3j8HxG5E9gc64eKyCoR2eTwmII1zpIPnALcBDwvIlEtJBSROSJSKSKV1dXVsVZTqeglomUQa8oTX5qHSsVJuJbGWqDS/tPz/FmgC3B1rB9qjDnPGDPM4fEiVgviT8byAdAM9AF2Acf7XKa/XeZ0/SXGmGJjTHHfvn1jraZS0UtFyyBcQNA8VCqejDExPYDlsb43zHWvBn5hPx+M1SUlwFBgA9AJGAR8CWSHu97o0aONUhnh6aeNGTjQGBHrz6efjuw9XbsaY4UD69G1q/97Bw70P+55DByYmPtQGQ+oNC7fqTHvpyEi240xcV8lJCI5wFJgJFAP3GiM+at9bAEwG2gE5hlr8WFIOntKZYRY9/iIZHaV2z7kuue4chFq9lTaBY1406ChMkKsU2sjCQg6bVdFKVTQCLe4r8jtENDR5ZhSKlqxTtUdMMA5IPjO1iorc27F6LRdFYOQQQP4dYhjn8WzIkq1a5F8+TuJJCDoynAVR+EW950d6pGsSirV5oWbqus2QyrS2VrxmLarFOHXafynz/NpAcd+mahKKdXuhPryDzdlNt4BQdd0qBDC5Z5aZ4wpCnzu9Dpd6UC4ynjJHMiOdRaXalNizj2F/5augauydbtXpZIhmbv+JXtbWpVxwgWNwLTobseUUokS73xWoSR7W1qVccLNnhohIvuxWhVd7OfYrzsntGZKKau76MCB4PJETZmNdRaXajfCzZ7KNsbkGWNyjTEd7Oee17pOQ6lE8owv7NnjX967d+LGGDQVuwojptToSqkkcBpfAOjePXGD0pqKXYURcxqRTKGzp1TG0pxRKkVaM3tKKZUqyRwAVypCGjSUSlc6vqDSkAYNpdKVji+oNKRBQ6l0lqicUZoqRMUo3DoNpVRbE5gqxJPLCrQVo8LSloZS7U26pQrRVk9G0ZaGUu1NOqUK0VZPxtGWhlLtTTpN5U23Vo8KS4OGUu1NOk3lTadWj4qIBg2l2pt0msqbTq0eFRENGkq1R+my/WtZGXQMyH3asaMuYExjGjSUUqklEvq1SisaNJRSqbNgAdTX+5fV1+tAeBrToKGUSo2KCucNn8Aq13UbaSntgoaIjBSRNSKyXkQqRWSsXS4i8qCIbBGRjSJSlOq6KqVi5FmfEYoxLes2NHCkjbQLGsCvgDuNMSOB2+zXAN8HTrQfc4BHUlI7pZS/WFZ0u20w5UTXbaSVdFwRboA8+3kPoMp+PgX4vbF2jVojIj1F5FhjzNepqKRSithXdEe7DkPXbaSNdGxpzAPuEZEdwL3ALXb5ccAOn/N22mVBRGSO3bVVWV1dnci6KtU+uLUmYl3R7bYOw23mVH5+NLVVCZSSoCEiq0Rkk8NjCvAT4AZjzPHADUB5tNc3xiwxxhQbY4r79u0b7+or1b54WhPbtgWPM4Rb0e0WbNxWpXfrlqi7UHGSku4pY8x5bsdE5PfA9fbLPwCP2893Acf7nNrfLlNKJVKo1sSAAc4zoAYMiKzrasECK8AMGGAFkh/9yLkONTXxuRfVaunYPVUFjLefnwN8YT9/CbjcnkV1ClCr4xlKJUGo1kSoPFbhuq6cVqVrWpG0l45B40rg1yKyAfgl1kwpgFeAL4EtwGPANampnlLtTKgv8lB5rGJJRphOyRSVI7EmI7VdxcXFprKyMtXVUCpzBXYzgfVFHi7JYUGBc9fVwIFWyyLU5wV2W+neGkklImuNMcVOx9KxpaGUSiexZsWNNRlhuiRTVI7ScZ2GUirdlJTE9uWtyQjbHG1pKKUSQ5MRtkkaNJRSiZHqXfliSW+iwtKgoZRKjFROnw21IFG1igYNpVRipHL6bKzpTVRYGjSUUomRyr3I4901pl1dXjp7SimVOLHOumqtUOlNohVrJt82SlsaSqm2J55dY9rV5UeDhlKq7XHqGrviCuuLPtouplTPAkszGjSUUm2T78rysjJ48snYZlNpEkU/GjSUUm1fa7qYNImiHw0aSqm2rzVdTKmcBZaGdPaUUqrta+1sqlTNAktD2tJQSrV92sUUNxo0lFJtn3YxxY12Tyml2gftYooLbWkopdoHTQUSF9rSUEq1fZoKJG60paGUavuiWaehLZKQNGgopdo+t/UY27b5BwbdhyMsDRpKqbYv1HoM38CgyQnD0qChlGr7nNZp+PIEhkhbJO2YBg2lVNvnu07DjadLKtRx7apKTdAQkWkisllEmkWkOODYLSKyRUQ+F5GJPuWT7LItInJz8mutlMponqy3oQJHONpVlbKWxibgYmC1b6GInAzMAIYCk4CHRSRbRLKB3wLfB04Gfmifq5RS0QnXVRVOO91HwyMl6zSMMZ8CiEjgoSnAc8aYo8BXIrIFGGsf22KM+dJ+33P2uZ8kp8ZKqTbDsy7DM4YRqkvKSTvdR8Mj3cY0jgN2+LzeaZe5lTsSkTkiUikildXV1QmpqFIqg/lu0BRNd5UmOUxc0BCRVSKyyeExJVGf6WGMWWKMKTbGFPft2zfRH6eUymRO3VUdO0Lv3tbz7GzrT01yCCSwe8oYc14Mb9sFHO/zur9dRohypZSKXWB31YABViBp58HBTbrlnnoJeEZE7gP6AScCHwACnCgig7CCxQzg0pTVUinVtmgG3IilJGiIyA+A3wB9gZUist4YM9EYs1lEnsca4G4ErjXGNNnv+SnwOpANLDXGbE5F3ZVSqj0TE+3MgQxTXFxsKisrU10NpZTKGCKy1hhT7HQs3WZPKaWUSmMaNJRSSkVMg4ZSSqmIadBQSikVMQ0aSimlIqZBQymlVMQ0aCilVKpl0L7k6bYiXCml2hfPvuSebWY9mz1BWq5S15aGUkqlUobtS65BQymlUsltU6c03exJg4ZSSqWS26ZOabrZkwYNpZRKJaf9PNJ4sycNGkoplUolJdbmTgMHgkjab/aks6eUUirVMmg/D21pKKWUipgGDaWUUhHToKGUUipiGjSUUkpFTIOGUkqpiGnQUEopFTENGkoppSKmQUMppVTENGgopVRbkuC9OXRFuFJKtRVJ2JtDWxpKKdVWJGFvjpQEDRGZJiKbRaRZRIp9yieIyFoR+dj+8xyfY6Pt8i0i8qCISCrqrpRSaSsJe3OkqqWxCbgYWB1Qvhv4v8aY4cAVwFM+xx4BrgROtB+TklBPpZTKHEnYmyMlQcMY86kx5nOH8o+MMVX2y81AFxHpJCLHAnnGmDXGGAP8Hvi35NVYKaUyQBL25kjnMY2pwDpjzFHgOGCnz7GddpkjEZkjIpUiUlldXZ3gaiqlVJpIwt4cCZs9JSKrgG87HFpgjHkxzHuHAncD58fy2caYJcASgOLiYhPLNZRSKiMleG+OhAUNY8x5sbxPRPoD/wNcboz5p128C+jvc1p/u0wppVQSpVX3lIj0BFYCNxtj3vGUG2O+BvaLyCn2rKnLgZCtFaWUUvGXqim3PxCRncA4YKWIvG4f+inwHeA2EVlvP46xj10DPA5sAf4JvJrseiulVHsn1mSktqu4uNhUVlamuhpKKZUxRGStMabY6VhadU8ppZRKb22+pSEi1cC2GN/eB2vBYXui99z2tbf7Bb3naA00xvR1OtDmg0ZriEilWxOtrdJ7bvva2/2C3nM8afeUUkqpiGnQUEopFTENGqEtSXUFUkDvue1rb/cLes9xo2MaSimlIqYtDaWUUhHToKGUUipiGjQAEZkkIp/buwLe7HC8k4gst4+/LyIFKahm3ERwv/8hIp+IyEYReVNEBqainvEU7p59zpsqIsZ3R8lMFck9i8i/2//Wm0XkmWTXMd4i+NkeICJvichH9s/3BamoZ7yIyFIR+UZENrkcF3un0y32/Ra1+kONMe36AWRj5bI6AcgBNgAnB5xzDfCo/XwGsDzV9U7w/Z4NdLWf/yST7zfSe7bPy8XaTXINUJzqeifh3/lE4COgl/36mFTXOwn3vAT4if38ZGBrquvdyns+EygCNrkcvwArT58ApwDvt/YztaUBY4EtxpgvjTH1wHPAlIBzpgBP2s9XAOdm8B7lYe/XGPOWMcazO/0a/NPSZ6JI/o0BFmLt43IkmZVLkEju+Urgt8aYvQDGmG+SXMd4i+SeDZBnP+8BVJHBjDGrgZoQp0wBfm8sa4Ce9k6oMdOgYe0AuMPntdOugN5zjDGNQC3QOym1i79I7tdXKZmfUTjsPdvN9uONMSuTWbEEiuTfeTAwWETeEZE1IjIpabVLjEju+Q7gMjvL9ivAdcmpWspE+/89rIRtwqQyn4hcBhQD41Ndl0QSkSzgPmBmiquSbB2wuqjOwmpNrhaR4caYfamsVIL9EFhmjPm1iIwDnhKRYcaY5lRXLFNoS8PaAfB4n9dOuwJ6zxGRDljN2j1JqV38RXK/iMh5wALgImPt057Jwt1zLjAM+JuIbMXq+30pwwfDI/l33gm8ZIxpMMZ8BfwDK4hkqkjuuRR4HsAY8x7QGSuxX1sV0f/3aGjQgA+BE0VkkIjkYA10vxRwzkvAFfbzS4C/GnuUKQOFvV8RGQX8DitgZHo/N4S5Z2NMrTGmjzGmwBhTgDWOc5ExJpM3Yonk5/oFrFYGItIHq7vqyyTWMd4iueftwLkAInISVtCoTmotk+sl4HJ7FtUpQK2xdkKNWbvvnjLGNIrIT4HXsWZfLDXGbBaRXwCVxpiXgHKsZuwWrEGnGamrcetEeL/3AN2BP9jj/duNMRelrNKtFOE9tykR3vPrwPki8gnQBNxkjMnUFnSk9/wz4DERuQFrUHxmBv8CiIg8ixX4+9jjNLcDHQGMMY9ijdtcgLXj6SFgVqs/M4P/vpRSSiWZdk8ppZSKmAYNpZRSEdOgoZRSKmIaNJRSSkVMg4ZSSqmIadBQKg5EZJmIXJLqeiiVaBo0lFJKRUyDhlIxEJHL7f0JNojIU3bxmSLyroh86Wl1iEh3e0+SdSLysYhMscsLRORTEXnM3sviDRHpYh8bY197vYjc49krQUSy7dcf2sevSsnNq3ZNg4ZSURKRocDPgXOMMSOA6+1DxwKnA5OBRXbZEeAHxpgirH1Kfu2TVv9ErNTkQ4F9wFS7/AngKmPMSKyV2h6lWGkgxgBjgCtFZFD871Apd+0+jYhSMTgH+IMxZjeAMabGjgMv2NlSPxGRb9nnCvBLETkTaMZKS+059pUxZr39fC1QICI9gVw7mR7AM1hBCOB8oNBn7KQHVuD5Kv63qJQzDRpKxY9vNmBPa6IE6AuMNsY02Fl0Ozuc3wR0CXN9Aa4zxrweh7oqFRPtnlIqen8FpolIbwARyQ9xbg/gGztgnA2E3G/d3suiTkS+Zxf5Jsd8HfiJiHS0P3ewiHSL8R6Uiom2NJSKkp05tQx4W0SasPbZdlMBvCwiHwOVwGcRfEQpVibWZuBtrJ0iAR4HCoB19rhINfBvMd2EUjHSLLdKpRkR6W6MOWA/vxk41hhzfZi3KZUU2tJQKv1cKCK3YP3/3Eb724ZWpTFtaSillIqYDoQrpZSKmAYNpZRSEdOgoZRSKmIaNJRSSkVMg4ZSSqmI/X+HEF8EJbaJHQAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -1049,32 +1166,23 @@ } ], "source": [ - "trained_sample = trained_result.sample(frac=0.01, random_state=42)\n", + "print(f\"Heuristic threshold: {even_result['change'].max()}\")\n", + "\n", + "# Changed random seed to get a dominated point in the diffs\n", + "trained_sample = trained_result.sample(frac=0.01, random_state=43)\n", "even_sample = even_result.loc[trained_sample.index]\n", "perfect_sample = perfect_result.loc[trained_sample.index]\n", - "\n", - "plt.scatter(trained_sample[\"change\"], trained_sample[\"ELUC\"], color=\"red\", label=\"Evolved Prescriptor\")\n", - "plt.scatter(even_sample[\"change\"], even_sample[\"ELUC\"], color=\"green\", label=\"Even Heuristic\")\n", - "plt.scatter(perfect_sample[\"change\"], perfect_sample[\"ELUC\"], color=\"lightgreen\", label=\"Perfect Heuristic\")\n", - "# Rearrange legend (from stackoverflow)\n", - "handles, labels = plt.gca().get_legend_handles_labels()\n", - "order = [1, 2, 0]\n", - "plt.legend([handles[idx] for idx in order], [labels[idx] for idx in order])\n", - "plt.xlabel(\"change\")\n", - "plt.ylabel(\"ELUC\")\n", - "#plt.title(\"Expanded view of ~20% change prescriptors (subsampled)\")\n", - "#plt.savefig(\"figures/prescexpanded.png\", format=\"png\", dpi=300)\n", - "plt.show()" + "plot_expanded(even_sample, perfect_sample, trained_sample, figure_dir / \"prescexpanded.png\")" ] }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 56, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1096,12 +1204,12 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 57, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1123,12 +1231,40 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_diffs(perfect_sample, trained_sample, save_path=None):\n", + " diff_df = pd.DataFrame()\n", + " diff_df[\"change\"] = trained_sample[\"change\"] - perfect_sample[\"change\"]\n", + " diff_df[\"ELUC\"] = trained_sample[\"ELUC\"] - perfect_sample[\"ELUC\"]\n", + " # diff_df[\"change\"] = trained_result[\"change\"] - perfect_result[\"change\"]\n", + " # diff_df[\"ELUC\"] = trained_result[\"ELUC\"] - perfect_result[\"ELUC\"]\n", + " dom = diff_df[(diff_df[\"change\"] < 0) & (diff_df[\"ELUC\"] < 0)]\n", + " other_dom = diff_df[(diff_df[\"change\"] > 0) & (diff_df[\"ELUC\"] > 0)]\n", + " plt.scatter(diff_df[\"change\"], diff_df[\"ELUC\"], label=\"No domination\")\n", + " plt.scatter(other_dom[\"change\"], other_dom[\"ELUC\"], color=\"lightgreen\", label=\"Perfect Heuristic dominates\")\n", + " plt.scatter(dom[\"change\"], dom[\"ELUC\"], color=\"red\", label=\"Evolved Prescriptor dominates\")\n", + " plt.axhline(0, color=\"black\", linestyle=\"--\")\n", + " plt.axvline(0, color=\"black\", linestyle=\"--\")\n", + " plt.xlabel(\"Change Difference\")\n", + " plt.ylabel(\"ELUC Difference\")\n", + " #plt.title(\"Change Diff vs. ELUC Diff Between Trained and Perfect (subsampled)\")\n", + " plt.legend()\n", + " if save_path:\n", + " plt.savefig(save_path, format=\"png\", dpi=300)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 59, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1140,80 +1276,31 @@ } ], "source": [ - "diff_df = pd.DataFrame()\n", - "diff_df[\"change\"] = trained_sample[\"change\"] - perfect_sample[\"change\"]\n", - "diff_df[\"ELUC\"] = trained_sample[\"ELUC\"] - perfect_sample[\"ELUC\"]\n", - "dom = diff_df[(diff_df[\"change\"] < 0) & (diff_df[\"ELUC\"] < 0)]\n", - "other_dom = diff_df[(diff_df[\"change\"] > 0) & (diff_df[\"ELUC\"] > 0)]\n", - "plt.scatter(diff_df[\"change\"], diff_df[\"ELUC\"], label=\"No domination\")\n", - "plt.scatter(other_dom[\"change\"], other_dom[\"ELUC\"], color=\"lightgreen\", label=\"Perfect Heuristic dominates\")\n", - "plt.scatter(dom[\"change\"], dom[\"ELUC\"], color=\"red\", label=\"Evolved Prescriptor dominates\")\n", - "plt.axhline(0, color=\"black\", linestyle=\"--\")\n", - "plt.axvline(0, color=\"black\", linestyle=\"--\")\n", - "plt.xlabel(\"Change Difference\")\n", - "plt.ylabel(\"ELUC Difference\")\n", - "#plt.title(\"Change Diff vs. ELUC Diff Between Trained and Perfect (subsampled)\")\n", - "plt.legend()\n", - "#plt.savefig(\"figures/prescdiffs.png\", format=\"png\", dpi=300)\n", - "plt.show()" + "plot_diffs(perfect_sample, trained_sample, figure_dir / \"prescdiffs.png\")" ] }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 69, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Number less change better ELUC: 47\n", - "Max difference in ELUC with less change: time lat lon \n", - "2016 42.875 45.875 -0.20701\n", - "Name: ELUC, dtype: float64\n", + "Number less change better ELUC: 23 (0.09502561560072716%)\n", + "Max difference in ELUC with less change: -0.19959735870361328\n", "Changes\n", - "time lat lon \n", - "2016 42.875 45.875 0.35\n", - "Name: change, dtype: float64 time lat lon \n", - "2016 42.875 45.875 0.35\n", - "Name: change, dtype: float64 time lat lon \n", - "2016 42.875 45.875 0.342483\n", - "Name: change, dtype: float64\n", + "0.35000000073796705 0.35000000073796705 0.3332486968858965\n", "\n", "ELUCs\n", - "time lat lon \n", - "2016 42.875 45.875 -21.525127\n", - "Name: ELUC, dtype: float64 time lat lon \n", - "2016 42.875 45.875 -26.671085\n", - "Name: ELUC, dtype: float64 time lat lon \n", - "2016 42.875 45.875 -26.878096\n", - "Name: ELUC, dtype: float64\n", + "-6.7735514640808105 -6.147274971008301 -6.346872329711914\n", "\n", - "['crop: time lat lon \\n2016 42.875 45.875 0.171379\\nName: crop, dtype: float32', 'pastr: time lat lon \\n2016 42.875 45.875 0.007045\\nName: pastr, dtype: float32', 'primf: time lat lon \\n2016 42.875 45.875 0.0\\nName: primf, dtype: float32', 'primn: time lat lon \\n2016 42.875 45.875 0.515484\\nName: primn, dtype: float32', 'range: time lat lon \\n2016 42.875 45.875 0.064521\\nName: range, dtype: float32', 'secdf: time lat lon \\n2016 42.875 45.875 0.0\\nName: secdf, dtype: float32', 'secdn: time lat lon \\n2016 42.875 45.875 0.239296\\nName: secdn, dtype: float32', 'urban: time lat lon \\n2016 42.875 45.875 0.002275\\nName: urban, dtype: float32', 'cell_area: time lat lon \\n2016 42.875 45.875 56631.582031\\nName: cell_area, dtype: float32', 'lat: time lat lon \\n2016 42.875 45.875 42.875\\nName: lat, dtype: float64', 'lon: time lat lon \\n2016 42.875 45.875 45.875\\nName: lon, dtype: float64', 'time: time lat lon \\n2016 42.875 45.875 2016\\nName: time, dtype: int64']\n", + "['crop: 0.00019714348309207708', 'pastr: 0.0', 'primf: 0.0', 'primn: 0.09017181396484375', 'range: 0.2005922496318817', 'secdf: 0.0', 'secdn: 0.2404637336730957', 'urban: 0.0', 'cell_area: 77122.2734375', 'lat: 3.625', 'lon: 35.875', 'time: 2021.0']\n", "Prescribed:\n", - "['crop_diff: time lat lon \\n2016 42.875 45.875 -0.124383\\nName: crop_diff, dtype: float64', 'pastr_diff: time lat lon \\n2016 42.875 45.875 -0.005113\\nName: pastr_diff, dtype: float64', 'range_diff: time lat lon \\n2016 42.875 45.875 -0.046828\\nName: range_diff, dtype: float64', 'secdf_diff: time lat lon \\n2016 42.875 45.875 0.35\\nName: secdf_diff, dtype: float64', 'secdn_diff: time lat lon \\n2016 42.875 45.875 -0.173676\\nName: secdn_diff, dtype: float64']\n", - "['crop_diff: time lat lon \\n2016 42.875 45.875 -0.171379\\nName: crop_diff, dtype: float64', 'pastr_diff: time lat lon \\n2016 42.875 45.875 -0.007045\\nName: pastr_diff, dtype: float64', 'range_diff: time lat lon \\n2016 42.875 45.875 -0.064521\\nName: range_diff, dtype: float64', 'secdf_diff: time lat lon \\n2016 42.875 45.875 0.35\\nName: secdf_diff, dtype: float64', 'secdn_diff: time lat lon \\n2016 42.875 45.875 -0.107055\\nName: secdn_diff, dtype: float64']\n", - "['crop_diff: time lat lon \\n2016 42.875 45.875 -0.171379\\nName: crop_diff, dtype: float64', 'pastr_diff: time lat lon \\n2016 42.875 45.875 -0.007045\\nName: pastr_diff, dtype: float64', 'range_diff: time lat lon \\n2016 42.875 45.875 0.000371\\nName: range_diff, dtype: float64', 'secdf_diff: time lat lon \\n2016 42.875 45.875 0.342112\\nName: secdf_diff, dtype: float64', 'secdn_diff: time lat lon \\n2016 42.875 45.875 -0.164059\\nName: secdn_diff, dtype: float64']\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/4c/sd5grc691sx_dp1xqn1s9dyc0000gq/T/ipykernel_43643/3349738372.py:6: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " print(f\"Max difference in ELUC with less change: {eluc_diff[min_idx]}\")\n", - "/var/folders/4c/sd5grc691sx_dp1xqn1s9dyc0000gq/T/ipykernel_43643/3349738372.py:9: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " print(even_result.loc[min_idx][\"change\"], perfect_result.loc[min_idx][\"change\"], trained_result.loc[min_idx][\"change\"])\n", - "/var/folders/4c/sd5grc691sx_dp1xqn1s9dyc0000gq/T/ipykernel_43643/3349738372.py:12: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " print(even_result.loc[min_idx][\"ELUC\"], perfect_result.loc[min_idx][\"ELUC\"], trained_result.loc[min_idx][\"ELUC\"])\n", - "/var/folders/4c/sd5grc691sx_dp1xqn1s9dyc0000gq/T/ipykernel_43643/3349738372.py:14: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " print([f\"{col}: {even_result.loc[min_idx][col]}\" for col in constants.CAO_MAPPING[\"context\"]])\n", - "/var/folders/4c/sd5grc691sx_dp1xqn1s9dyc0000gq/T/ipykernel_43643/3349738372.py:16: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " print([f\"{col}: {even_result.loc[min_idx][col]}\" for col in constants.DIFF_RECO_COLS])\n", - "/var/folders/4c/sd5grc691sx_dp1xqn1s9dyc0000gq/T/ipykernel_43643/3349738372.py:17: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " print([f\"{col}: {perfect_result.loc[min_idx][col]}\" for col in constants.DIFF_RECO_COLS])\n", - "/var/folders/4c/sd5grc691sx_dp1xqn1s9dyc0000gq/T/ipykernel_43643/3349738372.py:18: PerformanceWarning: indexing past lexsort depth may impact performance.\n", - " print([f\"{col}: {trained_result.loc[min_idx][col]}\" for col in constants.DIFF_RECO_COLS])\n" + "['crop_diff: -8.310068555122573e-05', 'pastr_diff: 0.0', 'range_diff: -0.08455442299802755', 'secdf_diff: 0.18599872926351962', 'secdn_diff: -0.10136120557994083']\n", + "['crop_diff: -0.00019714348309207708', 'pastr_diff: 0.0', 'range_diff: -0.18580158578042755', 'secdf_diff: 0.18599872926351962', 'secdn_diff: 0.0']\n", + "['crop_diff: -0.00019714348309207708', 'pastr_diff: 0.0', 'range_diff: -0.002269297761808786', 'secdf_diff: 0.17709666862516876', 'secdn_diff: -0.17463022850076537']\n" ] } ], @@ -1221,7 +1308,7 @@ "low_change_idx = change_diff[(change_diff < 0)].index\n", "low_change_eluc_diff = eluc_diff[low_change_idx]\n", "low_change_neg_eluc_diff = low_change_eluc_diff[low_change_eluc_diff < 0]\n", - "print(f\"Number less change better ELUC: {len(low_change_neg_eluc_diff)}\")\n", + "print(f\"Number less change better ELUC: {len(low_change_neg_eluc_diff)} ({len(low_change_neg_eluc_diff) / len(change_diff) * 100}%)\")\n", "min_idx = low_change_neg_eluc_diff.sort_values().index[0]\n", "print(f\"Max difference in ELUC with less change: {eluc_diff[min_idx]}\")\n", "\n", @@ -1240,16 +1327,16 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 61, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Number of points where trained prescriptor prescribes less change than perfect heuristic AND produces better ELUC by more than predictor model MAE: 4\n", - "Average difference in change for these points: -0.007977895921654751\n", - "Average difference in ELUC for these points: -0.14235717058181763\n" + "Number of points where trained prescriptor prescribes less change than perfect heuristic AND produces better ELUC by more than predictor model MAE: 1\n", + "Average difference in change for these points: -0.016751303852070576\n", + "Average difference in ELUC for these points: -0.19959735870361328\n" ] } ], @@ -1263,12 +1350,39 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_avg_prescription(even_result, perfect_result, trained_result, save_path=None):\n", + " even_total_diffs = even_result[constants.DIFF_RECO_COLS].sum(axis=0) / len(even_result)\n", + " perfect_total_diffs = perfect_result[constants.DIFF_RECO_COLS].sum(axis=0) / len(perfect_result)\n", + " trained_total_diffs = trained_result[constants.DIFF_RECO_COLS].sum(axis=0) / len(trained_result)\n", + "\n", + " xticks = np.arange(len(constants.DIFF_RECO_COLS))\n", + "\n", + " plt.bar(xticks-0.3, even_total_diffs, 0.3, label=\"Even Heuristic\", color=\"green\")\n", + " plt.bar(xticks, perfect_total_diffs, 0.3, label=\"Perfect Heuristic\", color=\"lightgreen\")\n", + " plt.bar(xticks+0.3, trained_total_diffs, 0.3, label=\"Evolved Prescriptor\", color=\"red\")\n", + " plt.xticks(xticks, constants.DIFF_RECO_COLS, rotation=90)\n", + " plt.legend()\n", + " plt.grid()\n", + " #plt.title(\"Average land use change for each prescriptor\")\n", + " fig = plt.gcf()\n", + " fig.set_tight_layout(True)\n", + " if save_path:\n", + " plt.savefig(save_path, format=\"png\", dpi=300)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 63, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1280,23 +1394,7 @@ } ], "source": [ - "even_total_diffs = even_result[constants.DIFF_RECO_COLS].sum(axis=0) / len(even_result)\n", - "perfect_total_diffs = perfect_result[constants.DIFF_RECO_COLS].sum(axis=0) / len(perfect_result)\n", - "trained_total_diffs = trained_result[constants.DIFF_RECO_COLS].sum(axis=0) / len(trained_result)\n", - "\n", - "xticks = np.arange(len(constants.DIFF_RECO_COLS))\n", - "\n", - "plt.bar(xticks-0.3, even_total_diffs, 0.3, label=\"Even Heuristic\", color=\"green\")\n", - "plt.bar(xticks, perfect_total_diffs, 0.3, label=\"Perfect Heuristic\", color=\"lightgreen\")\n", - "plt.bar(xticks+0.3, trained_total_diffs, 0.3, label=\"Evolved Prescriptor\", color=\"red\")\n", - "plt.xticks(xticks, constants.DIFF_RECO_COLS, rotation=90)\n", - "plt.legend()\n", - "plt.grid()\n", - "#plt.title(\"Average land use change for each prescriptor\")\n", - "fig = plt.gcf()\n", - "fig.set_tight_layout(True)\n", - "#plt.savefig(\"figures/prescbar.png\", format=\"png\", dpi=300)\n", - "plt.show()" + "plot_avg_prescription(even_result, perfect_result, trained_result, figure_dir / \"prescbar.png\")" ] }, { @@ -1308,19 +1406,19 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 64, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[0.9330519770471174, 0.3597655415302683, -0.30921000776144275, -0.2718086416064531, -0.09501254090287084, -0.11921383231465675, 0.2264343213066571, 0.14329173717985333, 0.31016870759090026, -0.25688973673661797, -0.25944979642860755, 0.005204622358066269]\n" + "[0.9034329723590094, 0.5270310236124349, -0.3437839547324, -0.28288466448177985, -0.01656602250485311, -0.12650073998417496, 0.14500440468048173, 0.15880564682906545, 0.3730995714791435, -0.3173523153618355, -0.26850716728343194, 0.015444815120229402]\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1355,7 +1453,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 66, "metadata": {}, "outputs": [], "source": [ @@ -1375,157 +1473,12 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 67, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEWCAYAAABrDZDcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAABNdUlEQVR4nO2deZyN1f/A35+5MxglhMSQsTOWLBOVyFJNlGinfpVCIUX6EpGQZN+KrEXZKaJNC20qGnsGZWcsIVTWMXN+f5xnuMa9M3fMvfe5y3m/XvOa+5xznud8nnuf53zOOZ9zPh9RSmEwGAyG8CXCbgEMBoPBYC9GERgMBkOYYxSBwWAwhDlGERgMBkOYYxSBwWAwhDlGERgMBkOYYxSBIUeISD8RmeF0fL+I7BWR/0Skpp2yhRqieV9EjonIKrvl8QQReVVEplifY0VEiUikl669S0TuuMJzG4rIPm/IEQoYReAGEXlMRBKtBu2AiHwhIrd54brTRGSgl2T02rW8yHCgs1LqaqXUWn9WLCLfWY1kbn/W6yki0kZEfsrBJW4D7gRKKKXquLl+qvXM/iMi60Tk3hzUl2OUUoOUUu3sqFtE6ojI5yJyXET+FpFVIvK0HbIEOkYRuEBEugGjgUFAUeAGYDzQwkaxgoVSwCZ/VyoisUB9QAH3+bt+P1EK2KWUOplJmV+UUlcDBYCpwDwRKZixkLd65ZnhjzoyqfsWYBnwPVAOKAR0BJraJVNAo5Qyf05/QH7gP+DhTMrkRiuK/dbfaCC3ldcQ2Ae8DPwFHACetvKeBVKAc1YdS6z04sBHwGFgJ/CilX6tda3m1vHVwDbgSXfXyiCnAKMsOf4BNgJVne5hOLAHOARMAKKdzm0BrLPO2w7cbaWXRr9c/wJfA+8AM6zr/YduiE8C213I8y4wPEPaJ0A36/MrQLJ17a1Ak2z8bn2BFcBI4NMMedPQivwLS8YVwPXW73YM2ALUdCpfGfgOOI5Wavc55X0HtHM6bgP85HSsgA7An9b546zfoTJwBki1ZDju5j6KA4uBv63fur2V3jbD+f1dnJtRlqsseeKBfsAC67f6B2iHftanop/RZGAg4LDOLWf9zieAI8Bcp+tWsX77v61n51Ur3VUd/YAZVn6sJc+z6PfmAPA/p+tGAD3Rz9tRYB5wrVP+E8BuK683sAu4w833+BMwLpPnpSFu3lMr/x5grXUfe4F+Tnnp9/EU+v05AvR2yo8GpqOfrc1AD2Bfht/4svfd1nbPbgEC7Q+4GzgPRGZSZgDwK3AdUAT4GXjD6QE7b5WJApoBp4CCVv40YKDTtSKA1eiGLBdQBtgBJFj5dwEHrbomAwuczr3kWi7kTLCuXYCLjVExK28UusG5FsgHLAHesvLqoBuAOy35YoBKVt4v6MY2N9AA3WjPcKpTAeXcyNPAeqnEOi4InLZejIpWXnErLxYom43fbRvQCaiNVpBFM3xPR6y8POie4k60QnWgG8DlVtko61qvWr9HY+seK1r535G1IvjU+s5vQL/sd7sq6+Y+fkArrTxADev8xp6c75wPRAJdLNnzoxvkFKCl9ZtGAwuBiWiFcR2wCnjOOn82urGNsGS5zUrPh240X7bS8wF1rTxXdfTjckUw26qzmnV/d1j5XdDvVQn08zURmG3lxaEVYAMrbyT6PbtMEQB50QqzUSbfVUMyf08bWvJFANXRCq9lhvuYbN3jjcBZoLKVPxitRAta97IBSxGQxftuW7tnZ+WB+Ac8DhzMosx2oJnTcQJ6yJ7+AJ3GSZGgexw3W5+ncakiqAvsyXD9XsD7Tsdvo3vzyUAhp/RLruVCzsbAH8DNQIRTuqB77WWd0m4BdlqfJwKjXFzvBuvlucopbRaeKwJB96AaWMftgWXW53LW93QHEJXN3+w2dANU2DreAryU4Xua7HT8ArDZ6bgaVg8dPb10MMP3NRurR4hniuA2p+N5QE9XZV3cR0l0A5bPKe0tYJqH57exfp/jaMX3Kxcb2X7AD05li6IbL+dRYGsuKsQPgEloewQZyqx1U/8ldTilZVQElZzyhwJTrc+bcRoFAsWs3zUS3XDOccq7Cj0adqUIYjLW46JMQzJ5T12UH431TjjdRwmn/FVAK+vzJQ07emSUrgiyfN/t+DM2gss5ChTOYn6zOHqIms5uK+3CNZRS552OT6GndVxRCihuGbSOi8hxdG+0qFOZSUBVdINw1LPbAKXUMvTUzTjgLxGZJCLXoEcxeYHVTnV+aaWDbpC2u7hkceCYunSOereLcu7kUcAcdGMC8Bgw08rbBnRFNxx/icgcESnu4jKueAr4Sil1xDqeZaU5c8jp82kXx+m/T3Fgr1IqzSl/N7px8ZSDTp8z++0zUhz4Wyn1bw7q/lUpVUApVVgpdbNS6hunvL1On0uhe8IHnJ6BieiRAejpDAFWicgmEXnGSnf3bLiqw5Myzu9OKWChkzyb0YqxqFXmwnnWM+juXTgGpKEVSWa4fU9FpK6ILBeRwyJyAj3dVzjD+e5+50tk5fLvPav33e8YRXA5v6B7Si0zKbMf/YOmc4OV5gkqw/FedE+8gNNfPqVUMwARcaAVwQdAJxEpl8m1Lq9MqbFKqdrooXUFoDu6t3gaqOJUZ36ljYzpMpV1cbkDQEERucop7YYs7/hSZgMPiUgpdO/oIydZZymlbkN/twoYktXFRCQaeAS4XUQOishB4CXgRhG5MZuygf4dS4qI87txA3o0Bnokldcp7/psXDur32s/cK2I5HNTd05xrn8v+jkv7PQMXKOUqgKglDqolGqvlCoOPAeMt569vejpDE/qcEdJp8/O785eoGmGdyGPUioZ/exdOE9E8qINwJcLoNQp9Hv8oAeyuGMWeuq0pFIqP9qGJh6eewA9JZSO8/1m+r7bhVEEGVBKnUAPQ8eJSEsRySsiUSLSVESGWsVmA31EpIiIFLbKz3B3zQwc4tIXaRXwr4i8IiLRIuIQkaoicpOV/yr65XoGGAZ8YCkHV9e6BBG5yerZRKEbsDNAmtXbnQyMEpHrrLIxIpJgnToVeFpEmohIhJVXSSm1G0gE+otILms5bXMP7xsApZeUHgGmAEuVUset+iuKSGNr6ecZtKJKc3uhi7RE9xrj0HPqNdC2kB/RNoDsshLdu+th/e4N0fc4x8pfBzxgPRfl0EZcTzkElBCRXK4ylVJ70famt0Qkj4hUt67v6bPlMUqpA8BXwAgRucb6ncuKyO0AIvKwiKQ3ZsfQz2Aa2v5RTES6ikhuEcknInWzWf1r1vdXBXgamGulTwDetDoJWO9XCytvAXCviNxmfX8DyLz96gG0EZHuIlLIut6NIjInk3OcyYcenZ0RkTro0aunzAN6iUhBEYkBOjvlZfW+24JRBC5QSo0AugF90Masvegfc5FVZCC6QdyAnrtfY6V5wlQgzhoWLlJKpQL3ohuwnVxsJPOLSG1LjietckPQL2RPV9dyUdc16Ab/GBdXWwyz8l5BG0V/FZF/gG/QBluUUqvQL+gotNH4ey6OgB5D9+T/Bl5Hj1Syyyy0LWCWU1putJHtCBeN470ARORxEXG3JPUp9PzqHqsXe1ApdRA9JfZ4dpcwKqXOoRv+ppYs49Hf/xaryCj03PQh9MqQmdm4/DL0KqSDInLETZnW6Dno/Whj7usZpne8yZNog2US+hlZwMXplJuAlSLyH7pn3EUptcOatroT/R0dRK+OapTNer9HP3vfoleRfWWlj7Hq+kpE/kXbOOoCKKU2Ac+jn5kDlrxuN4QppX5G28gaAztE5G/0yPpzD2XsBAyw5OiLbtw9ZYAl2070e7UAPfois/c9G9f3OumrNwwGg8HgA0SkI9qQfLvdsrjDjAgMBoPBi4hIMRGpZ023VUQvtV1ot1yZYdvOP4PBYAhRcqFXYJVGL+Wdg55iDFjM1JDBYDCEOWZqyGAwGMKcoJsaKly4sIqNjbVbDIPBYAgqVq9efUQpVcRVXtApgtjYWBITE+0Ww2AwGIIKEXHrBcBMDRkMBkOYYxSBwWAwhDlGERgMBkOYYxSBwWAwhDlGERgMBkOY4zNFICLvichfIvK7m3wRkbEisk1ENohILV/JYjAYDAb3+HJEMA0d9tEdTYHy1t+z6Hi2BoPBYPAzPttHoJT6QURiMynSAvjAilr1q4gUEJFilp90r7JobTLDlm4lcucOIkqUoMu91WhZMztBnwwGg8E+Tp48yeHDh/HVZlo7N5TFcGkIt31W2mWKQESeRY8auOGG7AXEWrQ2mV4fb+Tc2XN8taA/AK9t7wpdWhllYDAYAp5ly5bRvn178ufPT2JiIhER3p/ICQpjsVJqklIqXikVX6SIyx3Sbhm2dCunU1JJjXDQv0l7cp8/x4zp3Ul5/gX47z8fSWwwGAw54/jx47Rv354mTZoQERHBqFGjfKIEwF5FkMylsTxL4L3YrBcrOX76wucfytTmrrbjmF77Xh78ZRFUrQo7d3q7SoPBYMgRqamp3Hrrrbz33nv06NGDDRs2cPvtvotrY+fU0GKgsxVDtC5wwhf2AYcIqU6utk/liqb/Hc/xReUGzGM9pE81KQXiaWxqg8Fg8D5Hjx7l2muvxeFw8Oabb1KyZEni4+N9Xq8vl4/OBn4BKorIPhFpKyIdRKSDVeRzYAc6dulkdIxQr5PqJt7CqpjK8OGH4HDA4cNw443w8ce+EMFgMBgyRSnFjBkzqFChAlOmTAHg/vvv94sSAN+uGmqdRb5CB6P2KTEFoi+ZHnJOv8Dx4xAZCQ8+qP/eeQeuv97XohkMBgN79+6lQ4cOfP7559x8883Uq1fP7zIEhbE4J3RPqEh0lOOStOgoB90TKl5MKF8eVq6Et96CTz+FuDiYNk1PFxkMBoOPmD17NlWqVOG7775j9OjR/PTTT8TFxfldjpBXBC1rxvBg7Rgc1vy/Q4QHa8dcvnQ0Kgp69oT166FKFViyxNgMDAaDTylYsCB169bl999/p0uXLjgcjqxP8gFBF7M4Pj5eZScwTfo+gtMpqRfSoqMcvPVAJpvK0tLg5EnIlw/++AOWLoXnnwcfLd0yGAzhwfnz5xk1ahTnzp2jd+/egLYPiB86nSKyWinl0ugQ8i1b+j4CZ06npDJs6Vb3J0VEaCUAeoroxRehfn3YvNl3ghoMhpBm/fr13HzzzReWg6Z3wv2hBLIi5BXBfheG4szSL+PNN+GDD2DLFqhRAwYNgpQU7wloMBhCmrNnz/Laa68RHx/P3r17mT9/PnPmzAkIBZBOyCuC4s6rgzxIvwwReOIJSEqCli2hd28YOdJ7AhoMhpDmzz//ZMiQITz22GMkJSXx0EMPBZQSgDBQBI0quXZJ4S7dLUWLwty52ojcubNO27YNTns4sjAYDGHDf//9x8yZMwGoWrUqW7ZsYfr06RQqVMhmyVwT8opg+ZbD2UrPknvvhauugvPn4Z579HTRTz9duYAGgyGk+Prrr6lWrRpPPPEEmy27YpkyZWyWKnNCXhG42kyWWbrHREbCuHFw7pw2JHfuDP/+m7NrGgyGoOXYsWO0bduWu+66i1y5cvH9999TuXJlu8XyiJBXBBFupuLcpWeLO+6AjRuhSxcYP17vP9ixwwsXNhgMwURqair16tVj+vTp9OrVi/Xr11O/fn27xfIYO53O+YU0N9sk3KVnm6uvhtGj4dFH4d13oVQpq4I0s+/AYAhxjhw5csFJ3KBBg7jhhhuoVSv4ou6alspb3HKLXmaa7sSuWjWYN8+4qTAYQhClFB988MElTuJatmwZlEoAwkARREe5vkV36V7hxAmIjtajhAcegP37fVeXwWDwK7t376Zp06Y89dRTVK5cmQYNGtgtUo4JeUWQJ8q17w536V6hXDn49VcYOhS+/FI7sZs61YwODIYgZ8aMGVStWpWffvqJt99+mx9//JFKlSrZLVaOCXlFcOyU613A7tK9RmQkdO8OGzboWAdffmmc2BkMQU6RIkWoV68emzZtonPnzj4LHelvQt5YbDvly8Py5XDqlD7eulUrhc6dtT3BYDAELCkpKYwYMYKUlBRee+01EhISuOuuuwJuZ3BOCQ11FuhEROjVRaCjonXtCrfdpt1WGAyGgGTt2rXUrVuXXr16kZSUFFBO4ryNUQT+5o03YMYM+PNPqFlTH587Z7dUBoPB4syZM7z66qvcdNNN7N+/n48++ojZs2eHpAJIJ+QVQaSbnWPu0n2OCDz+uB4NPPAA9O0Lo0bZI4vBYLiMbdu2MXz4cJ588kk2b97MAw88YLdIPifkbQSpbnaOuUv3JYvWJjNs6Vb2Hz9N8QLRdO8xnJZPPAG3364L/PEHlCgBefP6XTaDIZz577//WLhwIU888QRVq1Zl69atlC5d2m6x/EbIjwjcNff+VgPpkdKSj59GoX0d9fp4I4uK3XjRiV3z5nqF0fff+1k6gyF8Wbp0KVWqVOGpp5664CQunJQAhIEicLiZ13OX7iuyjJQWGaldVKSlQcOG0LEj/POPX2U0GMKJo0eP8tRTT3H33XeTN29efvzxx6BxEudtQl4RtK5bMlvpvsKjSGmNG2sndi+/DJMmGSd2BoOPSHcSN3PmTHr37s3atWupV6+e3WLZRsjbCAa2rAbA7JV7SVUKhwit65a8kO4viheIdun6+rJIaXnzwvDh8MgjMGGCcWJnMHiRw4cPU6hQIRwOB0OGDKFUqVLUqFHDbrFsR1SQuT2Ij49XiYmJdouRbdJtBM7TQ9FRDt56oBota8ZkfvJff+npor59tf+iEF7GZjD4AqUU06ZNo1u3bgwePJjnnnvObpH8joisVkrFu8ozXUw/0bJmDG89UI2YAtEIEFMg2jMlADrgzdVXQ+vWOm5ycrKvxTUYQoZdu3aRkJDAM888Q7Vq1WjUqJHdIgUcYTEiuGzZZkJFzxrgQCI1FcaMgT59ICpKTx+1a2dGBwZDJnz44Yd07NgREWHo0KE899xzIeMfKLuE9YjA7bLNtUHWq3Y4oFs3bUyuXRu++sooAYMhC4oWLUqDBg3YtGkTHTt2DFslkBUhPyKoN3iZSyNtTIFoVvRs7E3R/IdScPKkni7asgU++0z7LzJO7AxhTkpKCkOHDiU1NZW+ffvaLU5AEdYjAo+WbQYbIhed2M2cCf/7n46Q9vvv9splMNjImjVruOmmm+jTpw9bt24l2Dq5dhLyiuCy5ZlZpAcdAwbA7NmwcyfUqgX9+hkndoaw4vTp0/Ts2ZM6depw6NAhFi5cyMyZM0PaSZy38akiEJG7RWSriGwTkZ4u8m8QkeUislZENohIM2/L0D2hItEZopFFRznonlDR21XZgwi0agWbN+u9B/37w8iRdktlMPiNHTt2MHLkSNq0aUNSUhItW7a0W6Sgw2c2AhFxAH8AdwL7gN+A1kqpJKcyk4C1Sql3RSQO+FwpFZvZdcN21ZCnLF0K9evrjWlbt0LJksaJnSHk+Oeff/j4449p06YNoOMIl0rffGlwSWY2Al/uLK4DbFNK7bCEmAO0AJyjsSjgGutzfsAnUd5b1owJ3YY/IwkJ+v/583Dfffr/lClg1k4bQoTPP/+cDh06kJycTN26dalcubJRAjnEl1NDMcBep+N9Vpoz/YD/E5F9wOfAC64uJCLPikiiiCQePnzYF7KGHpGR2l9RRIT2YfTss3DihN1SGQxXzJEjR3jiiSe45557yJcvHytWrAhbJ3Hexm5jcWtgmlKqBNAM+FBELpNJKTVJKRWvlIovUqSI34UMWm6/Hdavh+7dYepUiIuD7dvtlspgyDbpTuLmzJlD3759WbNmDTfffLPdYoUMvpwaSgacXXyWsNKcaQvcDaCU+kVE8gCFgb98KFfQky2bR968MHToRSd2sbE63TixMwQBhw4dokiRIjgcDoYPH06pUqWoXr263WKFHL5sCX4DyotIaRHJBbQCFmcoswdoAiAilYE8gJn7yYQr3ikdH69tBQ6HdmIXFwezZunNaQZDgKGUYurUqVSsWJFJkyYB0Lx5c6MEfITPFIFS6jzQGVgKbAbmKaU2icgAEbnPKvYy0F5E1gOzgTbK7ALJlCwD3HjCf/9BwYI6dnLz5rB3b9bnGAx+YseOHdxxxx20a9eOGjVqcMcdd9gtUsjj03gESqnP0UZg57S+Tp+TAJ9Hgwil5aNe2Sldpgz89BO88w68+qoOgDN0KDz3nPFfZLCV6dOn06lTJxwOBxMmTKB9+/bGP5AfCPlveNHaZLrPX3/JVEr3+eu94nRu0dpk6g1eRumen1Fv8DK/OLLz2k5phwO6dNFO7OrUgeXLjRIw2E7x4sVp3LgxSUlJYe0p1N+EvNO5Gv2/4vjplMvSC0RHse71u65YjhwFmskBPqlXKTh9WhuWt2yBJUvgpZf0ElSDwYecO3eOwYMHk5aWRr9+/ewWJ6QJa6dzrpRAZume4pW5+isgRwFu3CFycffxrFnQo4d2Yrdhg1dkNhhc8dtvv1G7dm1ef/11duzYYZzE2Yjp8l0hdno19elO6f79oVo16NxZxz3o1Qt694bcuX1TnyHsOHXqFH379mXUqFEUK1aMxYsX07x5c7vFCmtCfkRQMG9UttI9JWS9morAww9DUpIOjfnGGzBqlN1SGUKInTt38vbbb9O+fXs2bdpklEAAEPKK4J7qxbKV7ikh79W0UCH44AMdCe3FF3Xali06II7BkE1OnDjB+++/D0CVKlXYtm0bEyZMIH/+/DZLZoAwUATLt7jen+Yu3VN8MlcfiNx5p7YfpDuxq1YNvvnGbqkMQcRnn31GlSpVaNeuHVu2bAGgZMmSWZxl8CchbyPw5Vx+WHk1jYzUO5PbtdPK4ZlnYPhwvTHNYHDB4cOH6dq1K7NmzaJq1ap8/PHHVKpUyW6xDC4I+RFByM7l20GDBtqJXc+eMH26dlOxbZvdUhkCkNTUVG677Tbmz59P//79Wb16NXXq1LFbLIMbQl4RhPxcvr+Jjoa33oJVq7R7itKldXpqaubnGcKCgwcPkpaWhsPhYMSIEaxZs4a+ffuSK1cuu0UzZELIK4KWNWN4sHYMDmvXrEOEB2uH0ZSOr6hVS8c7cDjg0CGoXBk+/NA4sQtT0tLSmDhxIhUqVGDixIkA3HvvvVStWtVmyQyeEPKKYNHaZD5anUyq1UClKsVHq5P94g4ibDh1CooUgSefhGbNYM8euyUy+JFt27bRpEkTOnTowE033URCepQ8Q9AQ8orArh3AYUXp0vDjjzB2rP5fpQqMG2dGB2HA+++/T7Vq1VizZg2TJ0/mm2++oUyZMnaLZcgmIa8Ikt2sDnKXbrhCIiLghRfg99/h1lvhhx+ME7sw4IYbbiAhIYGkpCTatWuHmN88KAn55aMirjum5nn1EbGx8OWX2okdwObNsHgxvPyycWIXApw9e5a33nqLtLQ0BgwYQJMmTWjSpIndYhlySMiPCNzNTphZCx/i7MRu7ly93LRuXVi3zlaxDDlj5cqV1K5dm/79+7Nnzx7jJC6ECHlFYLCZfv1gwQJITtbhMnv3hjNn7JbKkA1OnjxJt27duOWWWzhx4gSffvop06ZNM9NAIUTIKwJfOZ0zZIMHH9RO7J58EgYNgtGj7ZbIkA12797N+PHj6dChA5s2beKee+6xWySDlwl5RfB68ypEOS7tuUQ5hNebV7FJojDl2mvhvffg228vOrHbvFnHTzYEHMePH2fKlCkAxMXFsW3bNsaPH88111xjs2QGXxDyiqBlzRiGPXTjJc7hhj10o9lQZheNG190YteiBVStqj2cGgKGTz75hLi4ODp06HDBSVyJEiVslsrgS8JiGUdYOYcLFiIj4f33tRO7hARo0wZGjNAjB4Mt/PXXX7z44ovMnTuX6tWrs3jxYuMkLkwI+RGBIYCpVw/WrtUG5A8/NE7sbCQ1NZV69eqxcOFCBg4cSGJiIvHxLsPbGkKQsBgRGAKYPHlg4EB46CGYMAHSd6Wmpmo/Rgafsn//fq6//nocDgdjxowhNjaWuLg4u8Uy+BkzIjAEBjVqaEUQEaGd2FWsCNOmmQ0fPiItLY13332XSpUqMWHCBACaNWtmlECYYhSBIfA4fRqKFYOnn9b2g1277JYopPjjjz9o1KgRnTp1om7dujRt2tRukQw2YxSBIfCIjYXvv9eO6375Ra8sGjvWjA68wNSpU7nxxhvZsGED7733Hl999RWl02NKGMIWowgMgUlEBHTqpJ3Y1a+vFYLZyZpjYmNjadq0KUlJSTz99NNmd7ABAAk2fyHx8fEqMTHRbjEM/kQp7ZYiOlrvUF64EHr0gCizOzwrzp49yxtvvAHAwIEDbZbGYCcislop5XIpmBkRGAIfEa0EAObPhz594KabYM0ae+UKcH7++Wdq1KjBm2++yYEDB4yTOINbjCIwBBevv65HBIcOQZ062rPpaRNbwpn//vuPLl26cNttt3Hq1Cm+/PJLpk6daqaBDG7xqSIQkbtFZKuIbBORnm7KPCIiSSKySURm+VIeQ4jQsqWeImrTBoYMgTFj7JYooNizZw8TJ07k+eef5/fffzehIw1Z4jMbgYg4gD+AO4F9wG9Aa6VUklOZ8sA8oLFS6piIXKeU+iuz6xobgeESvvtOxzqIjoZNm+CGGyBfPrul8jvHjh1j/vz5PPvss4DeKFa8eHGbpTIEEnbZCOoA25RSO5RS54A5QIsMZdoD45RSxwCyUgIGw2U0bKiVwPnzeqRQpQp88YXdUvmVhQsXEhcXR6dOndi6VcfiNkrAkB18qQhigL1Ox/usNGcqABVEZIWI/Coid7u6kIg8KyKJIpJ4+PBhH4lrCGoiI+GDD+Dqq6FZMx374OhRu6XyKQcPHuThhx/mgQce4Prrr2fVqlVUrFjRbrEMQYjdxuJIoDzQEGgNTBaRAhkLKaUmKaXilVLxRYoUyXYli9YmU2/wMkr3/Ix6g5exaG1yDsU2BCS33KKd2L32GsyeDZUrw59/2i2VT0hNTaV+/fosWbKEQYMGsWrVKmrVqmW3WIYgxZdO55KBkk7HJaw0Z/YBK5VSKcBOEfkDrRh+85YQi9Ym0+vjjZxOSdVCHT9Nr483AhjX1KFI7twwYMBFJ3Zly+r08+f1qCHI2bdvH8WLF8fhcDB27FhKly5tXEUbcowvRwS/AeVFpLSI5AJaAYszlFmEHg0gIoXRU0U7vCnEsKVbLyiBdE6npDJs6VZvVmMINKpXh/Hj9Q7lgwehQgWYOjVo3VSkpaXx9ttvU6lSJd59910AmjZtapSAwSt41EUSkbzAy8ANSqn21mqfikqpT92do5Q6LyKdgaWAA3hPKbVJRAYAiUqpxVbeXSKSBKQC3ZVSXp3Y3X/c9Rpzd+mGEOTsWb2aqF07PWU0adJFd9dBwJYtW2jXrh0rVqwgISGBe++9126RApaUlBT27dvHmTNn7BbFNvLkyUOJEiWIysbOe0/Hyu8Dq4FbrONkYD7gVhEAKKU+Bz7PkNbX6bMCull/PqF4gWiSXTT6xQtE+6pKQ6BRqhQsWwaTJ0P37lCtGrz5JnTpEvD+i6ZMmULnzp3Jmzcv06dP54knnjAbwzJh37595MuXj9jY2LD8npRSHD16lH379mXLmaCnU0NllVJDgRSrslNAUHzL3RMqugxe3z3BrK4IKyIi4Lnn9Ea0Ro1g5cqAVwIAZcuWpXnz5mzevJknn3wyLBu37HDmzBkKFSoUtt+TiFCoUKFsj4g8HRGcE5FoQFmVlQXOZk9E+0hNVZkeG8KIEiVgyRI9XQRaMXz0EbzyCuTKZa9s6IZswIABAAwaNIhGjRrRqFEjm6UKLsJVCaRzJffv6YjgdeBLoKSIzAS+BXpkuzYb6Ld4E2kZ0tKsdEOYIqJDZIJWAn37Qnw8/Oa1xWpXxIoVK6hRowZvvfUWhw8fNk7iDH7DI0WglPoaeABoA8wG4pVS3/lOLO9x/HRKttINYcZrr8Enn+jNZzffrN1bnzrlVxH+/fdfXnjhBerXr8/Zs2dZunQpkydPDvuercF/eKQIRKQWUAo4AOwHbhCRsiIS/AuzDYb77tNTRG3bwrBhfndit2/fPqZMmcILL7zAxo0bueuuu/xav8F79O3bl9GjR1847t27N2OyeJ5OnDhBxYoVL7gHad26NZMnT/almJfhaUM+HqgFbEAbiasCm4D8ItJRKfWVj+TLMVflcnDyXKrLdIPhAvnz62Wl//d/OtYB6OhoJUvqPC9z9OhR5s2bR8eOHalcuTI7duygWLFiXq8n3GnYsOFlaY888gidOnXi1KlTNGvW7LL8Nm3a0KZNG44cOcJDDz10Sd53332XaX3PPPMMDzzwAF27diUtLY05c+awbNkyatSo4bL8rFmziIuL45133qFNmzZ06dKFY8eO0b59e09v0St4qgj2A22VUpsARCQOGIC2E3wMBKwiiHJEoLcouEoPPRatTWbY0q3sP36a4gWi6Z5Q0eygzg4NGuj/qalw//061sHEiXDPPV65vFKKjz76iOeff56///6bxo0bU7FiRaMEQoTY2FgKFSrE2rVrOXToEDVr1qRUqVKsW7cu0/PuvPNO5s+fz/PPP8/69ev9I6wTniqCCulKAEAplSQilZRSOwJ9HjOcbATGnYYXcThg5kw9XXTvvfDYYzB6NFyBr6t0Dhw4wPPPP8/ChQupXbs2X331lXES52My68HnzZs30/zChQtnOQJwRbt27Zg2bRoHDx7kmWee4d9//6V+/fouy6aPCNLS0ti8eTN58+bl2LFjlChRItv15gRPFcEmEXkX7Uoa4FEgSURyY+0tCFQEa82ri/RQIzN3GkYRXAF16sDq1fDWW3oD2ldfwc8/Q/ny2b5UupO45ORkhg4dyksvvURkCPg+MlzO/fffT9++fUlJSWHWrFk4HI4sRwSjRo2icuXKDBo0iKeffppffvklWzuDc4qnT2IboBPQ1TpeAfwPrQQCepGzuwV4obgwz7jT8AG5cunwmA8+qKeI0p3YpaSABy/q3r17iYmJweFwMG7cOEqXLk2FChV8LLTBTnLlykWjRo0oUKAADkfWtsitW7cyZcoUVq1aRb58+WjQoAEDBw6kf//+fpBW4+ny0dNKqRFKqfutv+FKqVNKqTSl1H++FtLgGe7cZhh3GjlnUUpB6sXcT+lXv6B57wWcjC2rXVa4WeufmprK2LFjL3ESl5CQYJRAGJCWlsavv/5K27ZtPSpfsWJFNm/eTD4rst7IkSP9qgTA8+Wj9UTkaxH5Q0R2pP/5WjhvUDCv616bu/RgpntCRaKjLu2BREc5jDuNHJJue0k+fhoFHD32LxujroVnn4UmTWD79kvKb968mfr169OlSxduv/12mjdvbo/gBr+TlJREuXLlaNKkCeWvYArRLjxdOjMVGAncBtzk9Bfw3FPd9WoMd+nBTMuaMbz1QDViCkQjQEyBaN56oJqxD+SQjLaX/ddcR6tHBzL4/m7ahlCtGowcCUoxadIkatSowR9//MGHH37IZ599xg033GCj9AZ/EhcXx44dOxgxYoTdomQLT20EJ5RSQRkIdvkW16Et3aUHOy1rxpiG38u4tLGIMLFCY3q+3Q06dtQKQYTy5ctz//33M3bsWK677jr/C2swXAGeKoLlIjIMvWfggrM5pdQan0jlRVy5oM4s3WDISGauzE9fey39KlUiKi2NgUCjIkVoVKkSFCjgdzkNhivF06mhukA8MAgYYf0N95VQ3sThZp+Du3SDISPubC/NCh/jxhtvZOiwYRw9eVI7ifvkE+jfH2rVglWrbJLYYMgeHo0IlFIBvUQ0M1Ldreownh0NHpI+1Za+Y/u6PGlcmzSPPgM/oEyZMnz77bc0btxYF+7dG2rUgA4d4JZboGtXHUP5qqtsk99gyAqPd7SIyD1AFSBPeppSaoAvhPImMW6G9TFmSaUhGzjbXrZs2UKtWvPp1q0bAwYM4KqMjfw998CmTdCzpzYiFy4MvXrZILUhWHjnnXcYPXo027dv5/DhwxQuXNiv9Xu6fHQCejfxC+hNuQ+jvZEGPGZJpcEbHDlyhPHjxwNQqVIldu7cyYgRIy5XAulccw2MHw8//aRHBQAbN8KJE/4R2BBU1KtXj2+++YZSpexpVj21EdyqlHoSOKaU6o+OXRwUO2PMkkpDTlBKMXfuXOLi4ujatSt//PEHAEWLFvXsAvXqQXS0dmL3wAMQF6cjpBlCkitxQw1Qs2ZNYmNjMy3jS3fVnk4Npc+tnBKR4sBRIGgW4psllYYrYf/+/XTs2JHFixcTHx/Pt99+e+U7gx0OmD0bnnlGxz9o1UrHPTBLTH2LCzfUPPIIdOqkAxC5cENNmzb678gRyOCGGh+5ofaE/Pnz+8xdtaeK4FMRKQAMA9agXfVM8YoEBkMAkpqaSoMGDUhOTmb48OF06dIl507i4uMhMRGGDoU33oCvv9ZO7IzbiZDhSt1Qe4qv3FV7umroDevjRyLyKZBHKRU0k53GR7/BU3bv3k2JEiVwOByMHz+eMmXKUK5cOe9VkCsX9Omjp4kmToT0a3voxM6QTTLrwefNm3l+4cJZjgBccSVuqN2RkJDAoUOHiI+PZ8qUKT5zVy2eBsgWkVuBWJyUh1LqA69IkQ3i4+NVYmKix+Uz+ugHbSw2dgKDM6mpqYwZM4Y+ffowdOhQOnfu7L/K9+/X8ZJ79YLnnoOI0Aya5A82b95M5cqVbZXh3LlzVKtWjZSUFP7880+PPJCmExsbS2JiottVQyNGjGDr1q088cQTvPTSS27dVbv6HkRktVIq3tV1PV019CF6A5mzryGXFww0MvPRbzAA/P7779x66628/PLLNGnShJYtW/pXgNRUqFhRz1s3agR//unf+g1eJd0N9SOPPOKxEhg7diwlSpRg3759VK9enXbt2l1WJt1d9YgRI6hfv/4Fd9XewKMRgYhsBuKUp8MHH5LdEUHpnp+5DUyzc7B3wg8agpcJEybw4osvkj9/fsaOHUurVq2wJeqeUjBtGnTrBmfO6N3J3buD2QGfLQJhRJCWlkatWrWYP3++bR5IfTIiAH4Hrs+hbLaQP9r1vKu7dEN4kN6nqVy5Mg8//DBJSUm0bt3aHiUAusF/+mlISoKmTWHDBqMEgpBgdUOdqbFYRJagVwjlQ4emXMWlTufu8614Oefc+csD12eWbghtTp06Rd++fXE4HAwZMoTbb7+d22+/3W6xLlKsGHz0EZw7p49//x3mzWPxPW0YsnyXWfAQ4KS7oQ42slo1tBgoCvyYIb0+cMAnEnmZUylp2Uo3hC7fffcd7dq1Y/v27XTq1AmllH0jgMwQgdy59efFi+GNN4h7dxpF736R5JjKJB8/Ta+PNwIYZWDwCllNDbUAPlFKfe/8B3wCtPS5dAaDFzhx4gTPPfccjRpp34nLli1j3LhxgakEMvLqq7zcZhDRZ8+wYEYP+n4ziehzZ8yCh0wIAFOmrVzJ/WelCIoqpTa6qGgjeimpwRDwHDhwgBkzZvC///2PDRs2XFAIwcLHRatzV9txfFirGc+sXkybNdpFhcuAOWFOnjx5OHr0aNgqA6UUR48eJU+ePFkXdiKrqaECmeRl6b5TRO4GxgAOYIpSarCbcg8CC4CblFKeLwkyGNxw+PBh5syZwwsvvEClSpXYtWsXRYoUsVusK0IHxoHX7+zIJ3EN2VS0LAANTu+HY8egYEF7BQwg0pdgHj4cmhEIPSFPnjzZ3miWlSJIFJH2SqlLPBuJSDtgdWYniogDGAfcCewDfhORxUqppAzl8gFdgJXZktxDRPTKPFfphtBDKcXs2bN58cUX+eeff0hISKBChQpBqwRAe9BN3xS5JkYvCbzKAeMWDoJ5fbWX0/vvt1nKwCAqKorSpUvbLUbQkdXUUFfgaRH5TkRGWH/fA23RjXdm1AG2KaV2KKXOAXPQNoeMvAEMAc5kT3TPeLyu68Dh7tINwcvevXtp3rw5jz/+OOXKlWPt2rVX7iQugHDlQffNh2pw9aKP4PrrtbuKhx+GgwftFtUQpGSqCJRSh5RStwL9gV3WX3+l1C1Kqayeuhhgr9PxPivtAiJSCyiplPosswuJyLMikigiidkd8g1sWY16Za+9JK1e2WsZ2LJatq5jCGzOnz9Pw4YNWb58OaNGjWLFihVUqVLFbrG8RsuaMXRPqEjxAtHsP36aYUu3skiK6nCYgwZp19ZxcWC5yTYYsoOnTueWA8u9WbGIRAAjgTYe1D8JmAR6Z3F26lm0Npk1ey71j7dmzwkWrU02S+9CgF27dlGyZEkiIyOZOHEiZcqUoUyZMnaL5XUy+sy6uIS0Gi179dJTQ5MmXXRid+6cdnBnMHiAL71bJQMlnY5LWGnp5AOqAt+JyC7gZmCxiHjVh5HxNRSanD9/nuHDh1O5cuULkcPuuOOOkFQC4MFzXKmSDosZEaGd2JUtC+PGQZrZL2PIGl8qgt+A8iJSWkRyAa3QG9QAUEqdUEoVVkrFKqVigV+B+7y9asjdEjuz9C542bBhA7fccgvdu3cnISGBBx980G6RfE62nuO0ND1N1Lkz3H47bDWdHkPm+EwRKKXOA52BpcBmYJ5SapOIDBARv7mmKO4mSL27dENgM378eGrXrs3u3buZO3cuCxcupHjx4naL5XOy9RyXKAFffqmd2G3aBDfeCIMHu14+ZzDg2xEBSqnPlVIVlFJllVJvWml9lVKLXZRt6Is9BCZ4fWiQvkGoatWqtGrViqSkJB555JHg2B3sBTx9jhetTabe4GWU7vU59Q6U5Iu538K992qFIHIxv+dn1Bu8jEVrkzEYPA5MEyhk1w01mAhlwczJkyfp06cPkZGRDBs2zG5xbCWr5zjTIExVirBo02Hef3cxd21czth6rTkbmcsEaQojMnNDncMgrMGBCV4fnHz77be0b9+enTt38sILLwSukzg/kdVznJlBuWXNGIYt3cp9f6zk+V/nc/cfv9Cj6YusLhF3Id8QvoSFIuizaCOzV+4lVSkcIrSuW9LsIwhgjh8/zv/+9z+mTp1K+fLl+eGHH9zGfDVcJCuD8v7jp3n35of5vWhZ3vryHebPfIUPat3D8AZP+lNMQwAS8sFR+yzayIxf95BqTYGlKsWMX/fQZ9FlvvQMAcKhQ4eYM2cOr7zyCuvXrzdKwEOyMiin//+xdC3uajuO6bXv5ck1n9F581K/yWgITEJeEcxeuTdb6QZ7OHToEGPGjAGgYsWK7Nq1i8GDBxMdbVZ3eUpWBmXn/FO5oul/x3O0fnokxfv10oXXrYO///anyIYAIeQVQaobY7i7dIN/UUoxY8YM4uLi6NGjB39agdsLFy5ss2TBhyufRM6GYFf5rV94mPtuLgupqdpfUVycjpBmCCtC3kYg4DZ4vcFe9uzZQ4cOHfjiiy+45ZZbLtgEDFdOVgZlt/kOB8yfD23bwkMPaUd277yjQ2caQp6QHxG46/eb8YC9pDuJ++GHHxg7diw//vgjlStXtlus8KZGDVi5Um8+++wzPTowu5LDgpAfERgCix07dlCqVCkiIyOZPHkyZcuWJTY21m6xDOlERsIrr2gndhMnQvoI7ezZi3GUDSFHyI8IDIHB+fPnGTJkCHFxcTzX603qDV5Gu6/P8PicHWZ3ayBSoQKMGKGd2CUnQ5kyMHastiUYQg6jCAw+Z926ddStW5eePXtS49ZGfH+uHMnHT6O46E7ZKIMARkT7K+rSBerXh82b7ZbI4GVCXhGUv+6qbKUbvMs777zDTTfdRHJyMgsWLMBxV3dS8uS/pIxxCx7gFC+ubQYffqhtBjVqwMCBxoldCBHyiuD5Rq5XobhLN3iHdB9W1atX5/HHHycpKYkHH3zQuAUPVkTg//5PjwZattSR0MLY3UeoEfKKoP+STdlKN+SM//77jy5dutC9e3cAGjRowLRp07j2Wh0u1LgFD3Kuuw7mzoWpU/Xxhg3QsyecNoo8mAl5RXDsVEq20g1XzldffUXVqlV5++23SUlJwZVnW+MWPESIitL/v/wShgzRNoQffrBXJsMVE/KKwOB7jh07xtNPP01CQgJ58uThhx9+YMyYMS49hWa1+9UQZPToAd98A+fP62hozz8P//5rt1SGbBLy+wiioyI4nXJ53NboKKMDvcVff/3FggUL6NWrF3379iVPnjyZljduwUOMJk1g40bo0wfGjIGSJfV0kSFoCHlFEOHGoOUu3eAZBw8eZPbs2bz00ksXnMQVKlTIbrEMdnHVVTBqFDz2GFSvrtPWrtVKwfiNCnhCvlt88pzrDTDu0g2Zo5Ri+vTpxMXF0atXrwtO4owSMABw0016B3JqKjzyiHZTMW+eWWoa4IS8IjB4j127dnH33XfTpk0b4uLiWLdunXESZ3CNwwEffwylSsGjj2qXFfv32y2VwQ0hPzWUNyqCUy5sBHlzYCMIxxjI58+fp1GjRhw5coRx48bRoUMHIiJMP8KQCdWqwS+/aLtBnz56dLByJVQ0K8QCjZBXBLkiHS4VQa5Ih4vSWZMxQHi6iwQgJJXBtm3bKF26NJGRkbz33nuUKVOGUqVK2S2WIViIjISXX4YWLWDSJO3DCODMGchiUYHBf4R8l+74adf7BdylZ0VmAcJDiZSUFAYNGkSVKlUYN24cAI0aNTJKIAhYtDaZeoOXUbrnZ9QbvOwyP05Z5fuEcuVg6FC9Gzndid3o0caJXYAQ8orA24SDi4Q1a9ZQp04devfuTYsWLXj00UftFsngIekjVndO/bLK9wsiUKsWvPQS1KsHm8wuf7sxiiCbhLqLhLFjx1KnTh0OHjzIxx9/zLx58yhatKjdYuUIW3rANpHViDUgRrTFi8OSJTBzJmzbBjVrwoABZmWRjYS8jcDbdE+oeImNAELDRYJSChGhZs2aPPnkk4wYMYKCBQvaLVa2cGXEB8LKppPViDVgRrQies/BnXdq99bbtxsndjZiFEE2SW88QmXV0L///kuvXr3InTs3I0aMoH79+tSvX99usbKNOyN+nqgItz3gYP3NMqN4gWiSXTTq6SPWrPL9TpEiMGsWpFg2u/XrYcYM6N8f8ua1R6YwxEwNXQEta8awomdjdg6+hxU9Gwdtg/Lll19StWpVxo8fj1LKpZO4YMHdlIc754KhZNNxJiunfgHr9C/did1XX8Hw4Xp38nff2SpSOGEUQRhy9OhRnnrqKZo2bcpVV13FihUrGDlypEsnccFCdhv2ULHpZCQrp34B7/Sve3dYtkx/btQInnsOTpywV6YwwEwNhSFHjx5l4cKFvPbaa/Tu3ZvcIRCU3N2UR4HoKM6eTws5m447PNnsGPBO/xo10nEOXn8dRo6E2Fjo1ctuqUIan44IRORuEdkqIttE5DJ3hCLSTUSSRGSDiHwrImaRuo84cOAAw4cPRylFhQoV2L17NwMGDAgJJQDupzz63VclsHvAXiQgloZ6i7x5Ydgw+O036NZNp61eDYcP2ytXiOKzEYGIOIBxwJ3APuA3EVmslEpyKrYWiFdKnRKRjsBQwCxa9yJKKd5//326devG2bNnadGiBeXLlw+6FUFZkZURPxQb/oxktjQ0aO+/Vi39PzUVWrWC48dh7Fj9OYinMgMNX04N1QG2KaV2AIjIHKAFcEERKKWWO5X/Ffg/H8oTduzcuZNnn32Wb775hgYNGjB58uSQdhIX8FMePiZglob6AocDFi6Etm31stNZs+Ddd6FECbslCwl8OTUUA+x1Ot5npbmjLfCFqwwReVZEEkUk8bAZGnrE+fPnady4MStXruTdd99l+fLlVEj382IISUJ9syNVq8LPP2u7wbffQpUqsGWL3VKFBAGxakhE/g+IB4a5yldKTVJKxSul4osUKeJf4YKMP//8k9TUVCIjI3n//ffZtGmT8RTqAaGw+zhgl4Z6E4dDu6bYuBE6drzoyfR0CIx6bMSXrUMyUNLpuISVdgkicgfQG7hPKXXWh/KENCkpKQwcOJCqVavyzjvvANCwYUNKliyZxZmGUDGyBvzSUG9StiwMHqztBPv2aSd2w4fr2MmGbONLG8FvQHkRKY1WAK2Ax5wLiEhNYCJwt1LqLx/KEtIkJibStm1bNmzYQKtWrWjdunW2zg/H+ArOhJKRNSztJJGRULeu3oMwdy5MnXoxXKbBI3w2IlBKnQc6A0uBzcA8pdQmERkgIvdZxYYBVwPzRWSdiCz2lTyhypgxY6hbty5Hjhzhk08+Yfbs2Vx33XUenx8qveGcENJG1nDg+uu1IXnOHNi9G2rX1nsQgninvL/x6YYypdTnwOcZ0vo6fb7Dl/WHMulO4uLj42nbti1Dhw6lQIECWZ6Xsfd/6tz5kOkNXykB53/HkH1EdEjMJk20DWH3brO8NBsYC2KQ8c8//9CxY0e6WZts6tWrx6RJkzxWAhl7/+Hmi8cVYWFkDRcKF4YPP4QpU/Tx+vU6QtrJk/bKFeAYRRBEfP7551SpUoVJkyYRGRmZbSdxrubC3RFOveGwMrKGC5HWZMc33+jlptWrX/RhZLgM42vIiUA1mh45coSuXbsyc+ZMqlSpwoIFC6hbt262r+NpLz8ce8NhaWQNYLz2Lr78Mtx0E7Rrp6eN2rXTris8GEGHE2ZEYLFobTLdF6y/ZNqk+4L1l4T4s2ud+bFjx1iyZAmvv/46a9asuSIlAO57+QWio0xv2BAweH0BQ4MGeoqoRw947z2YMMGr8oYCZkRg0X/JJlJSL51qSUlV9F+i46leSZSrnPRqkpOTmTlzJt27d6d8+fLs3r3bIztAZriLrtbvviqm4TcEDDldzuv2vRsyRPsoiovTBRMToWRJCPJQrN7AjAgs3BlNj51KuaI4r1faq1FKMXnyZOLi4ujXrx/bt28HuGIl4DySGbZ0Kw/WjjG9f0NAk5PlvFm+dzVrQu7c2old69ZaKcyYEfZLTY0igCwb5yt5MK9EeWzfvp0mTZrw7LPPUqtWLTZs2EC5cuUylS0zXL0UH61OpntCxaCPrmYIXXLiM8nj987hgMWLtYuKJ56Ae+6BPXuuWOZgxygCyLRxLhAd5dGDmdGG4GpdOrhXHufPn6dJkyYkJiYyceJEvv322xwpAbgyZWQw2E1OlvNmq9NWuTL8+COMGQPffx/WTuyMjYDMe/b97qsC4HJuPf3BdBU4XQBXg82MSmXr1q2ULVuWyMhIpk+fTtmyZSnhJde6ZsesIRjJKrZEZmR7c6DDAS++CM2b670Hzk7sosNnCbUZEeD+ISmYN+rCssLM1pm76nkrIOO+Rmflce7cOfr370+1atUYN24cALfffrvXlEBm9xVOewQMwUnLmjGs6Nk421OYVzyaKF0a3nxT70beu1eHxxw6NGyc2JkRAe5X07zevMqF48zWmbvrYSu00sjYq1m1ahVt27bl999/57HHHuPxxx/36v2k4+6+wm2PgCF8yMlo4gK5ckG9evDKK9qJ3XvvwY03+kjiwMAoAnL+8LgbjsYUiGZFz8aXpI0ePZqXX36ZYsWKsWTJEu69996c34AbvPJSGAxBRo43BxYtCh99pP+efx7i46FnTxgwIGT9F0l23RTYTXx8vEpMTPS4fGzPz9zm7Rp8jzdEusxGAFywEcRYjW+LGsUREX7++Wc++OADhgwZQv78+b1Sv8Fg8BFHj0K3bhARAe+/b7c0OUJEViul4l3lmRGBF3DueWc0FO89dISn2w7ntkrFWTJrCrfeeiu33nqrbbIaDIZsUKgQTJ+u9x0ArF2rjwcOhKuvtlc2L2KMxV4i3bgVUyD6ghI4tW0l+6d05Pi6paxJ/i/bTuIMBkOA4LAM0MuX6+Wm1arB11+HRIhTMCMCr7P/+GlST53g728mcWrz90QViaXIA33IVawCEqLziwZDoOJ1R5Ldul10YnfXXaTeeCf/NmyLynO1x65nAhEzIvAyxQtEk3b2JKd3JJL/tscp9tQocherYJZsGgx+xmfR9+rXh/Xr+aBha1ps+Jb/W3sx9lawbtg0I4JskFnvYu/evcyYMYP/JTzBqwvP4ej4HhG5rwLMkk1vEahuwg2BiU9jUefJw+t1H2dW6VvZca3e+1P9wB8cyFeE/Tm7si0YReAhrnYP9/p4I2lpafz122f06NGD1NRU1j/8MG89UM00WF7G3fcPwTcMN/gHX++sL14gmi2UBiAiLZUxS4ZR8PS/vHNvJ1DNgmqpqZka8hBXvYt/Du3h6Yeb07FjR+rUqcPGjRspV67cFe+KNLjH+E0yZBdf76x33sWcFuGg3YN92V74BvosGApNm+q4yUGCUQQekrEXodJSOTT3Nf7dv42pU6fy9ddfU6ZMGZukC32M36TQwJ+rbHwdizqj65kzZSuwd9GX8Pbb8NNP2ond5s1eqcvXmKkhD0nfPZxyZC+R1xZHIhwUvrcbJUuV5plnHrFbvKAnq/n/bDsTMwQcdkzv5Y6MuFBfwbxRvN7cu0GYXO5irt35ohO7SpUAWPLzNvp+s+NC3JMC0VEBFRDKjAgywbn38u/JU/yzYib73+/Mv6s/BaBgmRvp/XA9m6UMfjxZ3eHr3p3B9/hzei/9mTp++mLAqTMpaV6vxy2lSsEbb4AIS7/4jVvvjKfVsllEpmondsdPp9B9/vqA2XdgFIEbnBunM8lb2PLu8xz7aTZXV27AVVUbmeheXsSTBiIrD7CGwMef03veVjo5mdIau2IPv5asyivfT2fRhy9T5ZCOOpiSpgLGxmWmhtyQ/iD9s+pjji1/H0e+wlz3UD+iy2pXHafOhYd7Wn/gaQORY2diBlvx5/SeN5VOTqe0ks7n4fmWvVi89Wfe+PpdPpn+EhPrPsiwBk8GjI3LKAKLjHPU+46dRCSCXMUrc3XNphS8vQ0RufNeKH/sVAovzV1H4u6/GdiyWraubZaTXoqZ/w8P/OkW3ZvPVE73I6TLsrTirfxSqjp9lk2h0KkTIEKECKV7fmZ7uxDyU0PuVvI6pztPA6We+Y/1swZz7JtJAOQpUZlCd3W6RAmko4CZv+7JdJjos92NIYSZ/w8P/Dm9581nKqeji+4JFYly6BbnnzxX06NZV15NeB6ASge38frXEzh+6Kit7ULIjwjcuXlTQM0BX12w4gOc+uMX/v76XVJPHueaug+CUlluClGQac/Ap7sbQwQTNyF88Nf0njefqZyOLtLr7L9k04X2RkVoJVVn7+88ueYz7ti2klcTOtNvcYQt70FYxyNIJ/Xkcf7+egKntv5E1HVlKNT0RXJfrwPHF4iOumTlgSsE2OkmtkHpnp+5VEaZnZMRM7VkcId5NnyPq3gj0VGOHI1mnNuFWvs2M/SLMZT7ex8fVW3MgMbtORGdzyv1OJNZPIKQnxryhLRzpzizay0FGjxJsSdHXlACMQWiWff6XYx+tAYFoqPcnp9ZzyCnuxv7LNrIS3PXmaklw2WYaUf/4IspLef3f02Jytzz9FjevuVR7kv6nsfWf3kh73RKKi/P8/0y07AdEZz/5y9O/r6ca255BBEh7eypS+wArjTx45N/YcX2vy+7Vr2y1zKz/S0u68lJb2LR2mRemrvO5YjCVRhMQ3hRb/Ayj0OkGgILV+0CQMXDu9hxbQwpjihu3L+V/dcU4fDV117Ij8nBqM+2CGUicjcwBnAAU5RSgzPk5wY+AGoDR4FHlVK7fCmTUmn8t/YLjn0/DVQaeSvXJ6pg8cuMwa4a6l1HXRuHft7+N4vWJrv8cXIyVzls6Va3Ng5vLjvzxfSCmbLwPcbthnew41nNGNUwna1FYgHtxG70p8O59tQ/DGzcjvnV7gARko+fpuvcdcxP3OO283kl+GxqSEQcwDigKRAHtBaRuAzF2gLHlFLlgFHAEF/JA5BydB+HZvXi76/fJXfxShRvO56ogsVdlnX1ILh7wdINxu64Uid0mb3Q3lpa6YvpBTNl4R987VQtHLDzWU1vF1wtR0mLcPDMQ/3YUiSWYV+M4YN5fSlx/OCF/BXb/6bPoo1ek8WXNoI6wDal1A6l1DlgDtAiQ5kWwHTr8wKgifgojJdKS+XQvL6kHN5FoWZdue6RAUTmL+qybMwVvGC+6IW5q0/Aa0srfbHt33gK9Q9m2W3OCYRn1d17vvPaGFo99hZ97upErf1beH9Bf0RddJMxe+Ver8ngS0UQAzhLus9Kc1lGKXUeOAEUynghEXlWRBJFJPHw4cNXJIxEOCjc/GWKtXuXq6vd4TZsZGYvUveEim73JfiiF+bqRRfg8Ztv8NrQ1RfTC2bKwj8Ytxs5JxCeVVfveTpKIphRsxl3tR1H92ZdUXKxyU71on03KPYRKKUmAZNAG4uv9Dp5SlTJNN8hkumL1LJmDIm7/2bmr3sumbv3VS/MH+vrfbGr1+wU9h/G7UbOCIRnNf336zZvHWluWrf911zH/muuuyTN4cXJE1+OCJKBkk7HJaw0l2VEJBLIjzYa+53oKAcjHrkxy5dqYMtqjHq0ht96Yb4OcuOL6QUzZWEIFgLlWW1ZM4aRj9QgIhtte+u6JbMu5CG+HBH8BpQXkdLoBr8V8FiGMouBp4BfgIeAZcrL61l3Db7H5RJSAfJHR3HidEq2e9qh1AvzxajD7BQ2BAuB9Kym19lv8aYLm1jzRkWQO8pxiQcEhwit65bM0sdZdvDpPgIRaQaMRi8ffU8p9aaIDAASlVKLRSQP8CFQE/gbaKWU2pHZNbO7j8BgMBgMNu4jUEp9DnyeIa2v0+czwMO+lMFgMBgMmWNcTBgMBkOYYxSBwWAwhDlGERgMBkOYYxSBwWAwhDlB531URA4Du6/w9MLAES+KEwyYew4PzD2HBzm551JKqSKuMoJOEeQEEUl0t3wqVDH3HB6Yew4PfHXPZmrIYDAYwhyjCAwGgyHMCTdFMMluAWzA3HN4YO45PPDJPYeVjcBgMBgMlxNuIwKDwWAwZMAoAoPBYAhzQlIRiMjdIrJVRLaJSE8X+blFZK6Vv1JEYm0Q06t4cM/dRCRJRDaIyLciUsoOOb1JVvfsVO5BEVEiEvRLDT25ZxF5xPqtN4nILH/L6G08eLZvEJHlIrLWer6b2SGntxCR90TkLxH53U2+iMhY6/vYICK1clypUiqk/tAur7cDZYBcwHogLkOZTsAE63MrYK7dcvvhnhsBea3PHcPhnq1y+YAfgF+BeLvl9sPvXB5YCxS0jq+zW24/3PMkoKP1OQ7YZbfcObznBkAt4Hc3+c2AL9BhVW4GVua0zlAcEdQBtimldiilzgFzgBYZyrQAplufFwBNxF0Q4+Agy3tWSi1XSp2yDn9FR4wLZjz5nQHeAIYAZ/wpnI/w5J7bA+OUUscAlFJ/+VlGb+PJPSvgGutzfmC/H+XzOkqpH9DxWdzRAvhAaX4FCohIsZzUGYqKIAbY63S8z0pzWUYpdR44ARTyi3S+wZN7dqYtukcRzGR5z9aQuaRS6vIQdcGJJ79zBaCCiKwQkV9F5G6/SecbPLnnfsD/icg+dPyTF/wjmm1k933PkqAIXm/wHiLyf0A8cLvdsvgSEYkARgJtbBbF30Sip4caokd9P4hINaXUcTuF8jGtgWlKqREicgvwoYhUVUql2S1YsBCKI4JkwDmqcwkrzWUZEYlEDyeP+kU63+DJPSMidwC9gfuUUmf9JJuvyOqe8wFVge9EZBd6LnVxkBuMPfmd9wGLlVIpSqmdwB9oxRCseHLPbYF5AEqpX4A8aOdsoYpH73t2CEVF8BtQXkRKi0gutDF4cYYyi4GnrM8PAcuUZYUJUrK8ZxGpCUxEK4FgnzeGLO5ZKXVCKVVYKRWrlIpF20XuU0oFc8BrT57tRejRACJSGD1VlGkc8ADHk3veAzQBEJHKaEVw2K9S+pfFwJPW6qGbgRNKqQM5uWDITQ0ppc6LSGdgKXrFwXtKqU0iMgBIVEotBqaih4/b0EaZVvZJnHM8vOdhwNXAfMsuvkcpdZ9tQucQD+85pPDwnpcCd4lIEpAKdFdKBe1o18N7fhmYLCIvoQ3HbYK5Yycis9HKvLBl93gdiAJQSk1A20GaAduAU8DTOa4ziL8vg8FgMHiBUJwaMhgMBkM2MIrAYDAYwhyjCAwGgyHMMYrAYDAYwhyjCAwGgyHMMYrAYPATIjJNRB6yPte3vIOuE5Fou2UzhDdGERgM9vA48JZSqoZS6rTdwhjCG7OPwGBwg4hchXZdUAK9mekN9CaekejNeUfQm5cOiEg5YAJQBL2R62H0jt63gTvRTsLOAe8BBYChaGeHPyulHvffXRkMlxNyO4sNBi9yN7BfKXUPgIjkR3ttbaGUOiwijwJvAs8AM4HBSqmFIpIHPdq+H6iI9pFfFEhC74ydIiK3AZ8qpRb4/a4MhgwYRWAwuGcjMEJEhgCfAsfQjuy+ttx0OIADIpIPiFFKLQRQSp0BEJEGwGylVCqwX0SW2XAPBkOWGEVgMLhBKfWHFdOgGTAQWAZsUkrd4lzOUgQGQ9BijMUGgxtEpDhwSik1A+20ry5QxPJ5j4hEiUgVpdS/wD4RaWml5xaRvOgQmY+KiMOKINXIlhsxGLLAjAgMBvdUA4aJSBqQgo71fB4Ya9kLIoHRwCbgCWCi5RUzBW0sXgg0RtsG9gC/+PsGDAZPMKuGDAaDIcwxU0MGg8EQ5hhFYDAYDGGOUQQGg8EQ5hhFYDAYDGGOUQQGg8EQ5hhFYDAYDGGOUQQGg8EQ5vw/mrRPzZvna6kAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEWCAYAAABrDZDcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAAz70lEQVR4nO2de5gdVZXof6s7J9BBpImJD5p0EhGDxAiRHokTvaKjBHCAiDKAMMj4YByvM4qYMYx8vGSGjBmvjxlGBx/jIMpb20hwghrUkTFCYifEgNEYHkkTJKCJQprQ6az7R9VJ6lRX1ak6XdX1OOv3ff31qapdVat27dpr77XXXltUFcMwDKN96chbAMMwDCNfTBEYhmG0OaYIDMMw2hxTBIZhGG2OKQLDMIw2xxSBYRhGm2OKoI0RERWRl+Uth9GIiFwtIk+KyON5yxIHETlXRO7ybKdWrkTkhyLy3hbPneHKMiENWaqMKYIWEJF3ishqEXlaRLaJyHdF5HUpXPerInJ1SjKmdq0i4T7XHhF5Sd6yBCEiJ4jI1jGc3wtcDBytqi8Ouf5et+z9UUQ2ishfjUXmsaKqX1fVE/O4t4i8XERudRXnThG5X0Q+IiKdechTVkwRJEREPgJ8Bvgn4EVAL/DvwOk5itUWiMhBwNuBncB5OYuTFb3AU6r6RESax1T1ecDzgY8BXxSRo/2JxqMlnGdrW0SOAH4GbAHmqOohwJlAH3BwXnKVElW1v5h/wCHA08CZEWkOwFEUj7l/nwEOcI+dAGzFafE9AWwD/so9diEwDDzn3uM77v7DgNuB7cBDwN+5+ye71zrV3X4esAk4P+xaAbIq8DLPs13v3ucR4FKgwz12AfAT4F+A37tynBxyzY8Bt/n2fRb4nOdam4E/utc5N0H+n4/z0X8I+IXv2BXArcAN7rXXAy8HLnHzegtwoif9YcAy4Hduvr3Pc+yrwNWe7ROArZ7th4GPAvfjKKWbgQOBg4AhYK+b708Dh4WUo1F5DbzZd/5XA85tkMXdtx14h5u39wCfBp4CrsYpj/8CPAr8FvgC0OWeNwW4A9jh5sP/eN75NOCb7rWfAv7N8/7897gA+ImvXP2d+56fBJbWr+sefzfwoFuWVgDTPcfeAvzSzdd/A34EvDekPNwALI8oLzNcWd7lPv+TwMc9x18D/NR9/m3u/Sb6nuP9wK/dNNcC4h7rBD7lXvMh4INu+gmed/xl97qDbj515l2HheZV3gKU6Q84CdhTf9khaa4CVgEvBKYC/wt8wj12gnv+VUANOAXYBRzqHv8qjRVQB7AGuAyYCLzU/bgWuMdPBB537/VFPBWw/1ohsnoVwfXAt3FaUjOAXwHvcY9dgKNY3ud+AH+Do+Qk4JrT3Wc62N3udD+GeTgV5R+AWe6xlwCzE+T/D4BP4vTE9gDHeY5dATwLLAAmuM/zEPBxN6/fBzzkSf9jnJ7cgcCxOBXem0LewwmMVgT34iiTyTiV2vuD0oY8R1ReR57vPe6Wj7e572aW+572AH/r5kEXToW9zJXzYOA7wDXu+dfgKIaa+/d6QNx3ts499yA3j17nKQv+e1zAaEVwt3vPXvf53useOx1H8b7CPf9S4H/dY1NwlPg7XHkucu8Vpggex21IhRyf4cryRVfOY4DdwCvc48fhlMsJbtoHgQ/7nuMOoNt9ju3ASe6x9wMPAIcDhwLfp1ERfAv4Dzf/XuiWl7/Ouw4Lzau8BSjTH3Au8HiTNL8BTvFsLwAedn+fgNPim+A5/gQwz/39VRoroOOBR33XvwT4T8/2v+K0fgeBF3j2N1wrRFYFXuZ++M/h2KXrx/4a+KH7+wJgk+fYJPfcF4dc9yfA+e7vtwC/cX8fhNOyejtuqzRB3vfitJSPdbdXAJ/1HL8C+J5n+1ScVnWnu32wK3M3Tmt3BFdZucevwW2BB7yHExitCM7zbH8S+EJQ2oDnaJbXzc4/wc2HHTit+LXA2Z739KgnrQDPAEd49r0WVyHiNEi+jdsY8KXZTkCDx38Pzz6/IjjJs/0B4Afu7+/iKj13uwOn4TAdp8e3yif/VsIVwbD3PgHHZ7iyHO7Zd289vwLSfxj4lu85XufZvgVY7P5eiadix+nNKY5SeRGOwunyHD8HuDtJmR/PPxsjSMZTwJQmdtHDcLr7dR5x9+27hqru8WzvwjHrBDEdOExEdtT/gH/AKWh1rgNeiVOJPRXvMUYxBacF5pe7x7O9z4NFVXe5P8Pk/gZOwQd4p7uNqj4DnIXTmtomIstF5KiYMv4l8KCqrnW3vw68U0RqnjS/9fweAp5U1RHPdl3mw4DfqeofPen9z9sMr0dP1Dv0Eyevm/GYqnar6mRVPVZVb/Ic2+L5PRVHaa/xlJ//dveDY7LZBNwlIptFZLG7fxrwiK+cetkSsj8sjfcbmA581iPP73Aq/B43zb7z1KlBo+71FE6vshmB78odaL5DRB4XkT/gjPtNiXOuX1bf7+k473ib5zn/A6dnUEhMESTjpziafmFEmsdwCkKdXndfHNS3vQWn9dbt+TtYVU8BcD0jrsMxNXzA57Lnv1YUT+K0rvxyDya4hpdbgRNE5HAc08U39gmlukJV34LzAf8Sp9seh/OBl7of7ePA/8P5aE9pQb7HgMki4h1Q9D7vMzgVaJ1R3jsRNMv3tPM66v5P4ijA2Z7yc4g6A82o6h9V9WJVfSlwGvAREfkznHLXG9HgiVO2pnl+e7+BLTgtaW+Z7lLV/8UxIe47T0TEdx0/38fpXbbK53HK4JGq+nycRpbEPHcbjlmojlfOLTj1xBTPMz5fVWePQdZMMUWQAFXdiWOvv1ZEForIJBGpicjJIvJJN9mNwKUiMlVEprjpb4h5i9/ijAPUuRf4o4h8TES6RKRTRF4pIn/iHv8HnI/y3Titu+s9bnP+a0U91whOt/cfReRgEZkOfCSB3P7rbQd+CPwnjiJ7EEBEXiQip7veP7txTDd7m11PRF4LHIEzuHes+/dKHAVzfgvybcEZu7lGRA4UkVcB72H/864FThGRySLyYhyTQVx+C7xARA4JuXeqeR2Fqu7FUbSfFpEXAohIj4gscH//uYi8zK1wd+KYy/bilLttwBIROcjNo/kJb79IRA4VkWk4g/s3u/u/AFwiIrNdGQ4RkTPdY8uB2SJyhquE/o5oJXw58KcistR9T7jPc4OIdMeQ8WCcMaun3Z7p3yR4vluAD7n52Y3jJAGAqm4D7gI+JSLPF5EOETlCRN6Q4PrjiimChKjqp3A+3Etx7KhbcDwG+t0kVwOrcTxK1gM/d/fF4cvA0W53st+tNP4cp+J7CKeF9yXgEBE5zpXjfDfdP+MohcVB14px77/FaQlvxrHxfwP4Sky5g/gGjt30G559Ha7Mj+GYBN6A+/GJyOtF5OmQa70L+LaqrlfVx+t/ON5Ify4ik1uQ7xwcG/JjOAN7l6vq991jX8MZLH0Y54O+OeD8QFT1lziNgc1u3h8WkCztvI7iYzjmn1Wu+eP7OAPLAEe620/j9Hb/XVXvdsvTqTjjR4/i2OnPSnjfb+M4OqzFqeC/DKCq38Ipqze58vwCONk99iSO++cSHLPPkTgeSoGo6m9wxjNmABtEZCeOh91qnEHnZnwUx3T5RxyFGfs9u+nvwvnOB4A7cQa266bI83EcPB7A8Y66jXhmrFyou0IZhmEYLSIiJ+M4DExvmriAWI/AMAwjIa6p9hQRmSAiPThmqm/lLVerWI/AMAwjISIyCWey21E4A/LLgQ+p6h9yFaxFTBEYhmG0OWYaMgzDaHNKF551ypQpOmPGjLzFMAzDKBVr1qx5UlWnBh0rnSKYMWMGq1evzlsMwzCMUiEij4QdM9OQYRhGm2OKwDAMo80xRWAYhtHmmCIwDMNoczJTBCLyFRF5QkR+EXJcRORzIrLJXWf01VnJYhiGYYSTpdfQV3GWfrs+5PjJOEGljsRZgOXz7n/DMNqE/oFBlq7YyGM7hjisu4tFC2axcG6SpRmMNMisR6CqP8aJMBnG6cD16rAK6BaRwkbnMwwjXfoHBrnkm+sZ3DGEAoM7hrjkm+vpH0hraQYjLnmOEfTQuKrPVkJWaRKRC0VktYis3r59+7gIZxhp0T8wyPwlK5m5eDnzl6y0is5l6YqNDA2PNOwbGh5h6YqNOUnUvpRisFhVr1PVPlXtmzo1cGKcYRQSa/WG89iOoUT7jezIUxEM0ri82+Gkt1yfYRQCa/WGc1h3V6L9RnbkqQiWAee73kPzgJ3uEm+GURms1RvOogWz6Kp1NuzrqnWyaMGskDOMrMjMa0hEbgROAKaIyFachRtqAKr6BZyl3U7BWUZvF/BXWcliGHlxWHcXgwGVvrV62ecdZF5D+ZOZIlDVc5ocV+D/ZnV/wygCixbM4pJvrm8wD1mrdz8L5/ZYxV8AShd91DDKhLV6jTJgisAwMibPVq9N2DLiYIrAMCpK3XW1bpaqu64CpgyMBkoxj8AwjOSY66oRF1MEhlFRwlxUB3cM2QxnowFTBIZRUaJcVG2Gs+HFFIFhjAN5xBsKmrDlxcxERh0bLDaMjMlr0Nbruho0qQ1shrPhYD0Cw8iYPAdtF87t4Z7Fb6Kn4nF9LMLr2DBFYBgZU4R4Q1WO62MRXseOKQLDyJgiRNlcOLeHa86YQ093FwL0dHdxzRlzKjGfwNxkx46NERhGxoxnvKGomcRVjetThB5X2TFFYBgZM17xhtp1JrFFeB07pggMYxwYj9Z4mInkimUb9h2vYsyhsfS4LBaTgykCw6gIYaaQHUPDLLp1HcN7FaheT6HVHle79qCCMEVgGBUhzEQC7FMCdeqDqVWp8FrpcUUNMlclX+JiXkOGURGSDj63+2CqDTLvxxSBYVSEhXN7OHRSLXb6DpHMfe2LPNGrCG69RcEUgWFUiMtPnT1q4litU6h1yKi0I6qZTrwq+kSvKk+yS4opAmMURW7FGdEETRxb+o5jWHrmMXTKaGWQ5cSrok/0qvIku6TYYLHRgHlSlJ+wgdOLbl4bmD4rm3gZbPBVnWSXFOsRGA0UvRVntM5428TNBl8eTBEYDZShFWe0xnjbxM0GXx7MNGQ0YNP1q8t4hbrI635G64iqNk9VIPr6+nT16tV5i1FZ/GME4LTi2nUQzTCqgoisUdW+oGPWIzAasFacYbQfpgiMUZgnRTmwgGlGWpgiMIwSYm6+RpqY15BhlBBz8zXSxBSBYZQQc/M10sQUgWGUEJusZaRJpopARE4SkY0isklEFgcc7xWRu0VkQETuF5FTspTHMKqCTdYy0iSzwWIR6QSuBd4CbAXuE5FlqvqAJ9mlwC2q+nkRORq4E5iRlUyGURXMzddIkyy9hl4DbFLVzQAichNwOuBVBAo83/19CPBYhvIYRqUwN18jLbI0DfUAWzzbW919Xq4AzhORrTi9gb8NupCIXCgiq0Vk9fbt27OQ1TAMo23Je7D4HOCrqno4cArwNREZJZOqXqeqfaraN3Xq1HEX0jAMo8pkaRoaBKZ5tg9393l5D3ASgKr+VEQOBKYAT2Qol+HDZqgaRnuTZY/gPuBIEZkpIhOBs4FlvjSPAn8GICKvAA4EzPYzjhR9OUHDMLInM0WgqnuADwIrgAdxvIM2iMhVInKam+xi4H0isg64EbhAyxYOteTYDFXDMDKNNaSqd+IMAnv3Xeb5/QAwP0sZ2pEkph6boWoYhgWdqxhJg5ElXYjGxhOMKtLu5TpvryEjZZKaepLMULXxBKOKWLk2RVA5kpp6Fs7t4Zoz5tDT3YUAPd1doauR2XiCUUWsXJtpqHK0suZw3BmqNp5gVBEr19YjqBxZBiOziJcGOKaU+UtWMnPxcuYvWVl6E4qVa1MElSOJqScpFvHSqKI93cq1mYYqSVbByCzipRFlTy9rObBybYrASIhFvGxvqmpPb/dybaYhwzBiY/b0amKKwDCM2Jg9vZqYacgwjNiYPb2amCIwcqHdp/SXmXa3p1cRUwTGuJM0HlJZMWVnlAVTBMa4U0UXRD/touzyxBRtethgsTHuVNUF0YvFr8mWKk5syxNTBMa40w4uiO2g7PLEFG26mCIwxp12cEFsB2WXJ6Zo08UUgTHuZBkPqSi0g7LLE1O06WKDxUYuVN0F0fzts2XRglkNg/FginYsmCIwjIyourLLE1O06WKKwDCMUmKKNj1sjMAwDKPNMUVgGIbR5pgiMAzDaHNMERiGYbQ5pggMwzDaHFMEhmEYbY4pAsMwjDbHFIFhGEabY4rAMAyjzclUEYjISSKyUUQ2icjikDR/ISIPiMgGEflGlvIYhmEYo8ksxISIdALXAm8BtgL3icgyVX3Ak+ZI4BJgvqr+XkRemJU8hmEYRjBZ9gheA2xS1c2q+hxwE3C6L837gGtV9fcAqvpEhvIYhmEYAWSpCHqALZ7tre4+Ly8HXi4i94jIKhE5KUN5DMMwjADyjj46ATgSOAE4HPixiMxR1R3eRCJyIXAhQG9v7ziLaBiGMZr+gcHKhMHOskcwCEzzbB/u7vOyFVimqsOq+hDwKxzF0ICqXqeqfaraN3Xq1MwENgzDiEP/wCCXfHM9gzuGUGBwxxCXfHM9/QP+Kq4cZKkI7gOOFJGZIjIROBtY5kvTj9MbQESm4JiKNmcok2EYxphZumJjw+poAEPDIyxdsTEnicZGZopAVfcAHwRWAA8Ct6jqBhG5SkROc5OtAJ4SkQeAu4FFqvpUVjIZhmGkwWM7hhLtLzqxxghEZBJwMdCrqu9z3T5nqeodUeep6p3Anb59l3l+K/AR988wDKMUHNbdxWBApX9Yd1cO0oyduD2C/wR2A691tweBqzORyDAMo+AsWjCLrlpnw76uWieLFszKSaKxEddr6AhVPUtEzgFQ1V0iIhnKZRilpkoeJcZo6u+yKu84riJ4TkS6AAUQkSNwegiGYfioe5TUBxPrHiVAaSsKYz9+Jf/ps44t/XuNaxq6HPhvYJqIfB34AfD3mUllGCWmah4lxn6q5jZaJ1aPQFW/JyI/B+YBAnxIVZ/MVDIjc8x8kQ1V8ygx9hOl5Mv87cT1Gnq1+3Ob+79XRA4BHnHdRI2SYeaL7KiaR4mxn6oq+bimoX8HVgHXAV8EfgrcCmwUkRMzks3IEDNfZEerHiX9A4PMX7KSmYuXM3/JytKbG6pImDIvu5KPqwgeA+a6YR6OA+bizAB+C/DJrIQzmtNK5dE/MBjYYoXyt2yKwMK5PVxzxhx6ursQoKe7i2vOmBPZ06qq7blqVM1ttE5cr6GXq+qG+oaqPiAiR6nqZvMizY9WzDv1c8Ioe8umKCyc25PIxFZV23PVqJrbaJ24imCDiHweZ00BgLOAB0TkAGA4E8mMprRSeQSdU6cKLZuyUlXbcxVJquTLQFxFcAHwAeDD7vY9wEdxlMAbU5fKiEUrlUfUMa/5wjyKxhcbYDbyJNYYgaoOqeqnVPVt7t+/qOouVd2rqk9nLaQRTCsDV92TaoH7e7q7GpSA2avHl6rano1yEEsRiMh8EfmeiPxKRDbX/7IWzogmaeXRPzDI08+O9vatdUrDOeZRNP60MsBsGGkR1zT0ZeAiYA0QbGA2xp2kA1dLV2xkeK+O2n/QxAkN55i9Oh/StD2bac9IQlxFsFNVv5upJEZLJKk8wirynUON4/1mry43NlnQSErceQR3i8hSEXmtiLy6/pepZEbqxB1TMHt1uTHTnpGUuD2C493/fZ59CrwpXXGMLFm0YFZDSxGCK/iq+kq3C2baM5ISN+icuYhWgCQVfBV9pdsFM+0ZSYnbI0BE3grMBg6s71PVq7IQysgOq+CrT9yen2HUiRt99AvAJJzJY18C3gHcm6FchmG0iJn2jKSIs358k0Qi96vqqzz/nwd8V1Vfn72IjfT19enq1avH+7aGYRilRkTWqGpf0LG4XkN1g+MuETkMJ7TES9IQzjAMw8iXuGMEd4hIN7AU+DmOx9CXshLKMIxyYBPXqkFcr6FPuD9vF5E7gANVdWd2YhmGUXRs4lp1SOI19KfAjPo5IoKqXp+RXIZhFBxbQ6E6xPUa+hpwBLCW/bGGFDBFYBhtik1cqw5xewR9wNEax8XIMEIwe3K1iDtxzd578YnrNfQL4MVZCmJUG1vjoDWKvKB9nJhU9t7LQeQ8AhH5Do4J6GDgWJxJZLvrx1X1tIzlG4XNIygn85esDGw99nR3cc/i8oasyrK16x+MBWftiIMmTmDn0HAhWtfNnj/qvS9aMMt6CuNI1DyCZqahZcCLgP/x7X89sC0F2Yw2oYr25Ky9ZoIGY4dHlB1u2PAieOk0C1kS9n7rspvHUTFoZho6Hfi2qv7I+wd8G1iYuXRGZWhlWc2ik3W45zhKsujhpcPeb6eIhcouEM0UwYtUdb1/p7tvRrOLi8hJIrJRRDaJyOKIdG8XERWRwG6LUX6quMZB1r2cuEqyyL2qsPc+EmKSLvKzVJlmiqA74lhkKRWRTuBa4GTgaOAcETk6IN3BwIeAnzWRxSgxVVyTN+teTlAlmuX9siDsvfdUsIdYZpqNEawWkfep6he9O0XkvTjrF0fxGmCTqm52z7kJx9T0gC/dJ4B/BhbFltooJVULgZ11uGd/FNHuSTWefnZPw7rTZehVhb13C5VdHJopgg8D3xKRc9lf8fcBE4G3NTm3B9ji2d7K/pXOAHCXu5ymqstFJFQRiMiFwIUAvb29TW5rGNkQ5CFzzRlzUvF8CfO+8VeiVfHJt1DZxSJuGOo3Aq90Nzeo6soY57wDOElV3+tu/yVwvKp+0N3uAFYCF6jqwyLyQ+CjqhrpG2ruo0YeBLlydtU6UzFvZXltw6gz5jDUqnq3qv6r+9dUCbgMAtM824e7++ocjKNcfigiDwPzgGU2YGwUkSw9hGyxeSNv4s4sboX7gCNFZKaITATOxpmXAICq7lTVKao6Q1VnAKuA05r1CAwjD7L0EKriHAujXGSmCFR1D/BBYAXwIHCLqm4QkatEZNxnJBvGWMjSQ6iKcyyMchE7DHUrqOqdwJ2+fZeFpD0hS1mM9KnKwGUcsvQQssXmk9FO5W68yFQRGNWl3RYlydLLxTxo4tNu5W68iOU1VCTMa6gYVDWInFFsrNy1zliCzhlGIDbAacD4m2ms3GWDKYI2I60PN+6iJEZ1ycNMY+UuG7J0HzUKRpqLhFQxiJyRjDzmP1i5ywbrEbQRaS42bgOc+VIEz5k8zDRW7rLBBovbiJmLlxP0tgV4aMlbx1sco0WCQlIAdHfVuOK02alXimFKJ2zgFvavQGYVdHGwwWIDyMa+WoSWadXx5/Ezu/eMUgIAO4aGU7fRR40DBM1/qGNuneXCxgjaiLTtq7YwefYE5XF9qcog0rbRNzMnRq0tYPGSyoMpgjYi7cVhLFha9gTlcTPStNE3GwdYOLeHexa/CRkHWYzsMNNQm9Hq4jBBJiDz6c6eVvIyTVfKuOZEc+ssN9YjMJoSZgLqnlQLTG8ff3qE5eWhk2ocGpD/abtSRpkT+wcGmb9kJTMXL+eZ3XuodUpgOqP4mCIwmhJmAlLFfLozJqwivvzU2QxcdiKfOevYTNeBDjMnAg2Ngx1Dw6COgqrKmtTthJmGjKaEmSd2Dg3z6bOONa+hDGnmNz8e60AH3WP+kpWjGgfDe5VJEycwcNmJmcpTFKrkMWeKwGhKlP23agvSF5Ei5nG7jw9VLQqqmYaMpti0fsNPuy+mUzWPOVMERlPSdjs1ovEOws5fsrKQ8zLavXFQtR6RmYaMWBTRPFFFymJyaLeYP/7xgEO6aoET+8raIzJFYBgFIs3AgFnTLo2DIOVc6xRqHcLw3v3Ru8rcIzLTkGEUiKqZHKpAkHIeHlGed+CEyphLrUdg5EqVXPDSoEwzdNvl3YUp4R27hivjKms9AiM3LGjdaMoyCNtO764dPKRMERi5UTUXvDSImsk796q7mLF4OTMWL+fYK+/KtdJtp3dXFuU8Fsw0ZORGO9nDvWaU7kk1VJ2Z2UEmFf8gbP/AIItuW8fwyP6ByR1Dwyy6dd2+9GnKF8fM007vrh08pEwRGLlRJnt4EvyV6huPmsrtawb3taB/v2u/22Ec99ClKzY2KIE6w3s1FW+iVlxWq+Y+WSdMIVbdQ8pMQ0ZuVLHLHWQ7//qqRyPXFGhmUolqZafRAr/yOxsSmXn6BwZ55rk9gcd2PbentOME7TTu4ccUgZEbZZqxHHe2b5DtPM6q4FEVelQre6wt8P6BwYYeShyZwnoo4PR2ylp5ttO4hx8zDRm5UoYudxzTSd2kELaYezO6J9WYv2RloA160YJZo8YIAGodMubeU1QlF6ZkmvVCijoBrhntNO7hx3oEhtGEZi3F+mBuq0qg1ik8/eyeBpPERTev5dL+/cpm6TuOaViIprurxtIzjxlzZRtVyYUpmTi9kDJWnu3gJhqG9QgMownNWopXfmdDqKkkCBE45MDaPq+hZ3bvGTXwqsDXVz1K3/TJmQ5Whg3Yd3fVQu+3aMGshh5S2HXLRtBzlX3MKi6mCIzCUpSZq828m8Js7KEorL18/4zUmYuXhyXL3MQSVvldcdrs0HO87pSDO4YQGsdBylp5toObaBiZKgIROQn4LNAJfElVl/iOfwR4L7AH2A68W1UfyVImoxwUKQpn2i3FuAu/Q3hvJC0l2Wrl5+2hBLnLLl2xkYtuXlu6yrQMY1ZZkNkYgYh0AtcCJwNHA+eIyNG+ZANAn6q+CrgN+GRW8hjlokgeHM28m7q7Ri8iDzCp1hHLPXbRglk0Lvu+nyATS1Zujgo8vvNZPnzz2kTrICyc28M9i9/EQ0veyqIFs7h9zWClXTDLsF5EUrLsEbwG2KSqmwFE5CbgdOCBegJVvduTfhVwXobyGCWiaB4cUS3FK06bzaJb1zWEJK51CP90xquA5q3thXN7WP3I7/j6qkdjmVjSDFXt73mNqCNBqz2wMoXRboUi9VTTJEtF0ANs8WxvBY6PSP8e4LtBB0TkQuBCgN7e3rTkMwpMmWYdx1lgvhlXL5xD3/TJsUw0aSrJoIq7TisVeNEUeNpUVdEVYrBYRM4D+oA3BB1X1euA6wD6+vriu2cYichycDbptYvowRH1DGnYluNeI00l2ayCTlqBl0mBt0JVFV2W8wgGgWme7cPdfQ2IyJuBjwOnqeruDOUxIshyen0r1y7arOMihR9IMzRHswo6aQVexbAhXqo61yBLRXAfcKSIzBSRicDZwDJvAhGZC/wHjhJ4IkNZjCZkOTjb6rW9g5D3LH5Trl3vMg1eJyGo4q7TSgVeNAUexFgGe8Pyq8wxliBD05Cq7hGRDwIrcNxHv6KqG0TkKmC1qi4DlgLPA24VEYBHVfW0rGQywsmyy1uF7nTRniEtN0f/nIBOEUZU6enuYsYLurj4lnV8+Oa1dIpwzvHTuHrhnHGTLQvGOthbT3PFsg0NkwDrMZbiXqdoZDpGoKp3Anf69l3m+f3mLO9vxCdL224V7MZhz9AhwszFy0vnL+8lqOK+tH89N6x6dN/2iOq+7TjKIA/ijEOlMdi7cG4PS1dsHDUbvMyDxhZryACyte1WwW4cZhIYUc19zCALbvzZlkT78ybuGE5aPbui9RDHSiG8hoz8yXJ6fZJrFyWshB//M3S4JhQvSVuE/QODDSaGQyfVuPzU2aNWJ8sjP/zP1my/lzxkjtvST6t3WoVerhdTBMY+4tp2W/nQ41y76JN1vM8QFh8obouwf2Bw1CS03+8aZtFt+5efbDU/0qiIOwMUXX1/s+fK4x3GDdGRlltyEd2bx4IpAiMRrXzocSumsFbdR25Zy4dvXgs44RyuOG127ophrC3CpSs2NiiBOsMj+5efDMuPK5ZtCM3PtCric46f1jBG4N3f7LmynnAVFNvIH/iujv99pNXzrVqAOlMERiKSfuhJKqaw1rS3vkx70fZWGWuLMKrnMLhjiGOvvCtwTWBw8qB+zJ+fcd5PHMVcHxC+8WdbGFGN7TWUte08qDz5Q3PUEYLXVEjT46qsFb8fUwRGIsI+6MEdQ4ErbCVRHN2TarFCOqe1aPtYGGuLMCriKBCqBILw5mezijiJYr564ZzEHkJZ286TLAWqFMOkWAZMERiJCPvQhf12Wm/lEreF2D8wyNPPBi+IHuf8PAhrEcZpcS9aMGufuSsN6vnRrCLO2nSTte08yXvvKenAbR6Y+6iRiCA3yiD7bL1yiTslP8xmHkZRvTPiujEunNvTsPTkWKnnRzNX3axNN0lnFied5Rv23v1D2HGUTxXDSbeKKQIjEUEfelj1/diOodhzCJJURGks2p4VSUJRXH7q7EClmhRvfjariMcjVk7c0CCtxG8KK0/nzutNFNaiSLGjioCZhozE+E0i85esDDVHxLWlR62dK7J/OciieA2FkaTFHZQ3bzxqKjffuyVR78hf6UUNYhbJ7bEVx4P6Od5QGK1466S9pkPZvYdMERhjplnlEse7Imrt3DJ9VEkHS4Pypm/65FGxbMLo8SjbOs3CZUMx3B6TKM2gBXTqZawV2dMykRV97ktcTBEYYyaNyqVIFdRYSKPFXVcOYT2tOkEmsjgVU1HcHpMozbQHudPybqrKQjWmCCpEnl3U8VyYpcikqdCiWqdhJrJmFVORzBhxlWb/wGDsmcNp37sZVYk5ZIqgIlSli1oF0lJoYa3Wnu4u7ln8psBzoiqmopWROEqzLnMYrQ5yp6WwqxJzyBRBRahKF7Xd8bbYuyfVqHVIw8CxAG88amro+VEVUxHLSDOlGbWmclgLvp6H3vUV6k4HO3YNN1T6Y33uIg2+jwVTBBWhCF1UbyV2iO/De+NRU7n7l9sLYZIoKv4We9AsawVuXzNI3/TJgfkXVTFdFDKBrUhmDL/pKmqMJMhFNGhQGRpnaqfZE/L3LOrl/qKb17J0xcbSlHObR1AR8l5L1e+XvWNomN/vGt7no33DqkfNZ9slbCJTVOvXS9QSmVHzCPIuI80I8u0PI8hbCtLJw6TU5018+qxj2b1nb0O5L0s5tx5BRci7ixr3A6wzNDzCxbfkHzxuvImy0ydpmUelDTN5jKWMpDnIHHatuGUoLJgcpJeHrVBE01tcTBFUhLzdL1v5qEZU225AO6qyaGYK8dJKK76ex1d+Z8M+s9MBE5obBcY6yOw3GT7z3B6GR3TUteKWoahgclnnYRRFMM+2ipmGKkLeboGtflRpdtHLQFRlsWjBrFghJsba03t2eO++3zuGhpuaL5KEzfATZDKsKwH/teKWoahgcmFLivrJordcdNNbFKYIKkAR4qbE/QCDKEOLKS2iKouFc3s4d17vKGVQ6xTH64WxB3FrpVIfS0s3rrknLC6Vn2YVuHeMBPavqNbdVePQSc3zcCyB6Mq8NreZhkpAs9Z+EWyTXtNUUNe8s0PYu1djrSJVBoLeCTQ3zTWz01+9cA590ye31LuLMuHUZUsyMav+jGFRj7pjRE+Nq+TD4lK14m3Wqlvopf3rGxa5SWoCy9s8OxZEYyxGXST6+vp09erVeYsxbvg/bnAqDm+LZubi5aErND205K3jI6iPsIqy2bOUgaB3UusQEBrMHmHPlsSMlyRtWEiK7q4au/fsjWyZ+yepBT2jn1qHsPTMYyLfXbMwGVCMMtA/MMhFN68N/I6iJvCVCRFZo6p9QcesR1AAoj72OK39Is5uDGuVrX7kdw3LH779uPKFlQh6J0HRQsN6ZXFbrEkHacNa382C1wWZL+KYdOKsFBfUA/Jy6KQal5+af2DBqJ5PO5gubYwgZ5rZ9+PYZ8tim+wfGOT2NYP7JvmMqHL7msFS+Fl7GS8XxaT2/FYUf5i9PK7czdL5bfb+8Q/vwHWeRD1HGU2XSTFFkDPNPvY4nghJV4XKg/6BQS6+ZV3gs158y7pSrRKVpGIYSyWSNNBaWIMgbCU0r8nDP0AaV+5DumqRg6ve3m6nSOhKdnkTtfJZ0RpUWWCKIGeatfjjtvbjrgqVB/Vez0jIeNSIaqlmYga9k1qHUOtsbO+OpVfWPzAY6koaNkgb1iAIWgmtLltYj/SNR02N5QW2Y2g4tDfrv3bY+4/r958lYUuwnjuvt1DfUlbYGEHONLPvl9UTwdsS7HADf8WhaDMxm43fJPEaSjLwG2WzfvrZPQ1hKfzXC7umd7GbA2sd+84P6qXd/cvtXHPGnIaJYM/tGWFXE1OOt4V/8S3rYr33uotnnkR9Z3nP0RkPzGsoZ6K8gqC4CiDq44jjcRJFnt5OXuJ4bGV1rTBPsDpBnkBR1wu7f9g78r6DVt5n1LWDeHgc3/el/esbHBbOOX4aVy+cE5i2f2CQRbeta/AGq3UKZ/3JtNIFUYzyGjLTUM4snNvD24/r2dcqqnvSAOM2SSzpJJpmA9xJ4w75Kcrg3Fhm1I71Ws3yYMfQcKLrhd0/rDXuvX/S99kpkjj9eJkDL+1fzw2rHm1wWLhh1aNc2h+85sGV39kwaib08IhWLoiimYZyJsyT5o5128ZlklgrcWSaubSOxVMmT2+nuCGQW3m+sHMGdwwxf8nKUS3KZm6Xce7jfZ6w3kV97d+oQHRJbPhC+FhAGN6YU5BtL/jGn20J3R/UKwgKBR5E0UyaScnUNCQiJwGfBTqBL6nqEt/xA4DrgeOAp4CzVPXhqGu2YhqKY+NrZurwBuoKWyYwKK0IqDoDd0H3jTPhJoj6ghth1w1bG6B7Uo1nh0cYcm29AoGVRHdXjYMOmBCYH1Fmi0m1jqZ25DDqg3PL79826gNs1oVvBf8iME8/u2fUIjBpTTCK854PmtjJrudGGsYcvGWpTletkwNrHYGVVF22uOacevmJ+j6OuOTO2JX7efN6uWPdtsC5CwK87IUH8esnngk894AJHezeE1x2DprYiaqOKltR5cL/DcQZ4/Bf94ZVj8ZKD81NmkEL5vSEjEVksZ5HlGkoM0UgIp3Ar4C3AFuB+4BzVPUBT5oPAK9S1feLyNnA21T1rKjrJlUEcWyzzez0fhshBM+qDLInegmy4TazBcchzvOMFe89jr3yrqaTlFqhs0NQVQLmZu3jvHm9qSiDuHnkVwZpjhFE4b1PK7O04ygeAT591rFNn2XG4uWxZAbH1j/3qrsClVStA7KaNuAvF1l8A804dFKNgctODDwWJU9XrZO3H9fD7WsGWyofcclrjOA1wCZV3ayqzwE3Aaf70pwO/Jf7+zbgz0TSdSGIY5uNSrN0xcbAir0+q9J/rzAlEHRfSMceHud50rxHVk4eI3ujlQCEd+2TEjePFFKZn+GfWNUMb34HuQY3mzsSx3wVFc7ZS1yZ6+l2hJhTspw75i8XWXwDzYhqU0fJMzQ8wo0/25J4PY80519kOUbQA3jfzlbg+LA0qrpHRHYCLwCe9CYSkQuBCwF6e3sTCRFnZm6r0RX9x+N8fP40rdqCo66b1ZT4+nXDPvTxIKn9OYy4eZRmnJl6BR7XHBhn1u5Y4vLHreDjlFHvuEKSNQHSwl8u8ggLsTOil9xMnlbKdZrPWAqvIVW9TlX7VLVv6tTwhbuDiDMzNypNVIvdfyxO696fpt6yG6svdZzniUtHiCj16+bp1ZOWz3mcZ8hq4DruugNjyedmIZ2TPFtQ7+O8eb2hvZGwSZBh5QpGh55Iir9c5FFGk9QVflop12k+Y5aKYBCY5tk+3N0XmEZEJgCH4Awap0acmblRaRYtmDVqxig4YwT+Dyksbdh96yyc28On/uKYyHOjiPM8Sa71zuN7I/NsLNePotYpkZUFwDnHT4tOEJPA2cEJ4v6PhbB1B7yMVQn5K++48fijruc1T129cE7oTPYws9U7jw/uzZ83r5dz5yXr6fvxl4usymgYQfVBXHm6ap2cc/y0RPKm3UjJ0jR0H3CkiMzEqfDPBt7pS7MMeBfwU+AdwEpNefQ6zszcOGnieA0FLQXYzGso8lwcO27dw+DQSTVUHR/yKK8h//NEeQ0dNLGTWmcHO4eGG547Kia+f+2B+jOC4zUEBHpnzD9iMmf29YZ6RkR5yqTtNZT3jG3/ugNBeTFWWVqNy58GQfeub0dN5vKuB+AlqddQ0Dfg9Rqql9kwT6X6dfumT+aSb96/73sB55xO2V/Go7wIg+QJ8xqKKg9peA1FkbX76CnAZ3DcR7+iqv8oIlcBq1V1mYgcCHwNmAv8DjhbVTdHXbNqM4sNwzDGg9zWI1DVO4E7ffsu8/x+FjgzSxkMwzCMaEoxWGwYhmFkhykCwzCMNscUgWEYRptjisAwDKPNKd16BCKyHXgkbzl8TME3G7rgmLzZYvJmi8nbGtNVNXBGbukUQRERkdVhbllFxOTNFpM3W0ze9DHTkGEYRptjisAwDKPNMUWQDtflLUBCTN5sMXmzxeRNGRsjMAzDaHOsR2AYhtHmmCIwDMNoc0wRJEREzhSRDSKyV0T6PPtniMiQiKx1/77gOXaciKwXkU0i8rm0l+NsRV732CWuTBtFZIFn/0nuvk0isni8ZPUjIleIyKAnT0/xHAuUPW+KkndRiMjDbnlcKyKr3X2TReR7IvJr9/+hOcr3FRF5QkR+4dkXKJ84fM7N7/tF5NUFkbdcZVdV7S/BH/AKYBbwQ6DPs38G8IuQc+4F5uEsMfBd4OQCyHs0sA44AJgJ/AYnXHin+/ulwEQ3zdE55fUVwEcD9gfKXoCyUZi8ayLnw8AU375PAovd34uBf85Rvv8DvNr7PYXJB5ziflPifmM/K4i8pSq71iNIiKo+qKqxV40WkZcAz1fVVeqUhOuBhVnJ5ydC3tOBm1R1t6o+BGwCXuP+bVLVzar6HHCTm7ZIhMmeN2XIuzBOB/7L/f1fjGMZ9aOqP8ZZn8RLmHynA9erwyqg2/3mxo0QecMoZNk1RZAuM0VkQER+JCKvd/f1AFs9aba6+/KmB9ji2a7LFbY/Lz7odvm/4jFXFE3GOkWVy48Cd4nIGhG50N33IlXd5v5+HHhRPqKFEiZfkfO8NGU304VpyoqIfB94ccChj6vqt0NO2wb0qupTInIc0C8iszMT0kOL8haCKNmBzwOfwKm4PgF8Cnj3+ElXWV6nqoMi8kLgeyLyS+9BVVURKaxfedHlcylV2TVFEICqvrmFc3YDu93fa0TkN8DLcdZrPtyT9HB3X2q0Iq8rg3fFb69cYftTJ67sIvJF4A53M0r2PCmqXA2o6qD7/wkR+RaOaeK3IvISVd3mmlaeyFXI0YTJV8g8V9Xf1n+XoeyaaSglRGSqiHS6v18KHAlsdruzfxCRea630PlAEVrpy4CzReQAEZmJI++9wH3AkSIyU0QmAme7accdn633bUDdKyNM9rwpTN6FISIHicjB9d/AiTj5ugx4l5vsXRSjjHoJk28ZcL7rPTQP2OkxIeVG6cpu3qPVZfvDealbcVr/vwVWuPvfDmwA1gI/B071nNOHUxB+A/wb7ozuPOV1j33clWkjHk8mHE+MX7nHPp5jXn8NWA/cj/MBvaSZ7Hn/FSXvIuR7KY7Xyjq3vH7c3f8C4AfAr4HvA5NzlPFGHFPrsFt23xMmH4630LVufq/H4xmXs7ylKrsWYsIwDKPNMdOQYRhGm2OKwDAMo80xRWAYhtHmmCIwDMNoc0wRGIZhtDmmCAwjISLydN4yGEaamCIwDMNoc0wRGEaLuLNZl4rIL9z4/me5+08QkR+KyG0i8ksR+bo7q9wwConFGjKM1jkDOBY4BpgC3CciP3aPzQVmA48B9wDzgZ/kIKNhNMV6BIbROq8DblTVEXWCjP0I+BP32L2qulVV9+KEHZmRj4iG0RxTBIaRDbs9v0ew3rdRYEwRGEbr/A9wloh0ishUnCUL848kaRgJsVaKYbTOt4DX4kTyVODvVfVxETkqX7EMIxkWfdQwDKPNMdOQYRhGm2OKwDAMo80xRWAYhtHmmCIwDMNoc0wRGIZhtDmmCAzDMNocUwSGYRhtzv8H6Jp8mztzOE0AAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "for feature in constants.LAND_USE_COLS + constants.NONLAND_FEATURES:\n", - " plot_context_change(feature, False)" + "# for feature in constants.LAND_USE_COLS + constants.NONLAND_FEATURES:\n", + "# plot_context_change(feature, False)" ] }, { @@ -1537,14 +1490,53 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 68, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 0%| | 0/6 [00:08\u001b[0;34m()\u001b[0m\n\u001b[1;32m 3\u001b[0m total_changes \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m pct \u001b[38;5;129;01min\u001b[39;00m tqdm(pcts):\n\u001b[0;32m----> 5\u001b[0m result_df \u001b[38;5;241m=\u001b[39m \u001b[43mheuristic_prescribe_and_predict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtest_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m2021\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[43mconstants\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mCAO_MAPPING\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcontext\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdummy_prescriptor\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mperfect_prescribe\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpct\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlinreg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcoef_\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 6\u001b[0m result_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtotal_emissions\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m result_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mELUC\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m*\u001b[39m result_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcell_area\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 7\u001b[0m result_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtotal_change\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m result_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mchange\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m*\u001b[39m result_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcell_area\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n", + "Input \u001b[0;32mIn [14]\u001b[0m, in \u001b[0;36mheuristic_prescribe_and_predict\u001b[0;34m(context_df, dummy_prescriptor, presc_func, *presc_args)\u001b[0m\n\u001b[1;32m 25\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mheuristic_prescribe_and_predict\u001b[39m(context_df, dummy_prescriptor, presc_func, \u001b[38;5;241m*\u001b[39mpresc_args):\n\u001b[1;32m 26\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 27\u001b[0m \u001b[38;5;124;03m Given a context and a heuristic function, prescribe actions and predict the resulting ELUC.\u001b[39;00m\n\u001b[1;32m 28\u001b[0m \u001b[38;5;124;03m :param context_df: The context dataframe.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 31\u001b[0m \u001b[38;5;124;03m :param presc_args: The arguments to pass to the heuristic function.\u001b[39;00m\n\u001b[1;32m 32\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 33\u001b[0m reco_df \u001b[38;5;241m=\u001b[39m \u001b[43mpresc_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcontext_df\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpresc_args\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 34\u001b[0m prescribed_actions_df \u001b[38;5;241m=\u001b[39m reco_df[constants\u001b[38;5;241m.\u001b[39mRECO_COLS] \u001b[38;5;241m-\u001b[39m context_df[constants\u001b[38;5;241m.\u001b[39mRECO_COLS]\n\u001b[1;32m 36\u001b[0m \u001b[38;5;66;03m# Rename the columns to match what the predictor expects\u001b[39;00m\n", + "Input \u001b[0;32mIn [14]\u001b[0m, in \u001b[0;36mperfect_prescribe\u001b[0;34m(context, pct_change, coefs)\u001b[0m\n\u001b[1;32m 10\u001b[0m reco_coefs \u001b[38;5;241m=\u001b[39m [coef \u001b[38;5;28;01mfor\u001b[39;00m coef \u001b[38;5;129;01min\u001b[39;00m coefficients \u001b[38;5;28;01mif\u001b[39;00m coef[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;129;01min\u001b[39;00m constants\u001b[38;5;241m.\u001b[39mRECO_COLS]\n\u001b[1;32m 11\u001b[0m reco_coefs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msorted\u001b[39m(reco_coefs, key\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mlambda\u001b[39;00m x: x[\u001b[38;5;241m1\u001b[39m], reverse\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m---> 12\u001b[0m adjusted \u001b[38;5;241m=\u001b[39m \u001b[43madjusted\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrow\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mperfect_prescribe_row\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrow\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mreco_coefs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpct_change\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m adjusted\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/frame.py:9568\u001b[0m, in \u001b[0;36mDataFrame.apply\u001b[0;34m(self, func, axis, raw, result_type, args, **kwargs)\u001b[0m\n\u001b[1;32m 9557\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcore\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mapply\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m frame_apply\n\u001b[1;32m 9559\u001b[0m op \u001b[38;5;241m=\u001b[39m frame_apply(\n\u001b[1;32m 9560\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 9561\u001b[0m func\u001b[38;5;241m=\u001b[39mfunc,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 9566\u001b[0m kwargs\u001b[38;5;241m=\u001b[39mkwargs,\n\u001b[1;32m 9567\u001b[0m )\n\u001b[0;32m-> 9568\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39m__finalize__(\u001b[38;5;28mself\u001b[39m, method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapply\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/apply.py:764\u001b[0m, in \u001b[0;36mFrameApply.apply\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 761\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mraw:\n\u001b[1;32m 762\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mapply_raw()\n\u001b[0;32m--> 764\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_standard\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/apply.py:891\u001b[0m, in \u001b[0;36mFrameApply.apply_standard\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 890\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply_standard\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m--> 891\u001b[0m results, res_index \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_series_generator\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 893\u001b[0m \u001b[38;5;66;03m# wrap results\u001b[39;00m\n\u001b[1;32m 894\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwrap_results(results, res_index)\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/apply.py:907\u001b[0m, in \u001b[0;36mFrameApply.apply_series_generator\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 904\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m option_context(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmode.chained_assignment\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m 905\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, v \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(series_gen):\n\u001b[1;32m 906\u001b[0m \u001b[38;5;66;03m# ignore SettingWithCopy here in case the user mutates\u001b[39;00m\n\u001b[0;32m--> 907\u001b[0m results[i] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 908\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(results[i], ABCSeries):\n\u001b[1;32m 909\u001b[0m \u001b[38;5;66;03m# If we have a view on v, we need to make a copy because\u001b[39;00m\n\u001b[1;32m 910\u001b[0m \u001b[38;5;66;03m# series_generator will swap out the underlying data\u001b[39;00m\n\u001b[1;32m 911\u001b[0m results[i] \u001b[38;5;241m=\u001b[39m results[i]\u001b[38;5;241m.\u001b[39mcopy(deep\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n", + "Input \u001b[0;32mIn [14]\u001b[0m, in \u001b[0;36mperfect_prescribe..\u001b[0;34m(row)\u001b[0m\n\u001b[1;32m 10\u001b[0m reco_coefs \u001b[38;5;241m=\u001b[39m [coef \u001b[38;5;28;01mfor\u001b[39;00m coef \u001b[38;5;129;01min\u001b[39;00m coefficients \u001b[38;5;28;01mif\u001b[39;00m coef[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;129;01min\u001b[39;00m constants\u001b[38;5;241m.\u001b[39mRECO_COLS]\n\u001b[1;32m 11\u001b[0m reco_coefs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28msorted\u001b[39m(reco_coefs, key\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mlambda\u001b[39;00m x: x[\u001b[38;5;241m1\u001b[39m], reverse\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m---> 12\u001b[0m adjusted \u001b[38;5;241m=\u001b[39m adjusted\u001b[38;5;241m.\u001b[39mapply(\u001b[38;5;28;01mlambda\u001b[39;00m row: \u001b[43mperfect_prescribe_row\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrow\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mreco_coefs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpct_change\u001b[49m\u001b[43m)\u001b[49m, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m adjusted\n", + "Input \u001b[0;32mIn [13]\u001b[0m, in \u001b[0;36mperfect_prescribe_row\u001b[0;34m(row, reco_coefs, pct_change)\u001b[0m\n\u001b[1;32m 5\u001b[0m scaled_change \u001b[38;5;241m=\u001b[39m pct_change \u001b[38;5;241m*\u001b[39m row[constants\u001b[38;5;241m.\u001b[39mLAND_USE_COLS]\u001b[38;5;241m.\u001b[39msum()\n\u001b[1;32m 6\u001b[0m best_col \u001b[38;5;241m=\u001b[39m reco_coefs[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m][\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m----> 7\u001b[0m max_change \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmin\u001b[39m(\u001b[43mrow\u001b[49m\u001b[43m[\u001b[49m\u001b[43mconstants\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mRECO_COLS\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241m.\u001b[39msum() \u001b[38;5;241m-\u001b[39m row[best_col], scaled_change)\n\u001b[1;32m 8\u001b[0m changed \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m coef \u001b[38;5;129;01min\u001b[39;00m reco_coefs:\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/series.py:1007\u001b[0m, in \u001b[0;36mSeries.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1004\u001b[0m key \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39masarray(key, dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mbool\u001b[39m)\n\u001b[1;32m 1005\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_values(key)\n\u001b[0;32m-> 1007\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_with\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/series.py:1047\u001b[0m, in \u001b[0;36mSeries._get_with\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1044\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39miloc[key]\n\u001b[1;32m 1046\u001b[0m \u001b[38;5;66;03m# handle the dup indexing case GH#4246\u001b[39;00m\n\u001b[0;32m-> 1047\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloc\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/indexing.py:1073\u001b[0m, in \u001b[0;36m_LocationIndexer.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1070\u001b[0m axis \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxis \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m 1072\u001b[0m maybe_callable \u001b[38;5;241m=\u001b[39m com\u001b[38;5;241m.\u001b[39mapply_if_callable(key, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj)\n\u001b[0;32m-> 1073\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_axis\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmaybe_callable\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/indexing.py:1301\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1298\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(key, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mndim\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mand\u001b[39;00m key\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m 1299\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot index with multidimensional key\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m-> 1301\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_iterable\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1303\u001b[0m \u001b[38;5;66;03m# nested tuple slicing\u001b[39;00m\n\u001b[1;32m 1304\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_nested_tuple(key, labels):\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/indexing.py:1239\u001b[0m, in \u001b[0;36m_LocIndexer._getitem_iterable\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1236\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_key(key, axis)\n\u001b[1;32m 1238\u001b[0m \u001b[38;5;66;03m# A collection of keys\u001b[39;00m\n\u001b[0;32m-> 1239\u001b[0m keyarr, indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_listlike_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1240\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_reindex_with_indexers(\n\u001b[1;32m 1241\u001b[0m {axis: [keyarr, indexer]}, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, allow_dups\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 1242\u001b[0m )\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/indexing.py:1432\u001b[0m, in \u001b[0;36m_LocIndexer._get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1429\u001b[0m ax \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis(axis)\n\u001b[1;32m 1430\u001b[0m axis_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobj\u001b[38;5;241m.\u001b[39m_get_axis_name(axis)\n\u001b[0;32m-> 1432\u001b[0m keyarr, indexer \u001b[38;5;241m=\u001b[39m \u001b[43max\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_indexer_strict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis_name\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1434\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m keyarr, indexer\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/indexes/base.py:6066\u001b[0m, in \u001b[0;36mIndex._get_indexer_strict\u001b[0;34m(self, key, axis_name)\u001b[0m\n\u001b[1;32m 6064\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_index_as_unique:\n\u001b[1;32m 6065\u001b[0m indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_indexer_for(keyarr)\n\u001b[0;32m-> 6066\u001b[0m keyarr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreindex\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkeyarr\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 6067\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 6068\u001b[0m keyarr, indexer, new_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reindex_non_unique(keyarr)\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/indexes/base.py:4393\u001b[0m, in \u001b[0;36mIndex.reindex\u001b[0;34m(self, target, method, level, limit, tolerance)\u001b[0m\n\u001b[1;32m 4391\u001b[0m target \u001b[38;5;241m=\u001b[39m idx[:\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 4392\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 4393\u001b[0m target \u001b[38;5;241m=\u001b[39m \u001b[43mensure_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtarget\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4395\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m (\n\u001b[1;32m 4396\u001b[0m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m, ABCMultiIndex) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(target, ABCMultiIndex)\n\u001b[1;32m 4397\u001b[0m ):\n\u001b[1;32m 4398\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m method \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/indexes/base.py:7333\u001b[0m, in \u001b[0;36mensure_index\u001b[0;34m(index_like, copy)\u001b[0m\n\u001b[1;32m 7331\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m Index\u001b[38;5;241m.\u001b[39m_with_infer(index_like, copy\u001b[38;5;241m=\u001b[39mcopy, tupleize_cols\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 7332\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 7333\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mIndex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_with_infer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mindex_like\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/indexes/base.py:715\u001b[0m, in \u001b[0;36mIndex._with_infer\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m 710\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 711\u001b[0m \u001b[38;5;124;03mConstructor that uses the 1.0.x behavior inferring numeric dtypes\u001b[39;00m\n\u001b[1;32m 712\u001b[0m \u001b[38;5;124;03mfor ndarray[object] inputs.\u001b[39;00m\n\u001b[1;32m 713\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 714\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m warnings\u001b[38;5;241m.\u001b[39mcatch_warnings():\n\u001b[0;32m--> 715\u001b[0m \u001b[43mwarnings\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfilterwarnings\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mignore\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m.*the Index constructor\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;167;43;01mFutureWarning\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 716\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mcls\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 718\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m result\u001b[38;5;241m.\u001b[39mdtype \u001b[38;5;241m==\u001b[39m _dtype_obj \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m result\u001b[38;5;241m.\u001b[39m_is_multi:\n\u001b[1;32m 719\u001b[0m \u001b[38;5;66;03m# error: Argument 1 to \"maybe_convert_objects\" has incompatible type\u001b[39;00m\n\u001b[1;32m 720\u001b[0m \u001b[38;5;66;03m# \"Union[ExtensionArray, ndarray[Any, Any]]\"; expected\u001b[39;00m\n\u001b[1;32m 721\u001b[0m \u001b[38;5;66;03m# \"ndarray[Any, Any]\"\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/warnings.py:155\u001b[0m, in \u001b[0;36mfilterwarnings\u001b[0;34m(action, message, category, module, lineno, append)\u001b[0m\n\u001b[1;32m 152\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mre\u001b[39;00m\n\u001b[1;32m 154\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m message:\n\u001b[0;32m--> 155\u001b[0m message \u001b[38;5;241m=\u001b[39m \u001b[43mre\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompile\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mre\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mI\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 156\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 157\u001b[0m message \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/re.py:249\u001b[0m, in \u001b[0;36mcompile\u001b[0;34m(pattern, flags)\u001b[0m\n\u001b[1;32m 243\u001b[0m \u001b[38;5;124;03m\"\"\"Return an iterator over all non-overlapping matches in the\u001b[39;00m\n\u001b[1;32m 244\u001b[0m \u001b[38;5;124;03m string. For each match, the iterator returns a Match object.\u001b[39;00m\n\u001b[1;32m 245\u001b[0m \n\u001b[1;32m 246\u001b[0m \u001b[38;5;124;03m Empty matches are included in the result.\"\"\"\u001b[39;00m\n\u001b[1;32m 247\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _compile(pattern, flags)\u001b[38;5;241m.\u001b[39mfinditer(string)\n\u001b[0;32m--> 249\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcompile\u001b[39m(pattern, flags\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m):\n\u001b[1;32m 250\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCompile a regular expression pattern, returning a Pattern object.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 251\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _compile(pattern, flags)\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], "source": [ "pcts = [0.01, 0.05, 0.1, 0.2, 0.5, 1]\n", "total_emissions = []\n", "total_changes = []\n", - "for pct in pcts:\n", + "for pct in tqdm(pcts):\n", " result_df = heuristic_prescribe_and_predict(dataset.test_df.loc[2021][constants.CAO_MAPPING[\"context\"]], dummy_prescriptor, perfect_prescribe, pct, linreg.coef_)\n", " result_df[\"total_emissions\"] = result_df[\"ELUC\"] * result_df[\"cell_area\"]\n", " result_df[\"total_change\"] = result_df[\"change\"] * result_df[\"cell_area\"]\n", @@ -1554,7 +1546,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1568,7 +1560,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -1595,7 +1587,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": null, "metadata": {}, "outputs": [ { diff --git a/use_cases/eluc/prescriptors/create_seeds.ipynb b/use_cases/eluc/prescriptors/create_seeds.ipynb index ba5ecb6..720b582 100644 --- a/use_cases/eluc/prescriptors/create_seeds.ipynb +++ b/use_cases/eluc/prescriptors/create_seeds.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 19, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -92,7 +92,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -101,630 +101,625 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Take small subset for training, we really don't need more and just need the model to converge\n", - "seed_sample = dataset.train_df.sample(1000)\n", + "seed_sample = dataset.train_df.sample(1000, random_state=42)\n", "encoded_seed_sample = dataset.encoder.encode_as_df(seed_sample)\n", - "seed_dir = Path(\"prescriptors/seeds/test\")" + "seed_dir = Path(\"prescriptors/seeds/no-overlap\")" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Metal device set to: Apple M1 Pro\n", - "\n", - "systemMemory: 16.00 GB\n", - "maxCacheSize: 5.33 GB\n", - "\n", "Epoch 1/300\n", - "8/8 [==============================] - 1s 33ms/step - loss: 0.4067 - mae: 0.4067\n", + "8/8 [==============================] - 1s 29ms/step - loss: 0.4246 - mae: 0.4246\n", "Epoch 2/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.3389 - mae: 0.3389\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.2984 - mae: 0.2984\n", "Epoch 3/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.3015 - mae: 0.3015\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.2446 - mae: 0.2446\n", "Epoch 4/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.2805 - mae: 0.2805\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.2366 - mae: 0.2366\n", "Epoch 5/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.2592 - mae: 0.2592\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.2178 - mae: 0.2178\n", "Epoch 6/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.2384 - mae: 0.2384\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.2059 - mae: 0.2059\n", "Epoch 7/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.2192 - mae: 0.2192\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.1937 - mae: 0.1937\n", "Epoch 8/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.2027 - mae: 0.2027\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1823 - mae: 0.1823\n", "Epoch 9/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1890 - mae: 0.1890\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1720 - mae: 0.1720\n", "Epoch 10/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1772 - mae: 0.1772\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1621 - mae: 0.1621\n", "Epoch 11/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1673 - mae: 0.1673\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1526 - mae: 0.1526\n", "Epoch 12/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1590 - mae: 0.1590\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1434 - mae: 0.1434\n", "Epoch 13/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.1521 - mae: 0.1521\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1346 - mae: 0.1346\n", "Epoch 14/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1459 - mae: 0.1459\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1263 - mae: 0.1263\n", "Epoch 15/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1403 - mae: 0.1403\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1185 - mae: 0.1185\n", "Epoch 16/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1352 - mae: 0.1352\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1109 - mae: 0.1109\n", "Epoch 17/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1304 - mae: 0.1304\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.1046 - mae: 0.1046\n", "Epoch 18/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1260 - mae: 0.1260\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0985 - mae: 0.0985\n", "Epoch 19/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1223 - mae: 0.1223\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0929 - mae: 0.0929\n", "Epoch 20/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1185 - mae: 0.1185\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0879 - mae: 0.0879\n", "Epoch 21/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1150 - mae: 0.1150\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0833 - mae: 0.0833\n", "Epoch 22/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1116 - mae: 0.1116\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0789 - mae: 0.0789\n", "Epoch 23/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1086 - mae: 0.1086\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0752 - mae: 0.0752\n", "Epoch 24/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1057 - mae: 0.1057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0713 - mae: 0.0713\n", "Epoch 25/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1029 - mae: 0.1029\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0677 - mae: 0.0677\n", "Epoch 26/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1002 - mae: 0.1002\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0640 - mae: 0.0640\n", "Epoch 27/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0978 - mae: 0.0978\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0607 - mae: 0.0607\n", "Epoch 28/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0950 - mae: 0.0950\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0575 - mae: 0.0575\n", "Epoch 29/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0925 - mae: 0.0925\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0546 - mae: 0.0546\n", "Epoch 30/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0901 - mae: 0.0901\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0517 - mae: 0.0517\n", "Epoch 31/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0879 - mae: 0.0879\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0490 - mae: 0.0490\n", "Epoch 32/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0861 - mae: 0.0861\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0460 - mae: 0.0460\n", "Epoch 33/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0838 - mae: 0.0838\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0435 - mae: 0.0435\n", "Epoch 34/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0817 - mae: 0.0817\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0409 - mae: 0.0409\n", "Epoch 35/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0796 - mae: 0.0796\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0384 - mae: 0.0384\n", "Epoch 36/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0778 - mae: 0.0778\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0361 - mae: 0.0361\n", "Epoch 37/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0757 - mae: 0.0757\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0337 - mae: 0.0337\n", "Epoch 38/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0739 - mae: 0.0739\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0317 - mae: 0.0317\n", "Epoch 39/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0719 - mae: 0.0719\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0295 - mae: 0.0295\n", "Epoch 40/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0700 - mae: 0.0700\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0277 - mae: 0.0277\n", "Epoch 41/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0680 - mae: 0.0680\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0260 - mae: 0.0260\n", "Epoch 42/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0664 - mae: 0.0664\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0248 - mae: 0.0248\n", "Epoch 43/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0644 - mae: 0.0644\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0235 - mae: 0.0235\n", "Epoch 44/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0623 - mae: 0.0623\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0228 - mae: 0.0228\n", "Epoch 45/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0604 - mae: 0.0604\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0216 - mae: 0.0216\n", "Epoch 46/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0586 - mae: 0.0586\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0208 - mae: 0.0208\n", "Epoch 47/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0567 - mae: 0.0567\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0197 - mae: 0.0197\n", "Epoch 48/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0545 - mae: 0.0545\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0188 - mae: 0.0188\n", "Epoch 49/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0526 - mae: 0.0526\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0181 - mae: 0.0181\n", "Epoch 50/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0507 - mae: 0.0507\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0173 - mae: 0.0173\n", "Epoch 51/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0487 - mae: 0.0487\n", + "8/8 [==============================] - 0s 15ms/step - loss: 0.0168 - mae: 0.0168\n", "Epoch 52/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0467 - mae: 0.0467\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0164 - mae: 0.0164\n", "Epoch 53/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0446 - mae: 0.0446\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0155 - mae: 0.0155\n", "Epoch 54/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0426 - mae: 0.0426\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0152 - mae: 0.0152\n", "Epoch 55/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0406 - mae: 0.0406\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0148 - mae: 0.0148\n", "Epoch 56/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0391 - mae: 0.0391\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0145 - mae: 0.0145\n", "Epoch 57/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0371 - mae: 0.0371\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0138 - mae: 0.0138\n", "Epoch 58/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0350 - mae: 0.0350\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0133 - mae: 0.0133\n", "Epoch 59/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0336 - mae: 0.0336\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0130 - mae: 0.0130\n", "Epoch 60/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0321 - mae: 0.0321\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0129 - mae: 0.0129\n", "Epoch 61/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0305 - mae: 0.0305\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0126 - mae: 0.0126\n", "Epoch 62/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0290 - mae: 0.0290\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0123 - mae: 0.0123\n", "Epoch 63/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0278 - mae: 0.0278\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0121 - mae: 0.0121\n", "Epoch 64/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0269 - mae: 0.0269\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0118 - mae: 0.0118\n", "Epoch 65/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0260 - mae: 0.0260\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0117 - mae: 0.0117\n", "Epoch 66/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0249 - mae: 0.0249\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0114 - mae: 0.0114\n", "Epoch 67/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0242 - mae: 0.0242\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0111 - mae: 0.0111\n", "Epoch 68/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0235 - mae: 0.0235\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0112 - mae: 0.0112\n", "Epoch 69/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0227 - mae: 0.0227\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0108 - mae: 0.0108\n", "Epoch 70/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0222 - mae: 0.0222\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0106 - mae: 0.0106\n", "Epoch 71/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0213 - mae: 0.0213\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0104 - mae: 0.0104\n", "Epoch 72/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0208 - mae: 0.0208\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0102 - mae: 0.0102\n", "Epoch 73/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0202 - mae: 0.0202\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0100 - mae: 0.0100\n", "Epoch 74/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0198 - mae: 0.0198\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0098 - mae: 0.0098\n", "Epoch 75/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0192 - mae: 0.0192\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0096 - mae: 0.0096\n", "Epoch 76/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0189 - mae: 0.0189\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0095 - mae: 0.0095\n", "Epoch 77/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0190 - mae: 0.0190\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0093 - mae: 0.0093\n", "Epoch 78/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0188 - mae: 0.0188\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0091 - mae: 0.0091\n", "Epoch 79/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0180 - mae: 0.0180\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0092 - mae: 0.0092\n", "Epoch 80/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0178 - mae: 0.0178\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0091 - mae: 0.0091\n", "Epoch 81/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0174 - mae: 0.0174\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0091 - mae: 0.0091\n", "Epoch 82/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0173 - mae: 0.0173\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0092 - mae: 0.0092\n", "Epoch 83/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0171 - mae: 0.0171\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0087 - mae: 0.0087\n", "Epoch 84/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0167 - mae: 0.0167\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0085 - mae: 0.0085\n", "Epoch 85/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0167 - mae: 0.0167\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0087 - mae: 0.0087\n", "Epoch 86/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0166 - mae: 0.0166\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0087 - mae: 0.0087\n", "Epoch 87/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0159 - mae: 0.0159\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0084 - mae: 0.0084\n", "Epoch 88/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0159 - mae: 0.0159\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0080 - mae: 0.0080\n", "Epoch 89/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0159 - mae: 0.0159\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0081 - mae: 0.0081\n", "Epoch 90/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0157 - mae: 0.0157\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0079 - mae: 0.0079\n", "Epoch 91/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0155 - mae: 0.0155\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0078 - mae: 0.0078\n", "Epoch 92/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0152 - mae: 0.0152\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0077 - mae: 0.0077\n", "Epoch 93/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0150 - mae: 0.0150\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0075 - mae: 0.0075\n", "Epoch 94/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0150 - mae: 0.0150\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0075 - mae: 0.0075\n", "Epoch 95/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0147 - mae: 0.0147\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0074 - mae: 0.0074\n", "Epoch 96/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0146 - mae: 0.0146\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0074 - mae: 0.0074\n", "Epoch 97/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0146 - mae: 0.0146\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0074 - mae: 0.0074\n", "Epoch 98/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0143 - mae: 0.0143\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0072 - mae: 0.0072\n", "Epoch 99/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0141 - mae: 0.0141\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0071 - mae: 0.0071\n", "Epoch 100/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0139 - mae: 0.0139\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0070 - mae: 0.0070\n", "Epoch 101/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0137 - mae: 0.0137\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0069 - mae: 0.0069\n", "Epoch 102/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0134 - mae: 0.0134\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0070 - mae: 0.0070\n", "Epoch 103/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0134 - mae: 0.0134\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0069 - mae: 0.0069\n", "Epoch 104/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0135 - mae: 0.0135\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0070 - mae: 0.0070\n", "Epoch 105/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0131 - mae: 0.0131\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0069 - mae: 0.0069\n", "Epoch 106/300\n", - "8/8 [==============================] - 0s 15ms/step - loss: 0.0129 - mae: 0.0129\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0068 - mae: 0.0068\n", "Epoch 107/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0127 - mae: 0.0127\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0070 - mae: 0.0070\n", "Epoch 108/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0128 - mae: 0.0128\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0066 - mae: 0.0066\n", "Epoch 109/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0129 - mae: 0.0129\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0065 - mae: 0.0065\n", "Epoch 110/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0127 - mae: 0.0127\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0065 - mae: 0.0065\n", "Epoch 111/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0124 - mae: 0.0124\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0061 - mae: 0.0061\n", "Epoch 112/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0119 - mae: 0.0119\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0062 - mae: 0.0062\n", "Epoch 113/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0119 - mae: 0.0119\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0063 - mae: 0.0063\n", "Epoch 114/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0118 - mae: 0.0118\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0063 - mae: 0.0063\n", "Epoch 115/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0117 - mae: 0.0117\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0062 - mae: 0.0062\n", "Epoch 116/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0117 - mae: 0.0117\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0062 - mae: 0.0062\n", "Epoch 117/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0116 - mae: 0.0116\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0065 - mae: 0.0065\n", "Epoch 118/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0115 - mae: 0.0115\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0060 - mae: 0.0060\n", "Epoch 119/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0119 - mae: 0.0119\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0061 - mae: 0.0061\n", "Epoch 120/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0117 - mae: 0.0117\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0060 - mae: 0.0060\n", "Epoch 121/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0114 - mae: 0.0114\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0059 - mae: 0.0059\n", "Epoch 122/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0111 - mae: 0.0111\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0059 - mae: 0.0059\n", "Epoch 123/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0111 - mae: 0.0111\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0058 - mae: 0.0058\n", "Epoch 124/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0108 - mae: 0.0108\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0057 - mae: 0.0057\n", "Epoch 125/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0109 - mae: 0.0109\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0058 - mae: 0.0058\n", "Epoch 126/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0109 - mae: 0.0109\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0060 - mae: 0.0060\n", "Epoch 127/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0108 - mae: 0.0108\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0057 - mae: 0.0057\n", "Epoch 128/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0105 - mae: 0.0105\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 129/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0104 - mae: 0.0104\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 130/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0106 - mae: 0.0106\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 131/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0106 - mae: 0.0106\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0059 - mae: 0.0059\n", "Epoch 132/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0103 - mae: 0.0103\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 133/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0104 - mae: 0.0104\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 134/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0102 - mae: 0.0102\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 135/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0098 - mae: 0.0098\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 136/300\n", - "8/8 [==============================] - 0s 15ms/step - loss: 0.0098 - mae: 0.0098\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 137/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0100 - mae: 0.0100\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 138/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0100 - mae: 0.0100\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 139/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0100 - mae: 0.0100\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 140/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0095 - mae: 0.0095\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 141/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0096 - mae: 0.0096\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 142/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0097 - mae: 0.0097\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 143/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0095 - mae: 0.0095\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 144/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0094 - mae: 0.0094\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 145/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0092 - mae: 0.0092\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 146/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0092 - mae: 0.0092\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 147/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0091 - mae: 0.0091\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 148/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0094 - mae: 0.0094\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0051 - mae: 0.0051\n", "Epoch 149/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0090 - mae: 0.0090\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 150/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0091 - mae: 0.0091\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 151/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0091 - mae: 0.0091\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 152/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0088 - mae: 0.0088\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 153/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0090 - mae: 0.0090\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 154/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0087 - mae: 0.0087\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 155/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0088 - mae: 0.0088\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0051 - mae: 0.0051\n", "Epoch 156/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0087 - mae: 0.0087\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 157/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0085 - mae: 0.0085\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 158/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0085 - mae: 0.0085\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 159/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0085 - mae: 0.0085\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 160/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0081 - mae: 0.0081\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0050 - mae: 0.0050\n", "Epoch 161/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0080 - mae: 0.0080\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 162/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0081 - mae: 0.0081\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 163/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0081 - mae: 0.0081\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0050 - mae: 0.0050\n", "Epoch 164/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0078 - mae: 0.0078\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 165/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0078 - mae: 0.0078\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 166/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0081 - mae: 0.0081\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 167/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0078 - mae: 0.0078\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 168/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0075 - mae: 0.0075\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 169/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0075 - mae: 0.0075\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 170/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0076 - mae: 0.0076\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 171/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0075 - mae: 0.0075\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 172/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0074 - mae: 0.0074\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 173/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0074 - mae: 0.0074\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 174/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0074 - mae: 0.0074\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 175/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0072 - mae: 0.0072\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 176/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 177/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 178/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 179/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 180/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0051 - mae: 0.0051\n", "Epoch 181/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0068 - mae: 0.0068\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 182/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0066 - mae: 0.0066\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 183/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0067 - mae: 0.0067\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 184/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0066 - mae: 0.0066\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 185/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0065 - mae: 0.0065\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 186/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0066 - mae: 0.0066\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 187/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0069 - mae: 0.0069\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 188/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0066 - mae: 0.0066\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 189/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0064 - mae: 0.0064\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 190/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0065 - mae: 0.0065\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 191/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0062 - mae: 0.0062\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 192/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0062 - mae: 0.0062\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 193/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0061 - mae: 0.0061\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 194/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0067 - mae: 0.0067\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 195/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 196/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0062 - mae: 0.0062\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 197/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0064 - mae: 0.0064\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 198/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0062 - mae: 0.0062\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 199/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0064 - mae: 0.0064\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 200/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0064 - mae: 0.0064\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 201/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0061 - mae: 0.0061\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 202/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0060 - mae: 0.0060\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 203/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0060 - mae: 0.0060\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 204/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0059 - mae: 0.0059\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 205/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0058 - mae: 0.0058\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 206/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0058 - mae: 0.0058\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 207/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0059 - mae: 0.0059\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 208/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0059 - mae: 0.0059\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 209/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0058 - mae: 0.0058\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 210/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0058 - mae: 0.0058\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 211/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 212/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 213/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 214/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 215/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 216/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0055 - mae: 0.0055\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 217/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 218/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 219/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 220/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 221/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 222/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 223/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 224/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 225/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 15ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 226/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 227/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 228/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 229/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0055 - mae: 0.0055\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 230/300\n", - "8/8 [==============================] - 0s 15ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 231/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 232/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 233/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 234/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0060 - mae: 0.0060\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 235/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 236/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 237/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 238/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 239/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0051 - mae: 0.0051\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 240/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0050 - mae: 0.0050\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 241/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0048 - mae: 0.0048\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 242/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 243/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0050 - mae: 0.0050\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 244/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 245/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 246/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 247/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0050 - mae: 0.0050\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 248/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 249/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0055 - mae: 0.0055\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 250/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 251/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 252/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 253/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0051 - mae: 0.0051\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 254/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0051 - mae: 0.0051\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 255/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 256/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 257/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 258/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0048 - mae: 0.0048\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 259/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 260/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 261/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 262/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 263/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 264/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 265/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 266/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 267/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 268/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 269/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 270/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 271/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 272/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 273/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 274/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 275/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 276/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 277/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0035 - mae: 0.0035\n", "Epoch 278/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 279/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 280/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 281/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 282/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 283/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 284/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 285/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 286/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0034 - mae: 0.0034\n", "Epoch 287/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0035 - mae: 0.0035\n", "Epoch 288/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0035 - mae: 0.0035\n", "Epoch 289/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0035 - mae: 0.0035\n", "Epoch 290/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0035 - mae: 0.0035\n", "Epoch 291/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0035 - mae: 0.0035\n", "Epoch 292/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 293/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0035 - mae: 0.0035\n", "Epoch 294/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0034 - mae: 0.0034\n", "Epoch 295/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0034 - mae: 0.0034\n", "Epoch 296/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0034 - mae: 0.0034\n", "Epoch 297/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 298/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0033 - mae: 0.0033\n", "Epoch 299/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0035 - mae: 0.0035\n", "Epoch 300/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0041 - mae: 0.0041\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0033 - mae: 0.0033\n", "Epoch 1/300\n" ] }, @@ -740,605 +735,605 @@ "name": "stdout", "output_type": "stream", "text": [ - "8/8 [==============================] - 1s 28ms/step - loss: 0.5399 - mae: 0.5399\n", + "8/8 [==============================] - 1s 27ms/step - loss: 0.3546 - mae: 0.3546\n", "Epoch 2/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.3729 - mae: 0.3729\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.2565 - mae: 0.2565\n", "Epoch 3/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.2427 - mae: 0.2427\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.2187 - mae: 0.2187\n", "Epoch 4/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1881 - mae: 0.1881\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.2067 - mae: 0.2067\n", "Epoch 5/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1895 - mae: 0.1895\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.1911 - mae: 0.1911\n", "Epoch 6/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1734 - mae: 0.1734\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1785 - mae: 0.1785\n", "Epoch 7/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1630 - mae: 0.1630\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1672 - mae: 0.1672\n", "Epoch 8/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1559 - mae: 0.1559\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1567 - mae: 0.1567\n", "Epoch 9/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1472 - mae: 0.1472\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1471 - mae: 0.1471\n", "Epoch 10/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1403 - mae: 0.1403\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1382 - mae: 0.1382\n", "Epoch 11/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1335 - mae: 0.1335\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1298 - mae: 0.1298\n", "Epoch 12/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.1271 - mae: 0.1271\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1215 - mae: 0.1215\n", "Epoch 13/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1209 - mae: 0.1209\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1143 - mae: 0.1143\n", "Epoch 14/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1150 - mae: 0.1150\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.1069 - mae: 0.1069\n", "Epoch 15/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1091 - mae: 0.1091\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.1004 - mae: 0.1004\n", "Epoch 16/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.1036 - mae: 0.1036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0940 - mae: 0.0940\n", "Epoch 17/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0980 - mae: 0.0980\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0879 - mae: 0.0879\n", "Epoch 18/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0925 - mae: 0.0925\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0826 - mae: 0.0826\n", "Epoch 19/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0872 - mae: 0.0872\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0776 - mae: 0.0776\n", "Epoch 20/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0819 - mae: 0.0819\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0734 - mae: 0.0734\n", "Epoch 21/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0769 - mae: 0.0769\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0692 - mae: 0.0692\n", "Epoch 22/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0720 - mae: 0.0720\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0655 - mae: 0.0655\n", "Epoch 23/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0674 - mae: 0.0674\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0619 - mae: 0.0619\n", "Epoch 24/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0630 - mae: 0.0630\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0583 - mae: 0.0583\n", "Epoch 25/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0593 - mae: 0.0593\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0554 - mae: 0.0554\n", "Epoch 26/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0560 - mae: 0.0560\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0522 - mae: 0.0522\n", "Epoch 27/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0534 - mae: 0.0534\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0495 - mae: 0.0495\n", "Epoch 28/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0512 - mae: 0.0512\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0469 - mae: 0.0469\n", "Epoch 29/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0493 - mae: 0.0493\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0446 - mae: 0.0446\n", "Epoch 30/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0475 - mae: 0.0475\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0425 - mae: 0.0425\n", "Epoch 31/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0460 - mae: 0.0460\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0404 - mae: 0.0404\n", "Epoch 32/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0444 - mae: 0.0444\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0387 - mae: 0.0387\n", "Epoch 33/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0427 - mae: 0.0427\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0369 - mae: 0.0369\n", "Epoch 34/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0411 - mae: 0.0411\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0352 - mae: 0.0352\n", "Epoch 35/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0397 - mae: 0.0397\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0337 - mae: 0.0337\n", "Epoch 36/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0384 - mae: 0.0384\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0324 - mae: 0.0324\n", "Epoch 37/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0372 - mae: 0.0372\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0312 - mae: 0.0312\n", "Epoch 38/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0361 - mae: 0.0361\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0302 - mae: 0.0302\n", "Epoch 39/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0347 - mae: 0.0347\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0293 - mae: 0.0293\n", "Epoch 40/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0334 - mae: 0.0334\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0282 - mae: 0.0282\n", "Epoch 41/300\n", - "8/8 [==============================] - 0s 15ms/step - loss: 0.0322 - mae: 0.0322\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0271 - mae: 0.0271\n", "Epoch 42/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0312 - mae: 0.0312\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0264 - mae: 0.0264\n", "Epoch 43/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0301 - mae: 0.0301\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0255 - mae: 0.0255\n", "Epoch 44/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0290 - mae: 0.0290\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0245 - mae: 0.0245\n", "Epoch 45/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0281 - mae: 0.0281\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0241 - mae: 0.0241\n", "Epoch 46/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0276 - mae: 0.0276\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0235 - mae: 0.0235\n", "Epoch 47/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0270 - mae: 0.0270\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0230 - mae: 0.0230\n", "Epoch 48/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0259 - mae: 0.0259\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0221 - mae: 0.0221\n", "Epoch 49/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0250 - mae: 0.0250\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0216 - mae: 0.0216\n", "Epoch 50/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0241 - mae: 0.0241\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0211 - mae: 0.0211\n", "Epoch 51/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0236 - mae: 0.0236\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0206 - mae: 0.0206\n", "Epoch 52/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0229 - mae: 0.0229\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0204 - mae: 0.0204\n", "Epoch 53/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0224 - mae: 0.0224\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0200 - mae: 0.0200\n", "Epoch 54/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0217 - mae: 0.0217\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0195 - mae: 0.0195\n", "Epoch 55/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0212 - mae: 0.0212\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0192 - mae: 0.0192\n", "Epoch 56/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0206 - mae: 0.0206\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0190 - mae: 0.0190\n", "Epoch 57/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0202 - mae: 0.0202\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0188 - mae: 0.0188\n", "Epoch 58/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0196 - mae: 0.0196\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0189 - mae: 0.0189\n", "Epoch 59/300\n", - "8/8 [==============================] - 0s 15ms/step - loss: 0.0193 - mae: 0.0193\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0183 - mae: 0.0183\n", "Epoch 60/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0188 - mae: 0.0188\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0177 - mae: 0.0177\n", "Epoch 61/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0185 - mae: 0.0185\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0175 - mae: 0.0175\n", "Epoch 62/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0179 - mae: 0.0179\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0172 - mae: 0.0172\n", "Epoch 63/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0175 - mae: 0.0175\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0169 - mae: 0.0169\n", "Epoch 64/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0172 - mae: 0.0172\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0169 - mae: 0.0169\n", "Epoch 65/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0169 - mae: 0.0169\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0171 - mae: 0.0171\n", "Epoch 66/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0166 - mae: 0.0166\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0163 - mae: 0.0163\n", "Epoch 67/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0161 - mae: 0.0161\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0160 - mae: 0.0160\n", "Epoch 68/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0158 - mae: 0.0158\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0160 - mae: 0.0160\n", "Epoch 69/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0154 - mae: 0.0154\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0158 - mae: 0.0158\n", "Epoch 70/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0152 - mae: 0.0152\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0153 - mae: 0.0153\n", "Epoch 71/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0149 - mae: 0.0149\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0150 - mae: 0.0150\n", "Epoch 72/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0145 - mae: 0.0145\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0150 - mae: 0.0150\n", "Epoch 73/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0143 - mae: 0.0143\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0149 - mae: 0.0149\n", "Epoch 74/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0140 - mae: 0.0140\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0145 - mae: 0.0145\n", "Epoch 75/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0137 - mae: 0.0137\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0143 - mae: 0.0143\n", "Epoch 76/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0136 - mae: 0.0136\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0142 - mae: 0.0142\n", "Epoch 77/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0133 - mae: 0.0133\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0142 - mae: 0.0142\n", "Epoch 78/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0132 - mae: 0.0132\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0137 - mae: 0.0137\n", "Epoch 79/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0132 - mae: 0.0132\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0140 - mae: 0.0140\n", "Epoch 80/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0128 - mae: 0.0128\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0140 - mae: 0.0140\n", "Epoch 81/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0124 - mae: 0.0124\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0137 - mae: 0.0137\n", "Epoch 82/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0122 - mae: 0.0122\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0129 - mae: 0.0129\n", "Epoch 83/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0118 - mae: 0.0118\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0129 - mae: 0.0129\n", "Epoch 84/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0116 - mae: 0.0116\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0125 - mae: 0.0125\n", "Epoch 85/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0115 - mae: 0.0115\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0121 - mae: 0.0121\n", "Epoch 86/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0114 - mae: 0.0114\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0120 - mae: 0.0120\n", "Epoch 87/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0112 - mae: 0.0112\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0118 - mae: 0.0118\n", "Epoch 88/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0111 - mae: 0.0111\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0117 - mae: 0.0117\n", "Epoch 89/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0109 - mae: 0.0109\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0117 - mae: 0.0117\n", "Epoch 90/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0107 - mae: 0.0107\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0116 - mae: 0.0116\n", "Epoch 91/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0106 - mae: 0.0106\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0117 - mae: 0.0117\n", "Epoch 92/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0104 - mae: 0.0104\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0112 - mae: 0.0112\n", "Epoch 93/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0104 - mae: 0.0104\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0109 - mae: 0.0109\n", "Epoch 94/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0100 - mae: 0.0100\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0108 - mae: 0.0108\n", "Epoch 95/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0099 - mae: 0.0099\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0108 - mae: 0.0108\n", "Epoch 96/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0099 - mae: 0.0099\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0112 - mae: 0.0112\n", "Epoch 97/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0099 - mae: 0.0099\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0107 - mae: 0.0107\n", "Epoch 98/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0099 - mae: 0.0099\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0102 - mae: 0.0102\n", "Epoch 99/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0100 - mae: 0.0100\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0104 - mae: 0.0104\n", "Epoch 100/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0095 - mae: 0.0095\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0100 - mae: 0.0100\n", "Epoch 101/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0096 - mae: 0.0096\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0098 - mae: 0.0098\n", "Epoch 102/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0092 - mae: 0.0092\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0097 - mae: 0.0097\n", "Epoch 103/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0092 - mae: 0.0092\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0097 - mae: 0.0097\n", "Epoch 104/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0090 - mae: 0.0090\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0098 - mae: 0.0098\n", "Epoch 105/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0090 - mae: 0.0090\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0096 - mae: 0.0096\n", "Epoch 106/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0088 - mae: 0.0088\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0094 - mae: 0.0094\n", "Epoch 107/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0086 - mae: 0.0086\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0094 - mae: 0.0094\n", "Epoch 108/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0084 - mae: 0.0084\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0091 - mae: 0.0091\n", "Epoch 109/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0084 - mae: 0.0084\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0088 - mae: 0.0088\n", "Epoch 110/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0082 - mae: 0.0082\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0085 - mae: 0.0085\n", "Epoch 111/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0080 - mae: 0.0080\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0085 - mae: 0.0085\n", "Epoch 112/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0080 - mae: 0.0080\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0085 - mae: 0.0085\n", "Epoch 113/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0082 - mae: 0.0082\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0085 - mae: 0.0085\n", "Epoch 114/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0079 - mae: 0.0079\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0083 - mae: 0.0083\n", "Epoch 115/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0079 - mae: 0.0079\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0082 - mae: 0.0082\n", "Epoch 116/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0076 - mae: 0.0076\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0080 - mae: 0.0080\n", "Epoch 117/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0075 - mae: 0.0075\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0079 - mae: 0.0079\n", "Epoch 118/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0077 - mae: 0.0077\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0080 - mae: 0.0080\n", "Epoch 119/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0073 - mae: 0.0073\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0077 - mae: 0.0077\n", "Epoch 120/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0073 - mae: 0.0073\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0077 - mae: 0.0077\n", "Epoch 121/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0074 - mae: 0.0074\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0076 - mae: 0.0076\n", "Epoch 122/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0075 - mae: 0.0075\n", "Epoch 123/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0073 - mae: 0.0073\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0076 - mae: 0.0076\n", "Epoch 124/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0075 - mae: 0.0075\n", "Epoch 125/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0071 - mae: 0.0071\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0074 - mae: 0.0074\n", "Epoch 126/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0070 - mae: 0.0070\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0077 - mae: 0.0077\n", "Epoch 127/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0069 - mae: 0.0069\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0074 - mae: 0.0074\n", "Epoch 128/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0068 - mae: 0.0068\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0073 - mae: 0.0073\n", "Epoch 129/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0067 - mae: 0.0067\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0074 - mae: 0.0074\n", "Epoch 130/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0066 - mae: 0.0066\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0070 - mae: 0.0070\n", "Epoch 131/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0068 - mae: 0.0068\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0069 - mae: 0.0069\n", "Epoch 132/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0067 - mae: 0.0067\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0071 - mae: 0.0071\n", "Epoch 133/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0065 - mae: 0.0065\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0068 - mae: 0.0068\n", "Epoch 134/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0064 - mae: 0.0064\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0068 - mae: 0.0068\n", "Epoch 135/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0064 - mae: 0.0064\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0071 - mae: 0.0071\n", "Epoch 136/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0063 - mae: 0.0063\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0070 - mae: 0.0070\n", "Epoch 137/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0063 - mae: 0.0063\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0069 - mae: 0.0069\n", "Epoch 138/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0063 - mae: 0.0063\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0068 - mae: 0.0068\n", "Epoch 139/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0062 - mae: 0.0062\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0068 - mae: 0.0068\n", "Epoch 140/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0061 - mae: 0.0061\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0065 - mae: 0.0065\n", "Epoch 141/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0060 - mae: 0.0060\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0068 - mae: 0.0068\n", "Epoch 142/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0059 - mae: 0.0059\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0066 - mae: 0.0066\n", "Epoch 143/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0060 - mae: 0.0060\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0065 - mae: 0.0065\n", "Epoch 144/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0060 - mae: 0.0060\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0066 - mae: 0.0066\n", "Epoch 145/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0061 - mae: 0.0061\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0068 - mae: 0.0068\n", "Epoch 146/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0059 - mae: 0.0059\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0067 - mae: 0.0067\n", "Epoch 147/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0058 - mae: 0.0058\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0065 - mae: 0.0065\n", "Epoch 148/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0064 - mae: 0.0064\n", "Epoch 149/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0058 - mae: 0.0058\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0069 - mae: 0.0069\n", "Epoch 150/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0067 - mae: 0.0067\n", "Epoch 151/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0058 - mae: 0.0058\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0065 - mae: 0.0065\n", "Epoch 152/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0066 - mae: 0.0066\n", "Epoch 153/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0066 - mae: 0.0066\n", "Epoch 154/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0063 - mae: 0.0063\n", "Epoch 155/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0061 - mae: 0.0061\n", "Epoch 156/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0064 - mae: 0.0064\n", "Epoch 157/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0069 - mae: 0.0069\n", "Epoch 158/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0063 - mae: 0.0063\n", "Epoch 159/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0061 - mae: 0.0061\n", "Epoch 160/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0055 - mae: 0.0055\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0062 - mae: 0.0062\n", "Epoch 161/300\n", - "8/8 [==============================] - 0s 15ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0063 - mae: 0.0063\n", "Epoch 162/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0059 - mae: 0.0059\n", "Epoch 163/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0055 - mae: 0.0055\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0060 - mae: 0.0060\n", "Epoch 164/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0058 - mae: 0.0058\n", "Epoch 165/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0061 - mae: 0.0061\n", "Epoch 166/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0055 - mae: 0.0055\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0058 - mae: 0.0058\n", "Epoch 167/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0060 - mae: 0.0060\n", "Epoch 168/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0057 - mae: 0.0057\n", "Epoch 169/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0058 - mae: 0.0058\n", "Epoch 170/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0057 - mae: 0.0057\n", "Epoch 171/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0052 - mae: 0.0052\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0057 - mae: 0.0057\n", "Epoch 172/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 173/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0057 - mae: 0.0057\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 174/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0056 - mae: 0.0056\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 175/300\n", "8/8 [==============================] - 0s 12ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 176/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0054 - mae: 0.0054\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 177/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0051 - mae: 0.0051\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 178/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0050 - mae: 0.0050\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 179/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0050 - mae: 0.0050\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 180/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0050 - mae: 0.0050\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 181/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0048 - mae: 0.0048\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 182/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 183/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0051 - mae: 0.0051\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 184/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0048 - mae: 0.0048\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 185/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 186/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 187/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 188/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 189/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 190/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0048 - mae: 0.0048\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0054 - mae: 0.0054\n", "Epoch 191/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 192/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0048 - mae: 0.0048\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 193/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0050 - mae: 0.0050\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0051 - mae: 0.0051\n", "Epoch 194/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0048 - mae: 0.0048\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0056 - mae: 0.0056\n", "Epoch 195/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0057 - mae: 0.0057\n", "Epoch 196/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 197/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0051 - mae: 0.0051\n", "Epoch 198/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 199/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0053 - mae: 0.0053\n", "Epoch 200/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 201/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0050 - mae: 0.0050\n", "Epoch 202/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0050 - mae: 0.0050\n", "Epoch 203/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0051 - mae: 0.0051\n", "Epoch 204/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 205/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 206/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 207/300\n", - "8/8 [==============================] - 0s 16ms/step - loss: 0.0048 - mae: 0.0048\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0050 - mae: 0.0050\n", "Epoch 208/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 209/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0046 - mae: 0.0046\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 210/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 10ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 211/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 212/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 213/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 214/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 215/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 216/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 217/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 218/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 219/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 220/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 221/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0051 - mae: 0.0051\n", "Epoch 222/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0052 - mae: 0.0052\n", "Epoch 223/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 224/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 225/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0041 - mae: 0.0041\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 226/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 227/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 228/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 229/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0050 - mae: 0.0050\n", "Epoch 230/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0051 - mae: 0.0051\n", "Epoch 231/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0040 - mae: 0.0040\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0055 - mae: 0.0055\n", "Epoch 232/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0045 - mae: 0.0045\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 233/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 234/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0049 - mae: 0.0049\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 235/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0047 - mae: 0.0047\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 236/300\n", - "8/8 [==============================] - 0s 16ms/step - loss: 0.0041 - mae: 0.0041\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 237/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0040 - mae: 0.0040\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 238/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0040 - mae: 0.0040\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 239/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 240/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 241/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 242/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 243/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 244/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0041 - mae: 0.0041\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 245/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 246/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0044 - mae: 0.0044\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 247/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0039 - mae: 0.0039\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 248/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0039 - mae: 0.0039\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 249/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0037 - mae: 0.0037\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 250/300\n", - "8/8 [==============================] - 0s 15ms/step - loss: 0.0037 - mae: 0.0037\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 251/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 252/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0039 - mae: 0.0039\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0047 - mae: 0.0047\n", "Epoch 253/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0039 - mae: 0.0039\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0046 - mae: 0.0046\n", "Epoch 254/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0037 - mae: 0.0037\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 255/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0037 - mae: 0.0037\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 256/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 257/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 258/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 259/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0037 - mae: 0.0037\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 260/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0037 - mae: 0.0037\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 261/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0039 - mae: 0.0039\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 262/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 263/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0037 - mae: 0.0037\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 264/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 265/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 266/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n", "Epoch 267/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0037 - mae: 0.0037\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 268/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0035 - mae: 0.0035\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 269/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0034 - mae: 0.0034\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 270/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0035 - mae: 0.0035\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 271/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0035 - mae: 0.0035\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 272/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 273/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 274/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 275/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 276/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0035 - mae: 0.0035\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 277/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0035 - mae: 0.0035\n", + "8/8 [==============================] - 0s 13ms/step - loss: 0.0041 - mae: 0.0041\n", "Epoch 278/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 14ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 279/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 280/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 281/300\n", - "8/8 [==============================] - 0s 13ms/step - loss: 0.0038 - mae: 0.0038\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0044 - mae: 0.0044\n", "Epoch 282/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 283/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0034 - mae: 0.0034\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 284/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0033 - mae: 0.0033\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 285/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0033 - mae: 0.0033\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 286/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0035 - mae: 0.0035\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0037 - mae: 0.0037\n", "Epoch 287/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0036 - mae: 0.0036\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 288/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0035 - mae: 0.0035\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0049 - mae: 0.0049\n", "Epoch 289/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0034 - mae: 0.0034\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0048 - mae: 0.0048\n", "Epoch 290/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0032 - mae: 0.0032\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0043 - mae: 0.0043\n", "Epoch 291/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0033 - mae: 0.0033\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0039 - mae: 0.0039\n", "Epoch 292/300\n", - "8/8 [==============================] - 0s 14ms/step - loss: 0.0033 - mae: 0.0033\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 293/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0032 - mae: 0.0032\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 294/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0033 - mae: 0.0033\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0036 - mae: 0.0036\n", "Epoch 295/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0034 - mae: 0.0034\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 296/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0032 - mae: 0.0032\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 297/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0031 - mae: 0.0031\n", + "8/8 [==============================] - 0s 12ms/step - loss: 0.0038 - mae: 0.0038\n", "Epoch 298/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0031 - mae: 0.0031\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0040 - mae: 0.0040\n", "Epoch 299/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0031 - mae: 0.0031\n", + "8/8 [==============================] - 0s 11ms/step - loss: 0.0042 - mae: 0.0042\n", "Epoch 300/300\n", - "8/8 [==============================] - 0s 12ms/step - loss: 0.0032 - mae: 0.0032\n" + "8/8 [==============================] - 0s 11ms/step - loss: 0.0045 - mae: 0.0045\n" ] }, { @@ -1364,7 +1359,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -1391,17 +1386,17 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "nnp = NeuralNetPredictor()\n", - "nnp.load(\"predictors/neural_network/trained_models/experiment_nn\")" + "nnp.load(\"predictors/neural_network/trained_models/no_overlap_nn\")" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -1416,7 +1411,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -1428,16 +1423,16 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "832/832 [==============================] - 3s 4ms/step\n", - "Average ELUC of no change prescriptor on test set: -0.11382823491332882\n", - "Average change of no change prescriptor on test set: 0.00790709342038866\n" + "757/757 [==============================] - 3s 3ms/step\n", + "Average ELUC of no change prescriptor on test set: -0.026735393928184182\n", + "Average change of no change prescriptor on test set: 0.008253560043512884\n" ] } ], @@ -1449,16 +1444,16 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "832/832 [==============================] - 3s 4ms/step\n", - "Average ELUC of max change prescriptor on test set: -24.31529475182165\n", - "Average change of max change prescriptor on test set: 0.4232487870116769\n" + "757/757 [==============================] - 3s 4ms/step\n", + "Average ELUC of max change prescriptor on test set: -24.469101948751415\n", + "Average change of max change prescriptor on test set: 0.4287855154635963\n" ] } ], diff --git a/use_cases/eluc/prescriptors/train_prescriptors.ipynb b/use_cases/eluc/prescriptors/train_prescriptors.ipynb index bda724c..f503ec2 100644 --- a/use_cases/eluc/prescriptors/train_prescriptors.ipynb +++ b/use_cases/eluc/prescriptors/train_prescriptors.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -29,7 +29,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -46,13 +46,13 @@ "print(\"Initializing predictor...\")\n", "nnp = NeuralNetPredictor()\n", "print(\"Loading predictor...\")\n", - "nnp.load(\"predictors/neural_network/trained_models/experiment_nn\")\n", + "nnp.load(\"predictors/neural_network/trained_models/no_overlap_nn\")\n", "print(\"Done!\")" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -67,9 +67,9 @@ " grpc.max_receive_message_length: 52428800\n", "Ready to connect.\n", "Starting training:\n", - " experiment_id: test\n", + " experiment_id: no-overlap\n", " checkpoint_id: None\n", - " timestamp: 20240213-120921\n", + " timestamp: 20240219-114622\n", "Asking ESP for a seed generation...\n", "Sending NextPopulation request\n", "NextPopulation response received.\n", @@ -78,113 +78,108 @@ "PopulationResponse:\n", " Generation: 1\n", " Population size: 100\n", - " Checkpoint id: test/1/20240213-200922\n", - "Evaluating candidates synchronously because max_workers == 0\n", - "Metal device set to: Apple M1 Pro\n", - "\n", - "systemMemory: 16.00 GB\n", - "maxCacheSize: 5.33 GB\n", - "\n", - "1233/1233 [==============================] - 5s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 5s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", + " Checkpoint id: no-overlap/1/20240219-194622\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 4ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", "Evaluation done.\n", "Reporting evaluated population for generation 1 and asking ESP for generation 2...:\n", "Sending NextPopulation request\n", @@ -327,112 +322,140 @@ "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" ] }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ "Generation 1 data persisted.\n", "Evaluated candidates:\n", - "Id: 1_62 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_62', 'origin': '(none)'} Metrics: ['ELUC: 24.16837250217435', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 19', 'change: 0.3058792256784068', 'is_elite: False']\n", - "Id: 1_48 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_48', 'origin': '(none)'} Metrics: ['ELUC: 24.160377914680172', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 18', 'change: 0.3058522537369433', 'is_elite: False']\n", - "Id: 1_33 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_33', 'origin': '(none)'} Metrics: ['ELUC: 21.8340816775995', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 17', 'change: 0.29215513419957373', 'is_elite: False']\n", - "Id: 1_36 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_36', 'origin': '(none)'} Metrics: ['ELUC: 21.81998855865037', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 16', 'change: 0.2906404291183297', 'is_elite: False']\n", - "Id: 1_19 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_19', 'origin': '(none)'} Metrics: ['ELUC: 21.206734397175566', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.2886055412282111', 'is_elite: False']\n", - "Id: 1_34 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_34', 'origin': '(none)'} Metrics: ['ELUC: 16.227480856574246', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2592234636053112', 'is_elite: False']\n", - "Id: 1_75 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_75', 'origin': '(none)'} Metrics: ['ELUC: 16.14581851799852', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.28538044591214784', 'is_elite: False']\n", - "Id: 1_50 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_50', 'origin': '(none)'} Metrics: ['ELUC: 14.686779811768218', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.27222708250538713', 'is_elite: False']\n", - "Id: 1_28 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_28', 'origin': '(none)'} Metrics: ['ELUC: 14.54547678690605', 'NSGA-II_crowding_distance: 1.098163339336243', 'NSGA-II_rank: 13', 'change: 0.28459661160048616', 'is_elite: False']\n", - "Id: 1_99 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_99', 'origin': '(none)'} Metrics: ['ELUC: 14.468930451722956', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2528801942852757', 'is_elite: False']\n", - "Id: 1_89 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_89', 'origin': '(none)'} Metrics: ['ELUC: 13.489656978165689', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2527074760235092', 'is_elite: False']\n", - "Id: 1_90 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_90', 'origin': '(none)'} Metrics: ['ELUC: 13.28978093446168', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.23281620422563812', 'is_elite: False']\n", - "Id: 1_43 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_43', 'origin': '(none)'} Metrics: ['ELUC: 12.194331721044524', 'NSGA-II_crowding_distance: 1.2463626181992233', 'NSGA-II_rank: 14', 'change: 0.3015629215508569', 'is_elite: False']\n", - "Id: 1_58 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_58', 'origin': '(none)'} Metrics: ['ELUC: 8.103104676511496', 'NSGA-II_crowding_distance: 1.4121515717445599', 'NSGA-II_rank: 10', 'change: 0.25747244524863994', 'is_elite: False']\n", - "Id: 1_46 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_46', 'origin': '(none)'} Metrics: ['ELUC: 7.760362617737104', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2689163199899994', 'is_elite: False']\n", - "Id: 1_67 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_67', 'origin': '(none)'} Metrics: ['ELUC: 7.742237866838712', 'NSGA-II_crowding_distance: 1.8199962519253705', 'NSGA-II_rank: 12', 'change: 0.28219094213592955', 'is_elite: False']\n", - "Id: 1_60 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_60', 'origin': '(none)'} Metrics: ['ELUC: 6.276140666014528', 'NSGA-II_crowding_distance: 1.9729368853996552', 'NSGA-II_rank: 15', 'change: 0.3125575026661681', 'is_elite: False']\n", - "Id: 1_74 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_74', 'origin': '(none)'} Metrics: ['ELUC: 5.175379443608467', 'NSGA-II_crowding_distance: 1.6293657735282299', 'NSGA-II_rank: 9', 'change: 0.2563338304410789', 'is_elite: False']\n", - "Id: 1_51 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_51', 'origin': '(none)'} Metrics: ['ELUC: 4.022880649890961', 'NSGA-II_crowding_distance: 1.2394291000432813', 'NSGA-II_rank: 14', 'change: 0.3042894254562674', 'is_elite: False']\n", - "Id: 1_15 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_15', 'origin': '(none)'} Metrics: ['ELUC: 4.011335714663428', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.22676464370277882', 'is_elite: False']\n", - "Id: 1_97 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_97', 'origin': '(none)'} Metrics: ['ELUC: 3.64209418955004', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.26487270902292165', 'is_elite: False']\n", - "Id: 1_13 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_13', 'origin': '(none)'} Metrics: ['ELUC: 3.5779167009948085', 'NSGA-II_crowding_distance: 1.3836497419486453', 'NSGA-II_rank: 13', 'change: 0.2951768808281396', 'is_elite: False']\n", - "Id: 1_76 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_76', 'origin': '(none)'} Metrics: ['ELUC: 3.17294914362004', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24561578434953166', 'is_elite: False']\n", - "Id: 1_63 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_63', 'origin': '(none)'} Metrics: ['ELUC: 3.011222273559701', 'NSGA-II_crowding_distance: 1.2395199988876495', 'NSGA-II_rank: 10', 'change: 0.2641199960152691', 'is_elite: False']\n", - "Id: 1_64 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_64', 'origin': '(none)'} Metrics: ['ELUC: 2.681652585814098', 'NSGA-II_crowding_distance: 1.1704961237120017', 'NSGA-II_rank: 9', 'change: 0.2636047301589581', 'is_elite: False']\n", - "Id: 1_83 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_83', 'origin': '(none)'} Metrics: ['ELUC: 2.6010482073800945', 'NSGA-II_crowding_distance: 0.6343334534033878', 'NSGA-II_rank: 3', 'change: 0.23664220099610356', 'is_elite: False']\n", - "Id: 1_4 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_4', 'origin': '(none)'} Metrics: ['ELUC: 2.560974368320742', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.24316776013445646', 'is_elite: False']\n", - "Id: 1_77 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_77', 'origin': '(none)'} Metrics: ['ELUC: 2.455070202705463', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25217118412652817', 'is_elite: False']\n", - "Id: 1_41 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_41', 'origin': '(none)'} Metrics: ['ELUC: 2.310102889976668', 'NSGA-II_crowding_distance: 0.8360749899106681', 'NSGA-II_rank: 15', 'change: 0.349874774646134', 'is_elite: False']\n", - "Id: 1_6 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_6', 'origin': '(none)'} Metrics: ['ELUC: 2.0409874431454655', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 16', 'change: 0.3527712988545227', 'is_elite: False']\n", - "Id: 1_9 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_9', 'origin': '(none)'} Metrics: ['ELUC: 2.0409874431454655', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 16', 'change: 0.3527712988545227', 'is_elite: False']\n", - "Id: 1_27 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_27', 'origin': '(none)'} Metrics: ['ELUC: 2.0409874431454655', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 16', 'change: 0.3527712988545227', 'is_elite: False']\n", - "Id: 1_12 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_12', 'origin': '(none)'} Metrics: ['ELUC: 1.9951530835576219', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.35053552843580854', 'is_elite: False']\n", - "Id: 1_71 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_71', 'origin': '(none)'} Metrics: ['ELUC: 1.747915293719701', 'NSGA-II_crowding_distance: 0.5129371187328966', 'NSGA-II_rank: 7', 'change: 0.25011323997937396', 'is_elite: False']\n", - "Id: 1_68 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_68', 'origin': '(none)'} Metrics: ['ELUC: 1.7475455431224656', 'NSGA-II_crowding_distance: 1.076603192707598', 'NSGA-II_rank: 7', 'change: 0.2550400918497024', 'is_elite: False']\n", - "Id: 1_30 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_30', 'origin': '(none)'} Metrics: ['ELUC: 1.5755472293780193', 'NSGA-II_crowding_distance: 0.7536373818007768', 'NSGA-II_rank: 14', 'change: 0.32429088014507657', 'is_elite: False']\n", - "Id: 1_2 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_2', 'origin': '(none)'} Metrics: ['ELUC: 0.8646508105982956', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.32711868970859537', 'is_elite: False']\n", - "Id: 1_20 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_20', 'origin': '(none)'} Metrics: ['ELUC: 0.35835904787961637', 'NSGA-II_crowding_distance: 0.9018366606637569', 'NSGA-II_rank: 13', 'change: 0.3126328503055798', 'is_elite: False']\n", - "Id: 1_35 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_35', 'origin': '(none)'} Metrics: ['ELUC: 0.164752157337882', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.23998292679082303', 'is_elite: False']\n", - "Id: 1_44 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_44', 'origin': '(none)'} Metrics: ['ELUC: 0.050031465149887204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3398871539036199', 'is_elite: False']\n", - "Id: 1_61 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_61', 'origin': '(none)'} Metrics: ['ELUC: 0.012517319378487159', 'NSGA-II_crowding_distance: 0.04239364358735292', 'NSGA-II_rank: 5', 'change: 0.24050026731696617', 'is_elite: False']\n", - "Id: 1_70 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_70', 'origin': '(none)'} Metrics: ['ELUC: 0.012517319378487159', 'NSGA-II_crowding_distance: 0.080181678416793', 'NSGA-II_rank: 5', 'change: 0.24050026731696617', 'is_elite: False']\n", - "Id: 1_47 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_47', 'origin': '(none)'} Metrics: ['ELUC: 0.010276717188162157', 'NSGA-II_crowding_distance: 0.7773482440794071', 'NSGA-II_rank: 4', 'change: 0.2396959800888411', 'is_elite: False']\n", - "Id: 1_14 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_14', 'origin': '(none)'} Metrics: ['ELUC: -0.21727721487948554', 'NSGA-II_crowding_distance: 1.4820604122540768', 'NSGA-II_rank: 12', 'change: 0.2933858456780706', 'is_elite: False']\n", - "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.2227250343797053', 'NSGA-II_crowding_distance: 1.2964442765422464', 'NSGA-II_rank: 6', 'change: 0.2499296406395586', 'is_elite: False']\n", - "Id: 1_7 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_7', 'origin': '(none)'} Metrics: ['ELUC: -0.2888341221702056', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.22668387310715232', 'is_elite: False']\n", - "Id: 1_55 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_55', 'origin': '(none)'} Metrics: ['ELUC: -0.30853011692439725', 'NSGA-II_crowding_distance: 0.13640301787301395', 'NSGA-II_rank: 5', 'change: 0.24467631242640347', 'is_elite: False']\n", - "Id: 1_52 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_52', 'origin': '(none)'} Metrics: ['ELUC: -0.39568227009633317', 'NSGA-II_crowding_distance: 0.4452586754965745', 'NSGA-II_rank: 5', 'change: 0.24655573347421406', 'is_elite: False']\n", - "Id: 1_79 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_79', 'origin': '(none)'} Metrics: ['ELUC: -0.7273529288078069', 'NSGA-II_crowding_distance: 0.19444635911150895', 'NSGA-II_rank: 4', 'change: 0.24039441127927505', 'is_elite: False']\n", - "Id: 1_87 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_87', 'origin': '(none)'} Metrics: ['ELUC: -0.8255930035433484', 'NSGA-II_crowding_distance: 0.5878484282554401', 'NSGA-II_rank: 10', 'change: 0.2684209967120516', 'is_elite: False']\n", - "Id: 1_95 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_95', 'origin': '(none)'} Metrics: ['ELUC: -0.851637702509403', 'NSGA-II_crowding_distance: 0.4588235537554882', 'NSGA-II_rank: 4', 'change: 0.24658760609192684', 'is_elite: False']\n", - "Id: 1_57 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_57', 'origin': '(none)'} Metrics: ['ELUC: -1.4209369638858649', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.29464405239417896', 'is_elite: False']\n", - "Id: 1_84 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_84', 'origin': '(none)'} Metrics: ['ELUC: -1.5048084307792846', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27793805552368134', 'is_elite: False']\n", - "Id: 1_24 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_24', 'origin': '(none)'} Metrics: ['ELUC: -1.9389253057812874', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2686256244829513', 'is_elite: False']\n", - "Id: 1_73 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_73', 'origin': '(none)'} Metrics: ['ELUC: -2.1540166709288586', 'NSGA-II_crowding_distance: 0.7558443418442955', 'NSGA-II_rank: 3', 'change: 0.2380852701101791', 'is_elite: False']\n", - "Id: 1_5 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_5', 'origin': '(none)'} Metrics: ['ELUC: -2.9155698509918704', 'NSGA-II_crowding_distance: 0.6237959196104762', 'NSGA-II_rank: 5', 'change: 0.2554856188132912', 'is_elite: False']\n", - "Id: 1_45 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_45', 'origin': '(none)'} Metrics: ['ELUC: -2.931542935674633', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2639279710538597', 'is_elite: False']\n", - "Id: 1_26 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_26', 'origin': '(none)'} Metrics: ['ELUC: -3.150228623763059', 'NSGA-II_crowding_distance: 0.519859631046565', 'NSGA-II_rank: 2', 'change: 0.2349909360761232', 'is_elite: False']\n", - "Id: 1_92 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_92', 'origin': '(none)'} Metrics: ['ELUC: -3.2790619157289447', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2603260280264673', 'is_elite: False']\n", - "Id: 1_98 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_98', 'origin': '(none)'} Metrics: ['ELUC: -3.364414440894428', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.283258287664256', 'is_elite: False']\n", - "Id: 1_91 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_91', 'origin': '(none)'} Metrics: ['ELUC: -3.3746813728077396', 'NSGA-II_crowding_distance: 1.4870628812671034', 'NSGA-II_rank: 7', 'change: 0.2597757471736627', 'is_elite: False']\n", - "Id: 1_29 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_29', 'origin': '(none)'} Metrics: ['ELUC: -3.4685336610348103', 'NSGA-II_crowding_distance: 0.6082626262418325', 'NSGA-II_rank: 3', 'change: 0.25477622192675226', 'is_elite: False']\n", - "Id: 1_93 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_93', 'origin': '(none)'} Metrics: ['ELUC: -3.475235890963808', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2771845988197979', 'is_elite: False']\n", - "Id: 1_88 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_88', 'origin': '(none)'} Metrics: ['ELUC: -3.4898379123337464', 'NSGA-II_crowding_distance: 1.4038715842536253', 'NSGA-II_rank: 6', 'change: 0.25789577044235984', 'is_elite: False']\n", - "Id: 1_78 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_78', 'origin': '(none)'} Metrics: ['ELUC: -3.515961585542842', 'NSGA-II_crowding_distance: 0.4061901550914813', 'NSGA-II_rank: 4', 'change: 0.25523011236673177', 'is_elite: False']\n", - "Id: 1_49 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_49', 'origin': '(none)'} Metrics: ['ELUC: -3.5621183479575067', 'NSGA-II_crowding_distance: 0.4022493319161961', 'NSGA-II_rank: 2', 'change: 0.24444970115258685', 'is_elite: False']\n", - "Id: 1_53 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_53', 'origin': '(none)'} Metrics: ['ELUC: -3.67653466206307', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.28829371745985455', 'is_elite: False']\n", - "Id: 1_42 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_42', 'origin': '(none)'} Metrics: ['ELUC: -4.696959015355664', 'NSGA-II_crowding_distance: 1.097419546013398', 'NSGA-II_rank: 5', 'change: 0.25713901778266246', 'is_elite: False']\n", - "Id: 1_22 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_22', 'origin': '(none)'} Metrics: ['ELUC: -4.749842160281162', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.22310495691341786', 'is_elite: True']\n", - "Id: 1_72 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_72', 'origin': '(none)'} Metrics: ['ELUC: -5.105024067677041', 'NSGA-II_crowding_distance: 0.4773744263764076', 'NSGA-II_rank: 4', 'change: 0.2563496323271655', 'is_elite: False']\n", - "Id: 1_21 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_21', 'origin': '(none)'} Metrics: ['ELUC: -5.208242310623751', 'NSGA-II_crowding_distance: 0.3401183099389573', 'NSGA-II_rank: 2', 'change: 0.25098300615583374', 'is_elite: False']\n", - "Id: 1_59 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_59', 'origin': '(none)'} Metrics: ['ELUC: -6.341352951385072', 'NSGA-II_crowding_distance: 0.365411795155298', 'NSGA-II_rank: 3', 'change: 0.255214673376636', 'is_elite: False']\n", - "Id: 1_38 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_38', 'origin': '(none)'} Metrics: ['ELUC: -6.477469844409696', 'NSGA-II_crowding_distance: 0.312209556214807', 'NSGA-II_rank: 2', 'change: 0.25241295493997634', 'is_elite: False']\n", - "Id: 1_80 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_80', 'origin': '(none)'} Metrics: ['ELUC: -6.520730586577443', 'NSGA-II_crowding_distance: 0.44658529336441205', 'NSGA-II_rank: 1', 'change: 0.23723970522187782', 'is_elite: True']\n", - "Id: 1_82 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_82', 'origin': '(none)'} Metrics: ['ELUC: -6.833186416126583', 'NSGA-II_crowding_distance: 0.47571819239515356', 'NSGA-II_rank: 4', 'change: 0.2698799313750465', 'is_elite: False']\n", - "Id: 1_40 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_40', 'origin': '(none)'} Metrics: ['ELUC: -7.110222850313951', 'NSGA-II_crowding_distance: 0.22012437381176264', 'NSGA-II_rank: 1', 'change: 0.24412666188444093', 'is_elite: True']\n", - "Id: 1_31 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_31', 'origin': '(none)'} Metrics: ['ELUC: -7.505625353213676', 'NSGA-II_crowding_distance: 1.1872006193359272', 'NSGA-II_rank: 5', 'change: 0.29502651805695573', 'is_elite: False']\n", - "Id: 1_18 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_18', 'origin': '(none)'} Metrics: ['ELUC: -8.084301976530588', 'NSGA-II_crowding_distance: 0.11300735601266435', 'NSGA-II_rank: 4', 'change: 0.2715653705470806', 'is_elite: False']\n", - "Id: 1_23 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_23', 'origin': '(none)'} Metrics: ['ELUC: -8.12467078249326', 'NSGA-II_crowding_distance: 0.23318769381319776', 'NSGA-II_rank: 1', 'change: 0.2448984513869198', 'is_elite: True']\n", - "Id: 1_3 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_3', 'origin': '(none)'} Metrics: ['ELUC: -8.209504292664239', 'NSGA-II_crowding_distance: 0.03941012892419736', 'NSGA-II_rank: 4', 'change: 0.2722312695170447', 'is_elite: False']\n", - "Id: 1_16 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_16', 'origin': '(none)'} Metrics: ['ELUC: -8.227040721925775', 'NSGA-II_crowding_distance: 0.05277319057294641', 'NSGA-II_rank: 4', 'change: 0.27302252546627814', 'is_elite: False']\n", - "Id: 1_8 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_8', 'origin': '(none)'} Metrics: ['ELUC: -8.417574766783341', 'NSGA-II_crowding_distance: 0.15463208816854895', 'NSGA-II_rank: 4', 'change: 0.2741505212965655', 'is_elite: False']\n", - "Id: 1_96 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_96', 'origin': '(none)'} Metrics: ['ELUC: -8.656624906941426', 'NSGA-II_crowding_distance: 0.6491913924181971', 'NSGA-II_rank: 3', 'change: 0.255344071181877', 'is_elite: False']\n", - "Id: 1_11 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_11', 'origin': '(none)'} Metrics: ['ELUC: -8.994615048092896', 'NSGA-II_crowding_distance: 0.3347464564858816', 'NSGA-II_rank: 5', 'change: 0.30460885547172883', 'is_elite: False']\n", - "Id: 1_66 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_66', 'origin': '(none)'} Metrics: ['ELUC: -9.074297745245556', 'NSGA-II_crowding_distance: 0.25148646748048264', 'NSGA-II_rank: 2', 'change: 0.25266455434506097', 'is_elite: False']\n", - "Id: 1_39 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_39', 'origin': '(none)'} Metrics: ['ELUC: -9.144657479263008', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.30540855668247086', 'is_elite: False']\n", - "Id: 1_86 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_86', 'origin': '(none)'} Metrics: ['ELUC: -9.39189814617824', 'NSGA-II_crowding_distance: 0.1787127283276076', 'NSGA-II_rank: 2', 'change: 0.2547120191182602', 'is_elite: False']\n", - "Id: 1_94 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_94', 'origin': '(none)'} Metrics: ['ELUC: -9.742974149774458', 'NSGA-II_crowding_distance: 0.35862818925692125', 'NSGA-II_rank: 1', 'change: 0.24651100589774422', 'is_elite: True']\n", - "Id: 1_37 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_37', 'origin': '(none)'} Metrics: ['ELUC: -9.902150012807782', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.27663322214642416', 'is_elite: False']\n", - "Id: 1_81 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_81', 'origin': '(none)'} Metrics: ['ELUC: -10.476679650565861', 'NSGA-II_crowding_distance: 0.5966637102374339', 'NSGA-II_rank: 3', 'change: 0.27471089920463004', 'is_elite: False']\n", - "Id: 1_85 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_85', 'origin': '(none)'} Metrics: ['ELUC: -10.613760713717365', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.27996965753031977', 'is_elite: False']\n", - "Id: 1_54 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_54', 'origin': '(none)'} Metrics: ['ELUC: -10.94191353696159', 'NSGA-II_crowding_distance: 0.3662555320740146', 'NSGA-II_rank: 2', 'change: 0.25526064127447917', 'is_elite: False']\n", - "Id: 1_17 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_17', 'origin': '(none)'} Metrics: ['ELUC: -11.144308180976543', 'NSGA-II_crowding_distance: 0.3214005412602207', 'NSGA-II_rank: 2', 'change: 0.26984754771287206', 'is_elite: False']\n", - "Id: 1_69 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_69', 'origin': '(none)'} Metrics: ['ELUC: -11.230568070901706', 'NSGA-II_crowding_distance: 0.5222800594599805', 'NSGA-II_rank: 2', 'change: 0.2744508829616873', 'is_elite: False']\n", - "Id: 1_32 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_32', 'origin': '(none)'} Metrics: ['ELUC: -11.261973725541184', 'NSGA-II_crowding_distance: 0.3841090012158862', 'NSGA-II_rank: 1', 'change: 0.25415983088095273', 'is_elite: True']\n", - "Id: 1_56 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_56', 'origin': '(none)'} Metrics: ['ELUC: -12.434823816828384', 'NSGA-II_crowding_distance: 0.6256350145740086', 'NSGA-II_rank: 1', 'change: 0.2605316124824141', 'is_elite: True']\n", - "Id: 1_100 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_100', 'origin': '(none)'} Metrics: ['ELUC: -13.810416881607777', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.29064007781330314', 'is_elite: False']\n", - "Id: 1_65 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_65', 'origin': '(none)'} Metrics: ['ELUC: -15.424949134878572', 'NSGA-II_crowding_distance: 0.9136398314287504', 'NSGA-II_rank: 1', 'change: 0.2783556836638049', 'is_elite: True']\n", - "Id: 1_10 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_10', 'origin': '(none)'} Metrics: ['ELUC: -17.580724861049067', 'NSGA-II_crowding_distance: 0.4811481889215347', 'NSGA-II_rank: 1', 'change: 0.3015936736594201', 'is_elite: True']\n", - "Id: 1_25 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_25', 'origin': '(none)'} Metrics: ['ELUC: -17.706449051990806', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.30260931794172286', 'is_elite: True']\n", + "Id: 1_34 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_34', 'origin': '(none)'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 16', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 1_3 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_3', 'origin': '(none)'} Metrics: ['ELUC: 23.83169073562653', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.303772775966599', 'is_elite: False']\n", + "Id: 1_57 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_57', 'origin': '(none)'} Metrics: ['ELUC: 23.228611004084033', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.30323486986263515', 'is_elite: False']\n", + "Id: 1_15 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_15', 'origin': '(none)'} Metrics: ['ELUC: 22.367188626420088', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.29449770174568296', 'is_elite: False']\n", + "Id: 1_79 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_79', 'origin': '(none)'} Metrics: ['ELUC: 18.889134071384188', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.27474885052896775', 'is_elite: False']\n", + "Id: 1_8 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_8', 'origin': '(none)'} Metrics: ['ELUC: 18.678942717268807', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2727622170091319', 'is_elite: False']\n", + "Id: 1_23 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_23', 'origin': '(none)'} Metrics: ['ELUC: 16.36660477063263', 'NSGA-II_crowding_distance: 0.3114418640332852', 'NSGA-II_rank: 11', 'change: 0.2728963458116424', 'is_elite: False']\n", + "Id: 1_32 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_32', 'origin': '(none)'} Metrics: ['ELUC: 15.90370589612425', 'NSGA-II_crowding_distance: 0.5908392064951156', 'NSGA-II_rank: 12', 'change: 0.28667848722773387', 'is_elite: False']\n", + "Id: 1_50 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_50', 'origin': '(none)'} Metrics: ['ELUC: 14.662151701876022', 'NSGA-II_crowding_distance: 0.6613051374124709', 'NSGA-II_rank: 12', 'change: 0.289221201579957', 'is_elite: False']\n", + "Id: 1_89 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_89', 'origin': '(none)'} Metrics: ['ELUC: 14.581134560193762', 'NSGA-II_crowding_distance: 0.7223234894615402', 'NSGA-II_rank: 11', 'change: 0.2766761865687803', 'is_elite: False']\n", + "Id: 1_21 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_21', 'origin': '(none)'} Metrics: ['ELUC: 10.90422414566142', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26506992202584573', 'is_elite: False']\n", + "Id: 1_30 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_30', 'origin': '(none)'} Metrics: ['ELUC: 8.440608506741016', 'NSGA-II_crowding_distance: 0.4676711450502461', 'NSGA-II_rank: 10', 'change: 0.2664254835188661', 'is_elite: False']\n", + "Id: 1_62 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_62', 'origin': '(none)'} Metrics: ['ELUC: 8.217087876986334', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.22990696821025067', 'is_elite: False']\n", + "Id: 1_92 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_92', 'origin': '(none)'} Metrics: ['ELUC: 7.820232422652064', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.258407635270379', 'is_elite: False']\n", + "Id: 1_87 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_87', 'origin': '(none)'} Metrics: ['ELUC: 7.213715905293946', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 13', 'change: 0.3068876977693688', 'is_elite: False']\n", + "Id: 1_46 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_46', 'origin': '(none)'} Metrics: ['ELUC: 6.782007575386292', 'NSGA-II_crowding_distance: 1.4091607935048842', 'NSGA-II_rank: 12', 'change: 0.2920928249836899', 'is_elite: False']\n", + "Id: 1_5 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_5', 'origin': '(none)'} Metrics: ['ELUC: 6.653671909894162', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25301901587612124', 'is_elite: False']\n", + "Id: 1_45 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_45', 'origin': '(none)'} Metrics: ['ELUC: 6.0613646004283535', 'NSGA-II_crowding_distance: 0.6204051856454046', 'NSGA-II_rank: 10', 'change: 0.26650197661363134', 'is_elite: False']\n", + "Id: 1_12 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_12', 'origin': '(none)'} Metrics: ['ELUC: 5.418981739617518', 'NSGA-II_crowding_distance: 1.6262707840136565', 'NSGA-II_rank: 11', 'change: 0.27854798623074273', 'is_elite: False']\n", + "Id: 1_54 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_54', 'origin': '(none)'} Metrics: ['ELUC: 5.215653486819887', 'NSGA-II_crowding_distance: 0.5053197313807041', 'NSGA-II_rank: 8', 'change: 0.2653339653850397', 'is_elite: False']\n", + "Id: 1_40 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_40', 'origin': '(none)'} Metrics: ['ELUC: 4.981758964007699', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2509817052895414', 'is_elite: False']\n", + "Id: 1_71 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_71', 'origin': '(none)'} Metrics: ['ELUC: 4.405003371691374', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.24088681182077668', 'is_elite: False']\n", + "Id: 1_16 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_16', 'origin': '(none)'} Metrics: ['ELUC: 4.36437836758972', 'NSGA-II_crowding_distance: 0.31723246608936384', 'NSGA-II_rank: 5', 'change: 0.2431197416501074', 'is_elite: False']\n", + "Id: 1_31 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_31', 'origin': '(none)'} Metrics: ['ELUC: 4.340979229980395', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.25003932589631567', 'is_elite: False']\n", + "Id: 1_9 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_9', 'origin': '(none)'} Metrics: ['ELUC: 4.057002364464704', 'NSGA-II_crowding_distance: 0.3572419752958411', 'NSGA-II_rank: 7', 'change: 0.25860791048270315', 'is_elite: False']\n", + "Id: 1_74 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_74', 'origin': '(none)'} Metrics: ['ELUC: 3.664403095789867', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.22857541769168677', 'is_elite: False']\n", + "Id: 1_43 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_43', 'origin': '(none)'} Metrics: ['ELUC: 3.4848109781069434', 'NSGA-II_crowding_distance: 0.34574177635148895', 'NSGA-II_rank: 8', 'change: 0.2656349949201772', 'is_elite: False']\n", + "Id: 1_44 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_44', 'origin': '(none)'} Metrics: ['ELUC: 3.0488307155223824', 'NSGA-II_crowding_distance: 0.7388085013495977', 'NSGA-II_rank: 7', 'change: 0.26084989472001224', 'is_elite: False']\n", + "Id: 1_93 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_93', 'origin': '(none)'} Metrics: ['ELUC: 2.562655726186546', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 15', 'change: 0.35138126876447806', 'is_elite: False']\n", + "Id: 1_39 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_39', 'origin': '(none)'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 1_42 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_42', 'origin': '(none)'} Metrics: ['ELUC: 2.2752645539701164', 'NSGA-II_crowding_distance: 0.5494944776759063', 'NSGA-II_rank: 5', 'change: 0.2452632933379485', 'is_elite: False']\n", + "Id: 1_19 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_19', 'origin': '(none)'} Metrics: ['ELUC: 2.222296736071684', 'NSGA-II_crowding_distance: 1.5323288549497538', 'NSGA-II_rank: 10', 'change: 0.2691540634964684', 'is_elite: False']\n", + "Id: 1_84 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_84', 'origin': '(none)'} Metrics: ['ELUC: 2.1369091786250354', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.350196896440753', 'is_elite: False']\n", + "Id: 1_37 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_37', 'origin': '(none)'} Metrics: ['ELUC: 1.9418354545421355', 'NSGA-II_crowding_distance: 1.5245379245693265', 'NSGA-II_rank: 9', 'change: 0.26641192518996265', 'is_elite: False']\n", + "Id: 1_58 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_58', 'origin': '(none)'} Metrics: ['ELUC: 1.9042401078349245', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.33578393192533906', 'is_elite: False']\n", + "Id: 1_73 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_73', 'origin': '(none)'} Metrics: ['ELUC: 1.7622781750639236', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3168153747961675', 'is_elite: False']\n", + "Id: 1_55 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_55', 'origin': '(none)'} Metrics: ['ELUC: 1.7252420968222033', 'NSGA-II_crowding_distance: 0.3843591933650251', 'NSGA-II_rank: 8', 'change: 0.2661459265366891', 'is_elite: False']\n", + "Id: 1_11 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_11', 'origin': '(none)'} Metrics: ['ELUC: 1.5393264396425093', 'NSGA-II_crowding_distance: 0.6894686832973789', 'NSGA-II_rank: 3', 'change: 0.23917237382548595', 'is_elite: False']\n", + "Id: 1_76 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_76', 'origin': '(none)'} Metrics: ['ELUC: 1.2664484928589435', 'NSGA-II_crowding_distance: 0.5192567456817543', 'NSGA-II_rank: 8', 'change: 0.276366263847326', 'is_elite: False']\n", + "Id: 1_10 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_10', 'origin': '(none)'} Metrics: ['ELUC: 1.1475681227857635', 'NSGA-II_crowding_distance: 0.8262615535989929', 'NSGA-II_rank: 5', 'change: 0.2524033390256032', 'is_elite: False']\n", + "Id: 1_96 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_96', 'origin': '(none)'} Metrics: ['ELUC: 0.7053206585995256', 'NSGA-II_crowding_distance: 1.149304544447935', 'NSGA-II_rank: 11', 'change: 0.3149648011045017', 'is_elite: False']\n", + "Id: 1_80 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_80', 'origin': '(none)'} Metrics: ['ELUC: 0.531602932539852', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2279278204005719', 'is_elite: False']\n", + "Id: 1_7 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_7', 'origin': '(none)'} Metrics: ['ELUC: 0.22587574400713933', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3165547092896193', 'is_elite: False']\n", + "Id: 1_47 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_47', 'origin': '(none)'} Metrics: ['ELUC: 0.15347973250038036', 'NSGA-II_crowding_distance: 0.21118521089616607', 'NSGA-II_rank: 2', 'change: 0.22902308871360716', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 1_27 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_27', 'origin': '(none)'} Metrics: ['ELUC: -0.21265033943427036', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3097661074408854', 'is_elite: False']\n", + "Id: 1_49 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_49', 'origin': '(none)'} Metrics: ['ELUC: -0.43887438417570523', 'NSGA-II_crowding_distance: 1.3614679561884835', 'NSGA-II_rank: 4', 'change: 0.23979064739391687', 'is_elite: False']\n", + "Id: 1_75 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_75', 'origin': '(none)'} Metrics: ['ELUC: -0.5624860130756664', 'NSGA-II_crowding_distance: 0.2777425371757243', 'NSGA-II_rank: 2', 'change: 0.2387220594944199', 'is_elite: False']\n", + "Id: 1_14 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_14', 'origin': '(none)'} Metrics: ['ELUC: -0.5941013652776992', 'NSGA-II_crowding_distance: 1.0460810941077823', 'NSGA-II_rank: 1', 'change: 0.22774267952277133', 'is_elite: True']\n", + "Id: 1_22 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_22', 'origin': '(none)'} Metrics: ['ELUC: -0.6152670079513743', 'NSGA-II_crowding_distance: 0.9708949231383447', 'NSGA-II_rank: 6', 'change: 0.2569700795121477', 'is_elite: False']\n", + "Id: 1_69 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_69', 'origin': '(none)'} Metrics: ['ELUC: -0.7623357193762051', 'NSGA-II_crowding_distance: 0.7718473943622386', 'NSGA-II_rank: 9', 'change: 0.284635508564864', 'is_elite: False']\n", + "Id: 1_26 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_26', 'origin': '(none)'} Metrics: ['ELUC: -1.2710339565301931', 'NSGA-II_crowding_distance: 0.3876444846427737', 'NSGA-II_rank: 9', 'change: 0.28464817828703937', 'is_elite: False']\n", + "Id: 1_64 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_64', 'origin': '(none)'} Metrics: ['ELUC: -1.3881871349194586', 'NSGA-II_crowding_distance: 0.42194322862306305', 'NSGA-II_rank: 9', 'change: 0.29811878142313636', 'is_elite: False']\n", + "Id: 1_29 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_29', 'origin': '(none)'} Metrics: ['ELUC: -1.7388692425908208', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30025870684365985', 'is_elite: False']\n", + "Id: 1_66 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_66', 'origin': '(none)'} Metrics: ['ELUC: -1.8843042997298278', 'NSGA-II_crowding_distance: 0.5688963381419189', 'NSGA-II_rank: 8', 'change: 0.2770205064839034', 'is_elite: False']\n", + "Id: 1_91 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_91', 'origin': '(none)'} Metrics: ['ELUC: -2.1540508156137887', 'NSGA-II_crowding_distance: 0.19172388505918064', 'NSGA-II_rank: 2', 'change: 0.2396992268768592', 'is_elite: False']\n", + "Id: 1_81 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_81', 'origin': '(none)'} Metrics: ['ELUC: -2.229355167756119', 'NSGA-II_crowding_distance: 0.7135472234675164', 'NSGA-II_rank: 7', 'change: 0.26493501929693786', 'is_elite: False']\n", + "Id: 1_38 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_38', 'origin': '(none)'} Metrics: ['ELUC: -3.0250639393456726', 'NSGA-II_crowding_distance: 0.799492435317811', 'NSGA-II_rank: 8', 'change: 0.2862879637573113', 'is_elite: False']\n", + "Id: 1_24 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_24', 'origin': '(none)'} Metrics: ['ELUC: -3.039698080101398', 'NSGA-II_crowding_distance: 0.4807796983380321', 'NSGA-II_rank: 6', 'change: 0.26473917100364674', 'is_elite: False']\n", + "Id: 1_33 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_33', 'origin': '(none)'} Metrics: ['ELUC: -3.0606326388925225', 'NSGA-II_crowding_distance: 1.0425846944560733', 'NSGA-II_rank: 7', 'change: 0.26672659441577684', 'is_elite: False']\n", + "Id: 1_86 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_86', 'origin': '(none)'} Metrics: ['ELUC: -3.160135378012214', 'NSGA-II_crowding_distance: 0.6712704954657711', 'NSGA-II_rank: 3', 'change: 0.23974591056826494', 'is_elite: False']\n", + "Id: 1_94 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_94', 'origin': '(none)'} Metrics: ['ELUC: -3.577945222295828', 'NSGA-II_crowding_distance: 0.7724059354798027', 'NSGA-II_rank: 5', 'change: 0.2555583952282739', 'is_elite: False']\n", + "Id: 1_13 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_13', 'origin': '(none)'} Metrics: ['ELUC: -3.731589741782766', 'NSGA-II_crowding_distance: 0.3224744282544435', 'NSGA-II_rank: 2', 'change: 0.23970421864811084', 'is_elite: False']\n", + "Id: 1_41 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_41', 'origin': '(none)'} Metrics: ['ELUC: -3.838854943908556', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3150723924163906', 'is_elite: False']\n", + "Id: 1_51 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_51', 'origin': '(none)'} Metrics: ['ELUC: -3.9739010117267837', 'NSGA-II_crowding_distance: 0.37561405464169123', 'NSGA-II_rank: 6', 'change: 0.26591689441177413', 'is_elite: False']\n", + "Id: 1_18 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_18', 'origin': '(none)'} Metrics: ['ELUC: -4.231031808781335', 'NSGA-II_crowding_distance: 0.8565059803116434', 'NSGA-II_rank: 5', 'change: 0.262363130471044', 'is_elite: False']\n", + "Id: 1_60 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_60', 'origin': '(none)'} Metrics: ['ELUC: -4.301738389168228', 'NSGA-II_crowding_distance: 0.5575120188434577', 'NSGA-II_rank: 6', 'change: 0.2793958856447297', 'is_elite: False']\n", + "Id: 1_67 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_67', 'origin': '(none)'} Metrics: ['ELUC: -4.460547353395721', 'NSGA-II_crowding_distance: 1.0109020997187337', 'NSGA-II_rank: 4', 'change: 0.25415178432280255', 'is_elite: False']\n", + "Id: 1_48 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_48', 'origin': '(none)'} Metrics: ['ELUC: -4.6449920743777255', 'NSGA-II_crowding_distance: 0.5367273738566898', 'NSGA-II_rank: 3', 'change: 0.25277819744885144', 'is_elite: False']\n", + "Id: 1_65 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_65', 'origin': '(none)'} Metrics: ['ELUC: -4.852359001151172', 'NSGA-II_crowding_distance: 0.37947956470700317', 'NSGA-II_rank: 1', 'change: 0.234700850215592', 'is_elite: True']\n", + "Id: 1_61 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_61', 'origin': '(none)'} Metrics: ['ELUC: -4.91908093097676', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.31189146911013', 'is_elite: False']\n", + "Id: 1_98 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_98', 'origin': '(none)'} Metrics: ['ELUC: -4.982741970783642', 'NSGA-II_crowding_distance: 0.5832359930913251', 'NSGA-II_rank: 4', 'change: 0.2717986722442674', 'is_elite: False']\n", + "Id: 1_6 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_6', 'origin': '(none)'} Metrics: ['ELUC: -4.988980121934541', 'NSGA-II_crowding_distance: 0.26888453031402565', 'NSGA-II_rank: 2', 'change: 0.2514636163006749', 'is_elite: False']\n", + "Id: 1_78 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_78', 'origin': '(none)'} Metrics: ['ELUC: -5.267005690768501', 'NSGA-II_crowding_distance: 0.10006603429234467', 'NSGA-II_rank: 2', 'change: 0.2528705476114906', 'is_elite: False']\n", + "Id: 1_99 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_99', 'origin': '(none)'} Metrics: ['ELUC: -5.803154441596001', 'NSGA-II_crowding_distance: 0.6534910222199641', 'NSGA-II_rank: 6', 'change: 0.2879188224266889', 'is_elite: False']\n", + "Id: 1_95 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_95', 'origin': '(none)'} Metrics: ['ELUC: -5.950462806160166', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3079746728839981', 'is_elite: False']\n", + "Id: 1_52 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_52', 'origin': '(none)'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.2452674003344285', 'NSGA-II_rank: 3', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 1_53 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_53', 'origin': '(none)'} Metrics: ['ELUC: -6.044446429202913', 'NSGA-II_crowding_distance: 0.03534968046837913', 'NSGA-II_rank: 3', 'change: 0.2628536451945061', 'is_elite: False']\n", + "Id: 1_4 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_4', 'origin': '(none)'} Metrics: ['ELUC: -6.086142935635936', 'NSGA-II_crowding_distance: 0.0831892095286377', 'NSGA-II_rank: 3', 'change: 0.2652532010998625', 'is_elite: False']\n", + "Id: 1_25 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_25', 'origin': '(none)'} Metrics: ['ELUC: -6.134173239960316', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27889222138637876', 'is_elite: False']\n", + "Id: 1_82 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_82', 'origin': '(none)'} Metrics: ['ELUC: -6.329145505950768', 'NSGA-II_crowding_distance: 0.32438945175731065', 'NSGA-II_rank: 2', 'change: 0.25324819108309027', 'is_elite: False']\n", + "Id: 1_97 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_97', 'origin': '(none)'} Metrics: ['ELUC: -6.501161566338806', 'NSGA-II_crowding_distance: 0.15804160829608926', 'NSGA-II_rank: 1', 'change: 0.240353372152284', 'is_elite: True']\n", + "Id: 1_63 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_63', 'origin': '(none)'} Metrics: ['ELUC: -6.603242759603913', 'NSGA-II_crowding_distance: 0.17715949913110568', 'NSGA-II_rank: 3', 'change: 0.2657717679192212', 'is_elite: False']\n", + "Id: 1_100 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_100', 'origin': '(none)'} Metrics: ['ELUC: -7.102567052050262', 'NSGA-II_crowding_distance: 0.209103688292957', 'NSGA-II_rank: 4', 'change: 0.27255985817506256', 'is_elite: False']\n", + "Id: 1_88 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_88', 'origin': '(none)'} Metrics: ['ELUC: -7.272355188276104', 'NSGA-II_crowding_distance: 0.1234892674886823', 'NSGA-II_rank: 1', 'change: 0.2406372309459325', 'is_elite: True']\n", + "Id: 1_17 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_17', 'origin': '(none)'} Metrics: ['ELUC: -7.285795225542859', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2744985706939313', 'is_elite: False']\n", + "Id: 1_36 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_36', 'origin': '(none)'} Metrics: ['ELUC: -7.8207974205601305', 'NSGA-II_crowding_distance: 0.384090272040699', 'NSGA-II_rank: 3', 'change: 0.268235714180001', 'is_elite: False']\n", + "Id: 1_77 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_77', 'origin': '(none)'} Metrics: ['ELUC: -8.325822281664735', 'NSGA-II_crowding_distance: 0.10300552424449166', 'NSGA-II_rank: 1', 'change: 0.24612235676881664', 'is_elite: False']\n", + "Id: 1_70 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_70', 'origin': '(none)'} Metrics: ['ELUC: -8.350449386511723', 'NSGA-II_crowding_distance: 0.5383413873295833', 'NSGA-II_rank: 3', 'change: 0.2841867389287305', 'is_elite: False']\n", + "Id: 1_20 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_20', 'origin': '(none)'} Metrics: ['ELUC: -8.5494158544996', 'NSGA-II_crowding_distance: 0.05829153816515299', 'NSGA-II_rank: 1', 'change: 0.24962836761245755', 'is_elite: False']\n", + "Id: 1_83 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_83', 'origin': '(none)'} Metrics: ['ELUC: -8.770838341857386', 'NSGA-II_crowding_distance: 0.6189919870471517', 'NSGA-II_rank: 2', 'change: 0.2620623618258315', 'is_elite: False']\n", + "Id: 1_90 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_90', 'origin': '(none)'} Metrics: ['ELUC: -8.828065232402377', 'NSGA-II_crowding_distance: 1.003816921973317', 'NSGA-II_rank: 2', 'change: 0.28775520154368506', 'is_elite: False']\n", + "Id: 1_59 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_59', 'origin': '(none)'} Metrics: ['ELUC: -8.923754139296403', 'NSGA-II_crowding_distance: 0.30649716719819786', 'NSGA-II_rank: 3', 'change: 0.30203290555037654', 'is_elite: False']\n", + "Id: 1_85 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_85', 'origin': '(none)'} Metrics: ['ELUC: -8.964154852876387', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30351324392919976', 'is_elite: False']\n", + "Id: 1_68 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_68', 'origin': '(none)'} Metrics: ['ELUC: -9.050669260168299', 'NSGA-II_crowding_distance: 0.4391667055533637', 'NSGA-II_rank: 1', 'change: 0.2511738280516456', 'is_elite: True']\n", + "Id: 1_35 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_35', 'origin': '(none)'} Metrics: ['ELUC: -13.843850666566142', 'NSGA-II_crowding_distance: 0.496326411259545', 'NSGA-II_rank: 1', 'change: 0.29052751716329306', 'is_elite: True']\n", + "Id: 1_56 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_56', 'origin': '(none)'} Metrics: ['ELUC: -15.35517983317119', 'NSGA-II_crowding_distance: 0.23471902814618478', 'NSGA-II_rank: 1', 'change: 0.29191965976244105', 'is_elite: True']\n", + "Id: 1_2 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_2', 'origin': '(none)'} Metrics: ['ELUC: -17.262052426474675', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3000347708540562', 'is_elite: False']\n", + "Id: 1_28 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_28', 'origin': '(none)'} Metrics: ['ELUC: -17.430044305448007', 'NSGA-II_crowding_distance: 0.16275321750853775', 'NSGA-II_rank: 1', 'change: 0.299479159311911', 'is_elite: True']\n", + "Id: 1_72 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_72', 'origin': '(none)'} Metrics: ['ELUC: -17.528957136274656', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.3034649597652902', 'is_elite: True']\n", "\n", "Done with generation 1.\n", "--------\n", @@ -441,108 +464,108 @@ "PopulationResponse:\n", " Generation: 2\n", " Population size: 100\n", - " Checkpoint id: test/2/20240213-201723\n", - "Evaluating candidates synchronously because max_workers == 0\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 5s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", + " Checkpoint id: no-overlap/2/20240219-195342\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", "Evaluation done.\n", "Reporting evaluated population for generation 2 and asking ESP for generation 3...:\n", "Sending NextPopulation request\n", @@ -825,112 +848,140 @@ "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" ] }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ "Generation 2 data persisted.\n", "Evaluated candidates:\n", - "Id: 2_48 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_7', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_48', 'origin': '1_7~CUW~1_80#MGNP'} Metrics: ['ELUC: 20.426217328818765', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.28388163557441326', 'is_elite: False']\n", - "Id: 2_30 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_49', '1_32'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_30', 'origin': '1_49~CUW~1_32#MGNP'} Metrics: ['ELUC: 15.660917880085844', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2619445933698604', 'is_elite: False']\n", - "Id: 2_13 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_25', '1_40'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_13', 'origin': '1_25~CUW~1_40#MGNP'} Metrics: ['ELUC: 12.838778286446749', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2513969080783454', 'is_elite: False']\n", - "Id: 2_37 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_22', '1_25'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_37', 'origin': '1_22~CUW~1_25#MGNP'} Metrics: ['ELUC: 12.7240622901354', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 12', 'change: 0.29343572271977947', 'is_elite: False']\n", - "Id: 2_84 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_80', '1_32'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_84', 'origin': '1_80~CUW~1_32#MGNP'} Metrics: ['ELUC: 12.056501792997064', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.24777232727449255', 'is_elite: False']\n", - "Id: 2_43 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_43', 'origin': '1_10~CUW~1_22#MGNP'} Metrics: ['ELUC: 9.001547075600925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.24434930859213802', 'is_elite: False']\n", - "Id: 2_81 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_49', '1_21'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_81', 'origin': '1_49~CUW~1_21#MGNP'} Metrics: ['ELUC: 3.6938531773462806', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2404335225436354', 'is_elite: False']\n", - "Id: 2_59 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_59', 'origin': '1_56~CUW~1_65#MGNP'} Metrics: ['ELUC: 2.6772179515421946', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2368409668392598', 'is_elite: False']\n", - "Id: 2_69 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_69', 'origin': '1_56~CUW~1_22#MGNP'} Metrics: ['ELUC: 2.4045494606766438', 'NSGA-II_crowding_distance: 0.9553581362381198', 'NSGA-II_rank: 5', 'change: 0.25054444620273914', 'is_elite: False']\n", - "Id: 2_19 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_54', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_19', 'origin': '1_54~CUW~1_22#MGNP'} Metrics: ['ELUC: 2.097709799994767', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.35200566041479775', 'is_elite: False']\n", - "Id: 2_36 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_25', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_36', 'origin': '1_25~CUW~1_22#MGNP'} Metrics: ['ELUC: 2.0410628671776574', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 15', 'change: 0.3527707209256947', 'is_elite: False']\n", - "Id: 2_40 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_40', 'origin': '1_10~CUW~1_65#MGNP'} Metrics: ['ELUC: 2.0409874431454655', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3527712988545227', 'is_elite: False']\n", - "Id: 2_51 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_51', 'origin': '1_65~CUW~1_56#MGNP'} Metrics: ['ELUC: 1.9366482789062243', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27087890015770416', 'is_elite: False']\n", - "Id: 2_15 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_15', 'origin': '1_10~CUW~1_56#MGNP'} Metrics: ['ELUC: 1.9041322550506818', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3502944593570661', 'is_elite: False']\n", - "Id: 2_53 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_32'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_53', 'origin': '1_10~CUW~1_32#MGNP'} Metrics: ['ELUC: 1.4280209827221864', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.33987967962493404', 'is_elite: False']\n", - "Id: 2_50 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_54', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_50', 'origin': '1_54~CUW~1_56#MGNP'} Metrics: ['ELUC: 1.3892363908474943', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.33465143733302843', 'is_elite: False']\n", - "Id: 2_99 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_54', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_99', 'origin': '1_54~CUW~1_22#MGNP'} Metrics: ['ELUC: 0.5841690159022983', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2761969731076208', 'is_elite: False']\n", - "Id: 2_85 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_22', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_85', 'origin': '1_22~CUW~1_80#MGNP'} Metrics: ['ELUC: 0.313245763661834', 'NSGA-II_crowding_distance: 0.3373597950493061', 'NSGA-II_rank: 3', 'change: 0.23818122564259014', 'is_elite: False']\n", - "Id: 2_57 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_25'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_57', 'origin': '1_56~CUW~1_25#MGNP'} Metrics: ['ELUC: 0.012517319378487159', 'NSGA-II_crowding_distance: 0.017483746472284276', 'NSGA-II_rank: 4', 'change: 0.24050026731696617', 'is_elite: False']\n", - "Id: 2_76 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_94', '1_25'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_76', 'origin': '1_94~CUW~1_25#MGNP'} Metrics: ['ELUC: 0.012517319378487159', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 4', 'change: 0.24050026731696617', 'is_elite: False']\n", - "Id: 2_100 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_32', '1_10'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_100', 'origin': '1_32~CUW~1_10#MGNP'} Metrics: ['ELUC: 0.012517319378487159', 'NSGA-II_crowding_distance: 0.289120583133341', 'NSGA-II_rank: 4', 'change: 0.24050026731696617', 'is_elite: False']\n", - "Id: 2_42 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_26', '1_21'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_42', 'origin': '1_26~CUW~1_21#MGNP'} Metrics: ['ELUC: -0.22610957912182805', 'NSGA-II_crowding_distance: 0.602694014869001', 'NSGA-II_rank: 4', 'change: 0.24223628500712518', 'is_elite: False']\n", - "Id: 2_61 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_32', '1_54'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_61', 'origin': '1_32~CUW~1_54#MGNP'} Metrics: ['ELUC: -0.6717420700468756', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.23500270042168184', 'is_elite: False']\n", - "Id: 2_87 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_17', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_87', 'origin': '1_17~CUW~1_22#MGNP'} Metrics: ['ELUC: -1.459243038609209', 'NSGA-II_crowding_distance: 1.4970516539613068', 'NSGA-II_rank: 10', 'change: 0.2754706530635265', 'is_elite: False']\n", - "Id: 2_71 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_80', '1_25'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_71', 'origin': '1_80~CUW~1_25#MGNP'} Metrics: ['ELUC: -1.6665029908548898', 'NSGA-II_crowding_distance: 0.2932778318810981', 'NSGA-II_rank: 3', 'change: 0.2398788107089712', 'is_elite: False']\n", - "Id: 2_72 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_17'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_72', 'origin': '1_56~CUW~1_17#MGNP'} Metrics: ['ELUC: -1.8825945564079392', 'NSGA-II_crowding_distance: 1.108778032999376', 'NSGA-II_rank: 7', 'change: 0.26320186632813636', 'is_elite: False']\n", - "Id: 2_94 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_23', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_94', 'origin': '1_23~CUW~1_56#MGNP'} Metrics: ['ELUC: -2.1645298207787618', 'NSGA-II_crowding_distance: 0.6596815787942834', 'NSGA-II_rank: 5', 'change: 0.2548879254348382', 'is_elite: False']\n", - "Id: 2_93 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_93', 'origin': '1_10~CUW~1_80#MGNP'} Metrics: ['ELUC: -2.3883695800495013', 'NSGA-II_crowding_distance: 0.3343560154290871', 'NSGA-II_rank: 2', 'change: 0.23769694164458563', 'is_elite: False']\n", - "Id: 2_54 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_54', '1_10'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_54', 'origin': '1_54~CUW~1_10#MGNP'} Metrics: ['ELUC: -2.5559508421266006', 'NSGA-II_crowding_distance: 1.191671879805221', 'NSGA-II_rank: 10', 'change: 0.28552958773921727', 'is_elite: False']\n", - "Id: 2_32 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_100', '1_32'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_32', 'origin': '1_100~CUW~1_32#MGNP'} Metrics: ['ELUC: -2.976369611056865', 'NSGA-II_crowding_distance: 0.4373287319925716', 'NSGA-II_rank: 3', 'change: 0.24233832715140477', 'is_elite: False']\n", - "Id: 2_12 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_40'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_12', 'origin': '1_10~CUW~1_40#MGNP'} Metrics: ['ELUC: -3.2232666068481546', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26829354468304945', 'is_elite: False']\n", - "Id: 2_78 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_23', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_78', 'origin': '1_23~CUW~1_65#MGNP'} Metrics: ['ELUC: -3.3228046422293285', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2944450152971345', 'is_elite: False']\n", - "Id: 2_65 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_69', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_65', 'origin': '1_69~CUW~1_80#MGNP'} Metrics: ['ELUC: -3.9249608417979815', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2909316618803815', 'is_elite: False']\n", - "Id: 2_24 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_94'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_24', 'origin': '1_65~CUW~1_94#MGNP'} Metrics: ['ELUC: -4.024203330515323', 'NSGA-II_crowding_distance: 0.9495673909777134', 'NSGA-II_rank: 9', 'change: 0.2889673810429613', 'is_elite: False']\n", - "Id: 2_34 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_23', '1_94'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_34', 'origin': '1_23~CUW~1_94#MGNP'} Metrics: ['ELUC: -4.108047988458287', 'NSGA-II_crowding_distance: 1.064883054759599', 'NSGA-II_rank: 8', 'change: 0.26643224228675594', 'is_elite: False']\n", - "Id: 2_39 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_21', '1_21'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_39', 'origin': '1_21~CUW~1_21#MGNP'} Metrics: ['ELUC: -4.151216827905124', 'NSGA-II_crowding_distance: 0.8888634009683813', 'NSGA-II_rank: 4', 'change: 0.25250335656375383', 'is_elite: False']\n", - "Id: 2_60 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_32', '1_10'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_60', 'origin': '1_32~CUW~1_10#MGNP'} Metrics: ['ELUC: -4.153105852102006', 'NSGA-II_crowding_distance: 1.2459966620739216', 'NSGA-II_rank: 9', 'change: 0.29519099107396035', 'is_elite: False']\n", - "Id: 2_79 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_79', 'origin': '1_10~CUW~1_80#MGNP'} Metrics: ['ELUC: -4.402440076883288', 'NSGA-II_crowding_distance: 1.1037456652876356', 'NSGA-II_rank: 6', 'change: 0.2605907821089973', 'is_elite: False']\n", - "Id: 1_22 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_22', 'origin': '(none)'} Metrics: ['ELUC: -4.749842160281162', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.22310495691341786', 'is_elite: True']\n", - "Id: 2_11 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_32', '1_69'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_11', 'origin': '1_32~CUW~1_69#MGNP'} Metrics: ['ELUC: -4.77776731735845', 'NSGA-II_crowding_distance: 0.3929634203353946', 'NSGA-II_rank: 5', 'change: 0.2585677661698497', 'is_elite: False']\n", - "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_80', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_49', 'origin': '1_80~CUW~1_22#MGNP'} Metrics: ['ELUC: -4.924084823322826', 'NSGA-II_crowding_distance: 0.16945325278785323', 'NSGA-II_rank: 6', 'change: 0.2635362698348847', 'is_elite: False']\n", - "Id: 2_44 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_40'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_44', 'origin': '1_10~CUW~1_40#MGNP'} Metrics: ['ELUC: -5.226491168901316', 'NSGA-II_crowding_distance: 1.0467128277466562', 'NSGA-II_rank: 8', 'change: 0.26920284517114407', 'is_elite: False']\n", - "Id: 2_20 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_40', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_20', 'origin': '1_40~CUW~1_22#MGNP'} Metrics: ['ELUC: -5.620416252525117', 'NSGA-II_crowding_distance: 0.28221961210345625', 'NSGA-II_rank: 2', 'change: 0.23810053961464253', 'is_elite: False']\n", - "Id: 2_26 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_94', '1_100'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_26', 'origin': '1_94~CUW~1_100#MGNP'} Metrics: ['ELUC: -5.647252404910705', 'NSGA-II_crowding_distance: 0.056877337026400375', 'NSGA-II_rank: 7', 'change: 0.2658650702832454', 'is_elite: False']\n", - "Id: 2_29 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_29', 'origin': '1_10~CUW~1_65#MGNP'} Metrics: ['ELUC: -5.647252404910705', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 7', 'change: 0.2658650702832454', 'is_elite: False']\n", - "Id: 2_98 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_22', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_98', 'origin': '1_22~CUW~1_56#MGNP'} Metrics: ['ELUC: -5.647252404910705', 'NSGA-II_crowding_distance: 0.4882603260907077', 'NSGA-II_rank: 7', 'change: 0.2658650702832454', 'is_elite: False']\n", - "Id: 2_82 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_54', '1_40'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_82', 'origin': '1_54~CUW~1_40#MGNP'} Metrics: ['ELUC: -5.647252412451274', 'NSGA-II_crowding_distance: 0.23429388704005932', 'NSGA-II_rank: 6', 'change: 0.2658650702832454', 'is_elite: False']\n", - "Id: 2_31 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_69', '1_26'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_31', 'origin': '1_69~CUW~1_26#MGNP'} Metrics: ['ELUC: -5.6486042252569355', 'NSGA-II_crowding_distance: 0.3620835488514629', 'NSGA-II_rank: 3', 'change: 0.2489551412874952', 'is_elite: False']\n", - "Id: 2_18 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_40', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_18', 'origin': '1_40~CUW~1_56#MGNP'} Metrics: ['ELUC: -5.8136542253082455', 'NSGA-II_crowding_distance: 0.891221967000624', 'NSGA-II_rank: 7', 'change: 0.28298734831627903', 'is_elite: False']\n", - "Id: 2_80 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_69', '1_94'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_80', 'origin': '1_69~CUW~1_94#MGNP'} Metrics: ['ELUC: -5.913444667240919', 'NSGA-II_crowding_distance: 0.17570849865184468', 'NSGA-II_rank: 2', 'change: 0.24289312510804228', 'is_elite: False']\n", - "Id: 2_55 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_55', 'origin': '1_56~CUW~1_22#MGNP'} Metrics: ['ELUC: -6.235905903947189', 'NSGA-II_crowding_distance: 0.18603296613636233', 'NSGA-II_rank: 3', 'change: 0.24996963105038744', 'is_elite: False']\n", - "Id: 2_73 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_54'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_73', 'origin': '1_10~CUW~1_54#MGNP'} Metrics: ['ELUC: -6.4780485006361115', 'NSGA-II_crowding_distance: 0.3991226108712058', 'NSGA-II_rank: 6', 'change: 0.2711790206262812', 'is_elite: False']\n", - "Id: 2_28 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_28', 'origin': '1_56~CUW~1_80#MGNP'} Metrics: ['ELUC: -6.512840050887923', 'NSGA-II_crowding_distance: 0.6651940261542215', 'NSGA-II_rank: 5', 'change: 0.259568492126685', 'is_elite: False']\n", - "Id: 1_80 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_80', 'origin': '(none)'} Metrics: ['ELUC: -6.520730586577443', 'NSGA-II_crowding_distance: 0.34874715808108314', 'NSGA-II_rank: 1', 'change: 0.23723970522187782', 'is_elite: True']\n", - "Id: 2_67 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_67', 'origin': '1_10~CUW~1_22#MGNP'} Metrics: ['ELUC: -6.794600535228962', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30732028820937557', 'is_elite: False']\n", - "Id: 2_52 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_80', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_52', 'origin': '1_80~CUW~1_80#MGNP'} Metrics: ['ELUC: -6.963881645907935', 'NSGA-II_crowding_distance: 0.18277652206179906', 'NSGA-II_rank: 1', 'change: 0.23740308158227272', 'is_elite: False']\n", - "Id: 1_40 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_40', 'origin': '(none)'} Metrics: ['ELUC: -7.110222850313951', 'NSGA-II_crowding_distance: 0.1585527220608237', 'NSGA-II_rank: 2', 'change: 0.24412666188444093', 'is_elite: False']\n", - "Id: 2_21 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_21', 'origin': '1_56~CUW~1_22#MGNP'} Metrics: ['ELUC: -7.583946187080995', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.30558976404061294', 'is_elite: False']\n", - "Id: 2_58 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_22', '1_100'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_58', 'origin': '1_22~CUW~1_100#MGNP'} Metrics: ['ELUC: -7.814203481696938', 'NSGA-II_crowding_distance: 0.5542796724669998', 'NSGA-II_rank: 4', 'change: 0.2564816991249483', 'is_elite: False']\n", - "Id: 2_70 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_25', '1_10'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_70', 'origin': '1_25~CUW~1_10#MGNP'} Metrics: ['ELUC: -7.901037774874465', 'NSGA-II_crowding_distance: 0.661960447672305', 'NSGA-II_rank: 6', 'change: 0.2797089143512146', 'is_elite: False']\n", - "Id: 2_63 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_94', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_63', 'origin': '1_94~CUW~1_56#MGNP'} Metrics: ['ELUC: -7.924846972527943', 'NSGA-II_crowding_distance: 0.2987179186474942', 'NSGA-II_rank: 3', 'change: 0.25100133085337245', 'is_elite: False']\n", - "Id: 2_62 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_22', '1_17'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_62', 'origin': '1_22~CUW~1_17#MGNP'} Metrics: ['ELUC: -7.9781561690936655', 'NSGA-II_crowding_distance: 0.5219673565253762', 'NSGA-II_rank: 4', 'change: 0.26354778624777486', 'is_elite: False']\n", - "Id: 1_23 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_23', 'origin': '(none)'} Metrics: ['ELUC: -8.12467078249326', 'NSGA-II_crowding_distance: 0.2551225388803557', 'NSGA-II_rank: 2', 'change: 0.2448984513869198', 'is_elite: False']\n", - "Id: 2_64 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_94', '1_69'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_64', 'origin': '1_94~CUW~1_69#MGNP'} Metrics: ['ELUC: -8.129917322355805', 'NSGA-II_crowding_distance: 0.19884255533529116', 'NSGA-II_rank: 1', 'change: 0.24199258439907814', 'is_elite: False']\n", - "Id: 2_88 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_7', '1_49'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_88', 'origin': '1_7~CUW~1_49#MGNP'} Metrics: ['ELUC: -8.173446742186982', 'NSGA-II_crowding_distance: 0.18013346057598217', 'NSGA-II_rank: 1', 'change: 0.24587773884027367', 'is_elite: False']\n", - "Id: 2_91 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_49', '1_94'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_91', 'origin': '1_49~CUW~1_94#MGNP'} Metrics: ['ELUC: -8.691850411044692', 'NSGA-II_crowding_distance: 0.44620919685098764', 'NSGA-II_rank: 3', 'change: 0.25699207056235635', 'is_elite: False']\n", - "Id: 2_41 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_26', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_41', 'origin': '1_26~CUW~1_22#MGNP'} Metrics: ['ELUC: -8.718346273049834', 'NSGA-II_crowding_distance: 0.6516784434264857', 'NSGA-II_rank: 5', 'change: 0.27132571749179046', 'is_elite: False']\n", - "Id: 2_66 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_23'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_66', 'origin': '1_56~CUW~1_23#MGNP'} Metrics: ['ELUC: -9.031093351393427', 'NSGA-II_crowding_distance: 0.2499283452339781', 'NSGA-II_rank: 2', 'change: 0.2538356722259193', 'is_elite: False']\n", - "Id: 2_35 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_7', '1_32'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_35', 'origin': '1_7~CUW~1_32#MGNP'} Metrics: ['ELUC: -9.14466221750015', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.3054085949299378', 'is_elite: False']\n", - "Id: 1_94 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_94', 'origin': '(none)'} Metrics: ['ELUC: -9.742974149774458', 'NSGA-II_crowding_distance: 0.34027188872791014', 'NSGA-II_rank: 1', 'change: 0.24651100589774422', 'is_elite: True']\n", - "Id: 2_95 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_49', '1_10'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_95', 'origin': '1_49~CUW~1_10#MGNP'} Metrics: ['ELUC: -9.984542073307328', 'NSGA-II_crowding_distance: 0.10705401224849344', 'NSGA-II_rank: 2', 'change: 0.25449646785412927', 'is_elite: False']\n", - "Id: 2_90 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_69'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_90', 'origin': '1_65~CUW~1_69#MGNP'} Metrics: ['ELUC: -10.144273611745142', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2942899493929687', 'is_elite: False']\n", - "Id: 2_96 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_100'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_96', 'origin': '1_56~CUW~1_100#MGNP'} Metrics: ['ELUC: -10.204114779853303', 'NSGA-II_crowding_distance: 0.10012162118756615', 'NSGA-II_rank: 2', 'change: 0.25645665071567825', 'is_elite: False']\n", - "Id: 2_22 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_22', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_22', 'origin': '1_22~CUW~1_56#MGNP'} Metrics: ['ELUC: -10.489444941478796', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27190310905153064', 'is_elite: False']\n", - "Id: 2_83 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_83', 'origin': '1_56~CUW~1_65#MGNP'} Metrics: ['ELUC: -10.602057330143435', 'NSGA-II_crowding_distance: 0.14166801627467532', 'NSGA-II_rank: 2', 'change: 0.2588464870339232', 'is_elite: False']\n", - "Id: 2_47 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_7', '1_94'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_47', 'origin': '1_7~CUW~1_94#MGNP'} Metrics: ['ELUC: -10.894145811060321', 'NSGA-II_crowding_distance: 0.5997440235573382', 'NSGA-II_rank: 4', 'change: 0.26813360515117995', 'is_elite: False']\n", - "Id: 1_32 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_32', 'origin': '(none)'} Metrics: ['ELUC: -11.261973725541184', 'NSGA-II_crowding_distance: 0.32150578178995715', 'NSGA-II_rank: 1', 'change: 0.25415983088095273', 'is_elite: True']\n", - "Id: 2_74 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_94', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_74', 'origin': '1_94~CUW~1_65#MGNP'} Metrics: ['ELUC: -11.32595740682195', 'NSGA-II_crowding_distance: 0.400641675473411', 'NSGA-II_rank: 3', 'change: 0.26232457146696153', 'is_elite: False']\n", - "Id: 2_16 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_7', '1_21'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_16', 'origin': '1_7~CUW~1_21#MGNP'} Metrics: ['ELUC: -11.552963384450878', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2768500810625162', 'is_elite: False']\n", - "Id: 2_45 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_100', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_45', 'origin': '1_100~CUW~1_56#MGNP'} Metrics: ['ELUC: -11.702662258726281', 'NSGA-II_crowding_distance: 0.27014933055259643', 'NSGA-II_rank: 2', 'change: 0.2601378972070906', 'is_elite: False']\n", - "Id: 2_17 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_100'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_17', 'origin': '1_10~CUW~1_100#MGNP'} Metrics: ['ELUC: -11.81909182148705', 'NSGA-II_crowding_distance: 0.37238462396808886', 'NSGA-II_rank: 3', 'change: 0.266930042490788', 'is_elite: False']\n", - "Id: 2_68 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_68', 'origin': '1_56~CUW~1_56#MGNP'} Metrics: ['ELUC: -12.094302937872234', 'NSGA-II_crowding_distance: 0.16966863749849287', 'NSGA-II_rank: 1', 'change: 0.25779785971029173', 'is_elite: False']\n", - "Id: 1_56 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_56', 'origin': '(none)'} Metrics: ['ELUC: -12.434823816828384', 'NSGA-II_crowding_distance: 0.2688220628708416', 'NSGA-II_rank: 1', 'change: 0.2605316124824141', 'is_elite: True']\n", - "Id: 2_25 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_7', '1_10'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_25', 'origin': '1_7~CUW~1_10#MGNP'} Metrics: ['ELUC: -12.989389828651557', 'NSGA-II_crowding_distance: 0.4680497343422576', 'NSGA-II_rank: 3', 'change: 0.27543609327124213', 'is_elite: False']\n", - "Id: 2_14 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_94', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_14', 'origin': '1_94~CUW~1_56#MGNP'} Metrics: ['ELUC: -13.08787717396445', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2859715285153917', 'is_elite: False']\n", - "Id: 2_33 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_80', '1_22'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_33', 'origin': '1_80~CUW~1_22#MGNP'} Metrics: ['ELUC: -13.501305411008932', 'NSGA-II_crowding_distance: 0.8991705223859388', 'NSGA-II_rank: 2', 'change: 0.2657014475274944', 'is_elite: False']\n", - "Id: 2_92 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_94'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_92', 'origin': '1_10~CUW~1_94#MGNP'} Metrics: ['ELUC: -14.482385812200995', 'NSGA-II_crowding_distance: 0.40182162915951886', 'NSGA-II_rank: 1', 'change: 0.2646579318855017', 'is_elite: True']\n", - "Id: 2_75 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_75', 'origin': '1_65~CUW~1_65#MGNP'} Metrics: ['ELUC: -15.093176253530329', 'NSGA-II_crowding_distance: 0.24388288724801382', 'NSGA-II_rank: 1', 'change: 0.27635008433432195', 'is_elite: False']\n", - "Id: 1_65 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_65', 'origin': '(none)'} Metrics: ['ELUC: -15.424949134878572', 'NSGA-II_crowding_distance: 0.46553081112589656', 'NSGA-II_rank: 1', 'change: 0.2783556836638049', 'is_elite: True']\n", - "Id: 2_77 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_49', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_77', 'origin': '1_49~CUW~1_56#MGNP'} Metrics: ['ELUC: -16.874625104114276', 'NSGA-II_crowding_distance: 0.7438237092402511', 'NSGA-II_rank: 2', 'change: 0.30068456683506284', 'is_elite: False']\n", - "Id: 2_27 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_26', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_27', 'origin': '1_26~CUW~1_65#MGNP'} Metrics: ['ELUC: -17.083371087053507', 'NSGA-II_crowding_distance: 0.0869203961296049', 'NSGA-II_rank: 2', 'change: 0.302000214938745', 'is_elite: False']\n", - "Id: 2_97 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_10'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_97', 'origin': '1_10~CUW~1_10#MGNP'} Metrics: ['ELUC: -17.31461373974912', 'NSGA-II_crowding_distance: 0.4563635748361891', 'NSGA-II_rank: 1', 'change: 0.2999183448345391', 'is_elite: True']\n", - "Id: 1_10 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_10', 'origin': '(none)'} Metrics: ['ELUC: -17.580724861049067', 'NSGA-II_crowding_distance: 0.06373289324937659', 'NSGA-II_rank: 1', 'change: 0.3015936736594201', 'is_elite: False']\n", - "Id: 1_25 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '1_25', 'origin': '(none)'} Metrics: ['ELUC: -17.706449051990806', 'NSGA-II_crowding_distance: 0.033741991285424947', 'NSGA-II_rank: 1', 'change: 0.30260931794172286', 'is_elite: False']\n", - "Id: 2_86 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_32', '1_25'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_86', 'origin': '1_32~CUW~1_25#MGNP'} Metrics: ['ELUC: -17.812317677903753', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3028708988969066', 'is_elite: False']\n", - "Id: 2_46 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_54', '1_32'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_46', 'origin': '1_54~CUW~1_32#MGNP'} Metrics: ['ELUC: -17.8123871931882', 'NSGA-II_crowding_distance: 0.011384426822430625', 'NSGA-II_rank: 1', 'change: 0.302870491623648', 'is_elite: False']\n", - "Id: 2_23 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_25', '1_25'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_23', 'origin': '1_25~CUW~1_25#MGNP'} Metrics: ['ELUC: -17.81238741867421', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.30287049749980044', 'is_elite: True']\n", - "Id: 2_38 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_100'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_38', 'origin': '1_56~CUW~1_100#MGNP'} Metrics: ['ELUC: -17.81238741867421', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.30287049749980044', 'is_elite: False']\n", - "Id: 2_56 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_69', '1_7'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_56', 'origin': '1_69~CUW~1_7#MGNP'} Metrics: ['ELUC: -17.81238741867421', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.30287049749980044', 'is_elite: False']\n", - "Id: 2_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_10', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'test', 'unique_id': '2_89', 'origin': '1_10~CUW~1_80#MGNP'} Metrics: ['ELUC: -17.81238741867421', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.30287049749980044', 'is_elite: True']\n", + "Id: 2_55 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_20'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_55', 'origin': '1_97~CUW~1_20#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 2_58 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_75', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_58', 'origin': '1_75~CUW~1_1#MGNP'} Metrics: ['ELUC: 23.112613016313176', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.29987231725423164', 'is_elite: False']\n", + "Id: 2_61 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_14', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_61', 'origin': '1_14~CUW~1_72#MGNP'} Metrics: ['ELUC: 21.99285931743566', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.29598290047463227', 'is_elite: False']\n", + "Id: 2_86 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_86', 'origin': '1_97~CUW~1_72#MGNP'} Metrics: ['ELUC: 15.823808944433878', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2832179265814955', 'is_elite: False']\n", + "Id: 2_50 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_80', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_50', 'origin': '1_80~CUW~1_1#MGNP'} Metrics: ['ELUC: 14.160368368432904', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2573391028841921', 'is_elite: False']\n", + "Id: 2_99 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_99', 'origin': '1_97~CUW~1_1#MGNP'} Metrics: ['ELUC: 11.306103884279834', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24198319325075998', 'is_elite: False']\n", + "Id: 2_13 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_2', '1_77'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_13', 'origin': '1_2~CUW~1_77#MGNP'} Metrics: ['ELUC: 10.084544955636156', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2404922950003067', 'is_elite: False']\n", + "Id: 2_48 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_48', 'origin': '1_35~CUW~1_1#MGNP'} Metrics: ['ELUC: 9.739960499610179', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2794933775249182', 'is_elite: False']\n", + "Id: 2_52 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_20'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_52', 'origin': '1_56~CUW~1_20#MGNP'} Metrics: ['ELUC: 9.10515742178414', 'NSGA-II_crowding_distance: 0.2123816099901193', 'NSGA-II_rank: 6', 'change: 0.24364524822677533', 'is_elite: False']\n", + "Id: 2_81 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_14'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_81', 'origin': '1_72~CUW~1_14#MGNP'} Metrics: ['ELUC: 9.03672939875219', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 12', 'change: 0.3118998738566341', 'is_elite: False']\n", + "Id: 2_62 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_97'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_62', 'origin': '1_56~CUW~1_97#MGNP'} Metrics: ['ELUC: 7.946725647318616', 'NSGA-II_crowding_distance: 0.7992275415301636', 'NSGA-II_rank: 6', 'change: 0.24537396547906298', 'is_elite: False']\n", + "Id: 2_33 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_88', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_33', 'origin': '1_88~CUW~1_80#MGNP'} Metrics: ['ELUC: 6.432341265843208', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2365831648247635', 'is_elite: False']\n", + "Id: 2_72 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_72', 'origin': '1_28~CUW~1_1#MGNP'} Metrics: ['ELUC: 6.165769108750263', 'NSGA-II_crowding_distance: 1.1366730353633752', 'NSGA-II_rank: 10', 'change: 0.26650101257170405', 'is_elite: False']\n", + "Id: 2_69 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_88', '1_20'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_69', 'origin': '1_88~CUW~1_20#MGNP'} Metrics: ['ELUC: 5.19655598663282', 'NSGA-II_crowding_distance: 1.6176767804778371', 'NSGA-II_rank: 5', 'change: 0.24278906933162211', 'is_elite: False']\n", + "Id: 2_64 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_14', '1_83'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_64', 'origin': '1_14~CUW~1_83#MGNP'} Metrics: ['ELUC: 4.825051572206127', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.22596954148709775', 'is_elite: False']\n", + "Id: 2_36 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_36', 'origin': '1_28~CUW~1_65#MGNP'} Metrics: ['ELUC: 4.51264182678449', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 13', 'change: 0.3268631416834539', 'is_elite: False']\n", + "Id: 2_51 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_14', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_51', 'origin': '1_14~CUW~1_80#MGNP'} Metrics: ['ELUC: 4.279552714258514', 'NSGA-II_crowding_distance: 0.32714785593802553', 'NSGA-II_rank: 4', 'change: 0.23444063368541682', 'is_elite: False']\n", + "Id: 2_53 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_53', 'origin': '1_97~CUW~1_80#MGNP'} Metrics: ['ELUC: 3.7176273075518638', 'NSGA-II_crowding_distance: 0.4755292987034634', 'NSGA-II_rank: 4', 'change: 0.23735239212747708', 'is_elite: False']\n", + "Id: 2_39 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_39', 'origin': '1_65~CUW~1_72#MGNP'} Metrics: ['ELUC: 3.209721585204197', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2541103877864334', 'is_elite: False']\n", + "Id: 2_70 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_88', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_70', 'origin': '1_88~CUW~1_72#MGNP'} Metrics: ['ELUC: 3.1469460329111114', 'NSGA-II_crowding_distance: 0.4916541948517533', 'NSGA-II_rank: 9', 'change: 0.25579491810275085', 'is_elite: False']\n", + "Id: 2_16 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_77', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_16', 'origin': '1_77~CUW~1_65#MGNP'} Metrics: ['ELUC: 1.3663175806352301', 'NSGA-II_crowding_distance: 1.484286080577042', 'NSGA-II_rank: 9', 'change: 0.26101560493345555', 'is_elite: False']\n", + "Id: 2_91 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_91', 'origin': '1_1~CUW~1_88#MGNP'} Metrics: ['ELUC: 1.0150921914573718', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3327673366104463', 'is_elite: False']\n", + "Id: 2_47 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_47', 'origin': '1_56~CUW~1_80#MGNP'} Metrics: ['ELUC: 0.9950199078278169', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.319508825403344', 'is_elite: False']\n", + "Id: 2_84 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_84', 'origin': '1_35~CUW~1_65#MGNP'} Metrics: ['ELUC: 0.8758971967635645', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25171817552029624', 'is_elite: False']\n", + "Id: 2_43 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_43', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.6938171476787476', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04753260086869466', 'is_elite: False']\n", + "Id: 2_12 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_14'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_12', 'origin': '1_97~CUW~1_14#MGNP'} Metrics: ['ELUC: 0.6374387918753502', 'NSGA-II_crowding_distance: 1.2020268419345315', 'NSGA-II_rank: 7', 'change: 0.25060091738323415', 'is_elite: False']\n", + "Id: 2_90 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_90', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.3983267378042199', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03275319114565443', 'is_elite: False']\n", + "Id: 2_40 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_2', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_40', 'origin': '1_2~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.2021080444878682', 'NSGA-II_crowding_distance: 1.4821699927297407', 'NSGA-II_rank: 8', 'change: 0.2532877449993814', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 2_14 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_77', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_14', 'origin': '1_77~CUW~1_72#MGNP'} Metrics: ['ELUC: -0.39620961672610316', 'NSGA-II_crowding_distance: 1.0308515604392239', 'NSGA-II_rank: 10', 'change: 0.2751558804080265', 'is_elite: False']\n", + "Id: 2_38 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_83'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_38', 'origin': '1_28~CUW~1_83#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.8724755194131459', 'NSGA-II_rank: 4', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 1_14 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_14', 'origin': '(none)'} Metrics: ['ELUC: -0.5941013652776992', 'NSGA-II_crowding_distance: 1.046153086471632', 'NSGA-II_rank: 1', 'change: 0.22774267952277133', 'is_elite: True']\n", + "Id: 2_67 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_80', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_67', 'origin': '1_80~CUW~1_35#MGNP'} Metrics: ['ELUC: -0.6070535911700932', 'NSGA-II_crowding_distance: 0.8213497459364767', 'NSGA-II_rank: 2', 'change: 0.23501185616786588', 'is_elite: False']\n", + "Id: 2_46 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_14'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_46', 'origin': '1_97~CUW~1_14#MGNP'} Metrics: ['ELUC: -0.8887443148568342', 'NSGA-II_crowding_distance: 0.821525266845582', 'NSGA-II_rank: 3', 'change: 0.23589590722141068', 'is_elite: False']\n", + "Id: 2_24 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_14', '1_20'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_24', 'origin': '1_14~CUW~1_20#MGNP'} Metrics: ['ELUC: -0.8961802561697916', 'NSGA-II_crowding_distance: 0.18102622165560128', 'NSGA-II_rank: 2', 'change: 0.235554471559538', 'is_elite: False']\n", + "Id: 2_31 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_31', 'origin': '1_97~CUW~1_56#MGNP'} Metrics: ['ELUC: -1.0331783884451435', 'NSGA-II_crowding_distance: 0.03810380125098654', 'NSGA-II_rank: 3', 'change: 0.23844747506671962', 'is_elite: False']\n", + "Id: 2_15 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_82'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_15', 'origin': '1_28~CUW~1_82#MGNP'} Metrics: ['ELUC: -1.2498144179385051', 'NSGA-II_crowding_distance: 0.11868042334471064', 'NSGA-II_rank: 3', 'change: 0.23891478131411856', 'is_elite: False']\n", + "Id: 2_63 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_2'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_63', 'origin': '1_1~CUW~1_2#MGNP'} Metrics: ['ELUC: -1.3018619836005803', 'NSGA-II_crowding_distance: 0.9641826255315371', 'NSGA-II_rank: 7', 'change: 0.25166590906075414', 'is_elite: False']\n", + "Id: 2_56 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_68', '1_77'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_56', 'origin': '1_68~CUW~1_77#MGNP'} Metrics: ['ELUC: -1.7494291324565039', 'NSGA-II_crowding_distance: 0.9820357181927437', 'NSGA-II_rank: 6', 'change: 0.24992368567051804', 'is_elite: False']\n", + "Id: 2_26 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_97'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_26', 'origin': '1_1~CUW~1_97#MGNP'} Metrics: ['ELUC: -2.3383530235267727', 'NSGA-II_crowding_distance: 1.7768950231264409', 'NSGA-II_rank: 8', 'change: 0.2653882810020392', 'is_elite: False']\n", + "Id: 2_66 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_66', 'origin': '1_97~CUW~1_80#MGNP'} Metrics: ['ELUC: -2.5782786773583832', 'NSGA-II_crowding_distance: 0.17575175463660933', 'NSGA-II_rank: 3', 'change: 0.23911612571724042', 'is_elite: False']\n", + "Id: 2_28 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_68', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_28', 'origin': '1_68~CUW~1_88#MGNP'} Metrics: ['ELUC: -3.0917542869793317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.29606149017206945', 'is_elite: False']\n", + "Id: 2_98 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_98', 'origin': '1_65~CUW~1_72#MGNP'} Metrics: ['ELUC: -3.355810812666601', 'NSGA-II_crowding_distance: 0.25048224128163177', 'NSGA-II_rank: 3', 'change: 0.2436877535711964', 'is_elite: False']\n", + "Id: 2_97 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_97', 'origin': '1_65~CUW~1_72#MGNP'} Metrics: ['ELUC: -3.613820882766968', 'NSGA-II_crowding_distance: 1.4949201791676088', 'NSGA-II_rank: 5', 'change: 0.24878069868376226', 'is_elite: False']\n", + "Id: 2_57 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_77', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_57', 'origin': '1_77~CUW~1_72#MGNP'} Metrics: ['ELUC: -3.6751668721014363', 'NSGA-II_crowding_distance: 0.1853697353818657', 'NSGA-II_rank: 2', 'change: 0.23768760012383447', 'is_elite: False']\n", + "Id: 2_96 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_96', 'origin': '1_1~CUW~1_56#MGNP'} Metrics: ['ELUC: -3.821145204976857', 'NSGA-II_crowding_distance: 0.8633269646366248', 'NSGA-II_rank: 10', 'change: 0.2918553928647616', 'is_elite: False']\n", + "Id: 2_74 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_14', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_74', 'origin': '1_14~CUW~1_72#MGNP'} Metrics: ['ELUC: -4.066268772667995', 'NSGA-II_crowding_distance: 0.20424286991543295', 'NSGA-II_rank: 2', 'change: 0.23786617409795954', 'is_elite: False']\n", + "Id: 2_95 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_14'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_95', 'origin': '1_72~CUW~1_14#MGNP'} Metrics: ['ELUC: -4.12480862805616', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30965110760045567', 'is_elite: False']\n", + "Id: 2_73 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_73', 'origin': '1_1~CUW~1_56#MGNP'} Metrics: ['ELUC: -4.295084310296482', 'NSGA-II_crowding_distance: 0.6722873106051706', 'NSGA-II_rank: 4', 'change: 0.24851184053315478', 'is_elite: False']\n", + "Id: 2_42 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_20', '1_65'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_42', 'origin': '1_20~CUW~1_65#MGNP'} Metrics: ['ELUC: -4.818208883281856', 'NSGA-II_crowding_distance: 1.5083458051482468', 'NSGA-II_rank: 9', 'change: 0.2687687644378452', 'is_elite: False']\n", + "Id: 2_80 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_83'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_80', 'origin': '1_1~CUW~1_83#MGNP'} Metrics: ['ELUC: -4.821205928271841', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2804545071049133', 'is_elite: False']\n", + "Id: 1_65 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_65', 'origin': '(none)'} Metrics: ['ELUC: -4.852359001151172', 'NSGA-II_crowding_distance: 0.3203770539366556', 'NSGA-II_rank: 1', 'change: 0.234700850215592', 'is_elite: True']\n", + "Id: 2_27 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_14', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_27', 'origin': '1_14~CUW~1_35#MGNP'} Metrics: ['ELUC: -4.881920334788118', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2665138001046288', 'is_elite: False']\n", + "Id: 2_11 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_11', 'origin': '1_35~CUW~1_88#MGNP'} Metrics: ['ELUC: -4.945869491601383', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.26469944304381815', 'is_elite: False']\n", + "Id: 2_71 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_71', 'origin': '1_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.971527366088326', 'NSGA-II_crowding_distance: 0.3671605502313574', 'NSGA-II_rank: 6', 'change: 0.2548922758217908', 'is_elite: False']\n", + "Id: 2_60 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_6'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_60', 'origin': '1_65~CUW~1_6#MGNP'} Metrics: ['ELUC: -5.141445547937862', 'NSGA-II_crowding_distance: 0.805582671817137', 'NSGA-II_rank: 6', 'change: 0.2596705008171556', 'is_elite: False']\n", + "Id: 2_37 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_20'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_37', 'origin': '1_56~CUW~1_20#MGNP'} Metrics: ['ELUC: -5.32206720856688', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3067997423649592', 'is_elite: False']\n", + "Id: 2_94 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_77'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_94', 'origin': '1_72~CUW~1_77#MGNP'} Metrics: ['ELUC: -5.551278695515998', 'NSGA-II_crowding_distance: 0.27676189769977794', 'NSGA-II_rank: 3', 'change: 0.24651007515231377', 'is_elite: False']\n", + "Id: 2_77 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_97'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_77', 'origin': '1_97~CUW~1_97#MGNP'} Metrics: ['ELUC: -5.629050866664285', 'NSGA-II_crowding_distance: 0.11272024670659403', 'NSGA-II_rank: 1', 'change: 0.23789140796583833', 'is_elite: False']\n", + "Id: 2_92 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_14'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_92', 'origin': '1_65~CUW~1_14#MGNP'} Metrics: ['ELUC: -5.756126564570115', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2519561066350549', 'is_elite: False']\n", + "Id: 2_19 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_68', '1_97'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_19', 'origin': '1_68~CUW~1_97#MGNP'} Metrics: ['ELUC: -6.119568455920386', 'NSGA-II_crowding_distance: 0.35382906708777334', 'NSGA-II_rank: 4', 'change: 0.24966177202476073', 'is_elite: False']\n", + "Id: 2_59 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_90', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_59', 'origin': '1_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.26264902601691', 'NSGA-II_crowding_distance: 0.630915106674861', 'NSGA-II_rank: 4', 'change: 0.25790193527725186', 'is_elite: False']\n", + "Id: 1_97 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_97', 'origin': '(none)'} Metrics: ['ELUC: -6.501161566338806', 'NSGA-II_crowding_distance: 0.10266585691824297', 'NSGA-II_rank: 1', 'change: 0.240353372152284', 'is_elite: False']\n", + "Id: 2_20 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_14', '1_28'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_20', 'origin': '1_14~CUW~1_28#MGNP'} Metrics: ['ELUC: -6.820626350129164', 'NSGA-II_crowding_distance: 0.13141129914179617', 'NSGA-II_rank: 3', 'change: 0.24812069778195128', 'is_elite: False']\n", + "Id: 2_85 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_85', 'origin': '1_72~CUW~1_88#MGNP'} Metrics: ['ELUC: -6.918040768197296', 'NSGA-II_crowding_distance: 0.23888623157330802', 'NSGA-II_rank: 2', 'change: 0.24400938334356703', 'is_elite: False']\n", + "Id: 2_100 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_83', '1_77'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_100', 'origin': '1_83~CUW~1_77#MGNP'} Metrics: ['ELUC: -7.186990121984908', 'NSGA-II_crowding_distance: 0.035461293814171804', 'NSGA-II_rank: 3', 'change: 0.24881104547233837', 'is_elite: False']\n", + "Id: 2_54 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_13', '1_28'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_54', 'origin': '1_13~CUW~1_28#MGNP'} Metrics: ['ELUC: -7.199260535978648', 'NSGA-II_crowding_distance: 0.06675019940440181', 'NSGA-II_rank: 3', 'change: 0.25004526304672475', 'is_elite: False']\n", + "Id: 1_88 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_88', 'origin': '(none)'} Metrics: ['ELUC: -7.272355188276104', 'NSGA-II_crowding_distance: 0.06648961719016683', 'NSGA-II_rank: 1', 'change: 0.2406372309459325', 'is_elite: False']\n", + "Id: 2_25 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_90', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_25', 'origin': '1_90~CUW~1_88#MGNP'} Metrics: ['ELUC: -7.566111422593919', 'NSGA-II_crowding_distance: 0.0464765815810978', 'NSGA-II_rank: 1', 'change: 0.24211986491506207', 'is_elite: False']\n", + "Id: 2_30 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_30', 'origin': '1_1~CUW~1_88#MGNP'} Metrics: ['ELUC: -7.57493293109276', 'NSGA-II_crowding_distance: 0.09695959068321972', 'NSGA-II_rank: 3', 'change: 0.2591797436490047', 'is_elite: False']\n", + "Id: 2_78 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_78', 'origin': '1_56~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.729624967432534', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2736085414469689', 'is_elite: False']\n", + "Id: 2_93 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_88', '1_14'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_93', 'origin': '1_88~CUW~1_14#MGNP'} Metrics: ['ELUC: -7.837691166138025', 'NSGA-II_crowding_distance: 0.07954786212306665', 'NSGA-II_rank: 2', 'change: 0.2455849523072806', 'is_elite: False']\n", + "Id: 2_18 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_77', '1_77'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_18', 'origin': '1_77~CUW~1_77#MGNP'} Metrics: ['ELUC: -7.839625044839789', 'NSGA-II_crowding_distance: 0.07855561267043992', 'NSGA-II_rank: 1', 'change: 0.24487806284974903', 'is_elite: False']\n", + "Id: 2_65 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_88', '1_68'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_65', 'origin': '1_88~CUW~1_68#MGNP'} Metrics: ['ELUC: -8.013404750265233', 'NSGA-II_crowding_distance: 0.036649577184912754', 'NSGA-II_rank: 2', 'change: 0.24900333196820626', 'is_elite: False']\n", + "Id: 2_34 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_68'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_34', 'origin': '1_65~CUW~1_68#MGNP'} Metrics: ['ELUC: -8.019010613296334', 'NSGA-II_crowding_distance: 0.05839789259806251', 'NSGA-II_rank: 3', 'change: 0.2597842329273014', 'is_elite: False']\n", + "Id: 2_41 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_68', '1_97'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_41', 'origin': '1_68~CUW~1_97#MGNP'} Metrics: ['ELUC: -8.09333183815428', 'NSGA-II_crowding_distance: 0.08321499520063563', 'NSGA-II_rank: 3', 'change: 0.26453299321602725', 'is_elite: False']\n", + "Id: 2_23 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_77', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_23', 'origin': '1_77~CUW~1_88#MGNP'} Metrics: ['ELUC: -8.172097988132306', 'NSGA-II_crowding_distance: 0.17441346834462218', 'NSGA-II_rank: 2', 'change: 0.2504566986831349', 'is_elite: False']\n", + "Id: 2_32 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_90', '1_2'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_32', 'origin': '1_90~CUW~1_2#MGNP'} Metrics: ['ELUC: -8.259336906100167', 'NSGA-II_crowding_distance: 0.17515847067165372', 'NSGA-II_rank: 3', 'change: 0.277764324285421', 'is_elite: False']\n", + "Id: 2_88 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_68', '1_68'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_88', 'origin': '1_68~CUW~1_68#MGNP'} Metrics: ['ELUC: -8.553210109080277', 'NSGA-II_crowding_distance: 0.08997843152373598', 'NSGA-II_rank: 1', 'change: 0.24880774017307886', 'is_elite: False']\n", + "Id: 2_79 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_68'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_79', 'origin': '1_35~CUW~1_68#MGNP'} Metrics: ['ELUC: -8.622186784851888', 'NSGA-II_crowding_distance: 0.1504860157345618', 'NSGA-II_rank: 3', 'change: 0.30190149722594817', 'is_elite: False']\n", + "Id: 2_22 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_20'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_22', 'origin': '1_1~CUW~1_20#MGNP'} Metrics: ['ELUC: -9.012296785543725', 'NSGA-II_crowding_distance: 0.036997521985176536', 'NSGA-II_rank: 3', 'change: 0.30366689737359676', 'is_elite: False']\n", + "Id: 2_82 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_68'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_82', 'origin': '1_35~CUW~1_68#MGNP'} Metrics: ['ELUC: -9.017984874358277', 'NSGA-II_crowding_distance: 0.0012787650250081152', 'NSGA-II_rank: 3', 'change: 0.303893630306371', 'is_elite: False']\n", + "Id: 2_29 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_20', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_29', 'origin': '1_20~CUW~1_80#MGNP'} Metrics: ['ELUC: -9.018266366272098', 'NSGA-II_crowding_distance: 0.3405966847269848', 'NSGA-II_rank: 3', 'change: 0.303895911857366', 'is_elite: False']\n", + "Id: 1_68 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_68', 'origin': '(none)'} Metrics: ['ELUC: -9.050669260168299', 'NSGA-II_crowding_distance: 0.150442152554442', 'NSGA-II_rank: 1', 'change: 0.2511738280516456', 'is_elite: True']\n", + "Id: 2_35 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_77'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_35', 'origin': '1_72~CUW~1_77#MGNP'} Metrics: ['ELUC: -10.131376608610884', 'NSGA-II_crowding_distance: 0.24237411017037835', 'NSGA-II_rank: 2', 'change: 0.26423657971085124', 'is_elite: False']\n", + "Id: 2_21 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_6'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_21', 'origin': '1_72~CUW~1_6#MGNP'} Metrics: ['ELUC: -10.65917775781869', 'NSGA-II_crowding_distance: 0.5575519798133929', 'NSGA-II_rank: 2', 'change: 0.278513961103949', 'is_elite: False']\n", + "Id: 2_87 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_14'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_87', 'origin': '1_28~CUW~1_14#MGNP'} Metrics: ['ELUC: -11.038544889744824', 'NSGA-II_crowding_distance: 0.23813121922932712', 'NSGA-II_rank: 1', 'change: 0.2515194286694687', 'is_elite: True']\n", + "Id: 2_17 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_20', '1_28'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_17', 'origin': '1_20~CUW~1_28#MGNP'} Metrics: ['ELUC: -11.960152905922111', 'NSGA-II_crowding_distance: 0.179679606642474', 'NSGA-II_rank: 1', 'change: 0.27285204288836606', 'is_elite: True']\n", + "Id: 2_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_72'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_89', 'origin': '1_35~CUW~1_72#MGNP'} Metrics: ['ELUC: -12.59642310703102', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.32358844720172203', 'is_elite: False']\n", + "Id: 2_44 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_97'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_44', 'origin': '1_35~CUW~1_97#MGNP'} Metrics: ['ELUC: -12.938138091935414', 'NSGA-II_crowding_distance: 0.08909244563066925', 'NSGA-II_rank: 1', 'change: 0.2728951369841441', 'is_elite: False']\n", + "Id: 2_45 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_45', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -13.257527000143446', 'NSGA-II_crowding_distance: 0.11060679163487114', 'NSGA-II_rank: 1', 'change: 0.2774184049956194', 'is_elite: False']\n", + "Id: 1_35 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_35', 'origin': '(none)'} Metrics: ['ELUC: -13.843850666566142', 'NSGA-II_crowding_distance: 0.16790486473748895', 'NSGA-II_rank: 1', 'change: 0.29052751716329306', 'is_elite: True']\n", + "Id: 1_56 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_56', 'origin': '(none)'} Metrics: ['ELUC: -15.35517983317119', 'NSGA-II_crowding_distance: 0.21391053685234712', 'NSGA-II_rank: 1', 'change: 0.29191965976244105', 'is_elite: True']\n", + "Id: 2_76 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_1'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_76', 'origin': '1_35~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.13446528840325', 'NSGA-II_crowding_distance: 0.14334377867467757', 'NSGA-II_rank: 1', 'change: 0.2985109100353784', 'is_elite: False']\n", + "Id: 1_28 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_28', 'origin': '(none)'} Metrics: ['ELUC: -17.430044305448007', 'NSGA-II_crowding_distance: 0.041442349277033025', 'NSGA-II_rank: 1', 'change: 0.299479159311911', 'is_elite: False']\n", + "Id: 1_72 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_72', 'origin': '(none)'} Metrics: ['ELUC: -17.528957136274656', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3034649597652902', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 2_68 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_56'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_68', 'origin': '1_72~CUW~1_56#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 2_75 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_72', '1_80'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_75', 'origin': '1_72~CUW~1_80#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 2_83 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_83', 'origin': '1_97~CUW~1_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", "\n", "Done with generation 2.\n", "--------\n", @@ -939,42 +990,65486 @@ "PopulationResponse:\n", " Generation: 3\n", " Population size: 100\n", - " Checkpoint id: test/3/20240213-202530\n", - "Evaluating candidates synchronously because max_workers == 0\n", - "1233/1233 [==============================] - 4s 3ms/step\n", - "1233/1233 [==============================] - 4s 4ms/step\n", - "1233/1233 [==============================] - 5s 4ms/step\n", - " 193/1233 [===>..........................] - ETA: 3s" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "Input \u001b[0;32mIn [7]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 18\u001b[0m esp_service \u001b[38;5;241m=\u001b[39m EspService(presc_config, esp_username, esp_password)\n\u001b[1;32m 19\u001b[0m esp_evaluator \u001b[38;5;241m=\u001b[39m UnileafPrescriptor(presc_config,\n\u001b[1;32m 20\u001b[0m eval_df_encoded,\n\u001b[1;32m 21\u001b[0m dataset\u001b[38;5;241m.\u001b[39mencoder,\n\u001b[1;32m 22\u001b[0m [nnp])\n\u001b[0;32m---> 23\u001b[0m experiment_results_dir \u001b[38;5;241m=\u001b[39m \u001b[43mesp_service\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43mesp_evaluator\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/esp_sdk/esp_service.py:137\u001b[0m, in \u001b[0;36mEspService.train\u001b[0;34m(self, evaluator, checkpoint_id, early_stopper, plotter)\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 125\u001b[0m \u001b[38;5;124;03mTrains and persists Prescriptors according to the experiment parameters.\u001b[39;00m\n\u001b[1;32m 126\u001b[0m \u001b[38;5;124;03m:param evaluator: an EspEvaluator to evaluate the candidate Prescriptors\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 134\u001b[0m \u001b[38;5;124;03m:return: the name of the folder to which the Prescriptors have been persisted at the end of each generation\u001b[39;00m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 136\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_session \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 137\u001b[0m persistence_directory \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_training_loop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_with_evaluator\u001b[49m\u001b[43m(\u001b[49m\u001b[43mevaluator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 138\u001b[0m \u001b[43m \u001b[49m\u001b[43mcheckpoint_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcheckpoint_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 139\u001b[0m \u001b[43m \u001b[49m\u001b[43mearly_stopper\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mearly_stopper\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 140\u001b[0m \u001b[43m \u001b[49m\u001b[43mplotter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mplotter\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 141\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 142\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed to connect to ESP service. Can\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt train.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/esp_sdk/training/esp_training_loop.py:135\u001b[0m, in \u001b[0;36mEspTrainingLoop.train_with_evaluator\u001b[0;34m(self, evaluator, checkpoint_id, early_stopper, plotter)\u001b[0m\n\u001b[1;32m 132\u001b[0m logging\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPersistence directory: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28mstr\u001b[39m(persistence_dir))\n\u001b[1;32m 134\u001b[0m eval_pop_start_time \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m--> 135\u001b[0m \u001b[43mevaluator\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mevaluate_population\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnext_population_response\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 136\u001b[0m eval_pop_end_time \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[1;32m 137\u001b[0m eval_pop_times\u001b[38;5;241m.\u001b[39mappend(eval_pop_end_time \u001b[38;5;241m-\u001b[39m eval_pop_start_time)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/esp_sdk/esp_evaluator.py:76\u001b[0m, in \u001b[0;36mEspEvaluator.evaluate_population\u001b[0;34m(self, response)\u001b[0m\n\u001b[1;32m 74\u001b[0m population_evaluator \u001b[38;5;241m=\u001b[39m DefaultPopulationEvaluator(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig, \u001b[38;5;28mself\u001b[39m)\n\u001b[1;32m 75\u001b[0m evaluation_data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;66;03m# None passed in with this interface\u001b[39;00m\n\u001b[0;32m---> 76\u001b[0m \u001b[43mpopulation_evaluator\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mevaluate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresponse\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevaluation_data\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/esp_sdk/evaluation/default_population_evaluator.py:100\u001b[0m, in \u001b[0;36mDefaultPopulationEvaluator.evaluate\u001b[0;34m(self, component, evaluation_data)\u001b[0m\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mEvaluating candidates synchronously because max_workers == 0\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 97\u001b[0m population_evaluator \u001b[38;5;241m=\u001b[39m SynchronousPopulationEvaluator(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_config,\n\u001b[1;32m 98\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_candidate_evaluator,\n\u001b[1;32m 99\u001b[0m candidates_to_evaluate)\n\u001b[0;32m--> 100\u001b[0m \u001b[43mpopulation_evaluator\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mevaluate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpopulation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevaluation_data\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/esp_sdk/evaluation/synchronous_population_evaluator.py:77\u001b[0m, in \u001b[0;36mSynchronousPopulationEvaluator.evaluate\u001b[0;34m(self, component, evaluation_data)\u001b[0m\n\u001b[1;32m 73\u001b[0m model \u001b[38;5;241m=\u001b[39m ModelUtil\u001b[38;5;241m.\u001b[39mmodel_from_bytes(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_config, candidate\u001b[38;5;241m.\u001b[39minterpretation)\n\u001b[1;32m 75\u001b[0m \u001b[38;5;66;03m# Actually evaluate a single candidate\u001b[39;00m\n\u001b[1;32m 76\u001b[0m \u001b[38;5;66;03m# Simply pass along the evaluation_data, whatever it is\u001b[39;00m\n\u001b[0;32m---> 77\u001b[0m metrics \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_candidate_evaluator\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mevaluate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevaluation_data\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 79\u001b[0m \u001b[38;5;66;03m# Update the metrics of the candidate in place in the population list\u001b[39;00m\n\u001b[1;32m 80\u001b[0m candidate\u001b[38;5;241m.\u001b[39mmetrics \u001b[38;5;241m=\u001b[39m MetricsSerializer\u001b[38;5;241m.\u001b[39mencode(metrics)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/esp_sdk/esp_evaluator.py:89\u001b[0m, in \u001b[0;36mEspEvaluator.evaluate\u001b[0;34m(self, component, evaluation_data)\u001b[0m\n\u001b[1;32m 79\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 80\u001b[0m \u001b[38;5;124;03mEvaluates a single kind of model object on the given evaluation_data\u001b[39;00m\n\u001b[1;32m 81\u001b[0m \u001b[38;5;124;03mreturning a metrics dictionary giving clues as to how the evaluation\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 86\u001b[0m \u001b[38;5;124;03mpassed in.\u001b[39;00m\n\u001b[1;32m 87\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 88\u001b[0m _ \u001b[38;5;241m=\u001b[39m evaluation_data\n\u001b[0;32m---> 89\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mevaluate_candidate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcomponent\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/workspace/mvp/use_cases/eluc/prescriptors/prescriptor.py:122\u001b[0m, in \u001b[0;36mUnileafPrescriptor.evaluate_candidate\u001b[0;34m(self, candidate)\u001b[0m\n\u001b[1;32m 110\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 111\u001b[0m \u001b[38;5;124;03mEvaluates a single Prescriptor candidate and returns its metrics.\u001b[39;00m\n\u001b[1;32m 112\u001b[0m \u001b[38;5;124;03mImplements the EspEvaluator interface\u001b[39;00m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;124;03m:param candidate: a Keras neural network or rule based Prescriptor candidate\u001b[39;00m\n\u001b[1;32m 114\u001b[0m \u001b[38;5;124;03m:return metrics: A dictionary of {'metric_name': metric_value}\u001b[39;00m\n\u001b[1;32m 115\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 116\u001b[0m \u001b[38;5;66;03m# Save candidate to local file for easy debug\u001b[39;00m\n\u001b[1;32m 117\u001b[0m \u001b[38;5;66;03m# candidate.save('prescriptor.h5')\u001b[39;00m\n\u001b[1;32m 118\u001b[0m \n\u001b[1;32m 119\u001b[0m \u001b[38;5;66;03m# Prescribe actions\u001b[39;00m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;66;03m# Single action, recommended percentage for each land use type\u001b[39;00m\n\u001b[1;32m 121\u001b[0m \u001b[38;5;66;03m# Note: prescribed action is a softmax, NOT encoded in the same scale as the context\u001b[39;00m\n\u001b[0;32m--> 122\u001b[0m prescribed_actions_df \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprescribe\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcandidate\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 124\u001b[0m \u001b[38;5;66;03m# Convert the softmax into a DataFrame\u001b[39;00m\n\u001b[1;32m 125\u001b[0m reco_land_use_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(prescribed_actions_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreco_land_use\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mtolist(),\n\u001b[1;32m 126\u001b[0m columns\u001b[38;5;241m=\u001b[39mconstants\u001b[38;5;241m.\u001b[39mRECO_COLS)\n", - "File \u001b[0;32m~/workspace/mvp/use_cases/eluc/prescriptors/prescriptor.py:201\u001b[0m, in \u001b[0;36mUnileafPrescriptor.prescribe\u001b[0;34m(self, candidate, context_df)\u001b[0m\n\u001b[1;32m 193\u001b[0m row_index \u001b[38;5;241m=\u001b[39m context_df\u001b[38;5;241m.\u001b[39mindex\n\u001b[1;32m 195\u001b[0m \u001b[38;5;66;03m# Temporarily removed, may come back if we do rule-based prescription\u001b[39;00m\n\u001b[1;32m 196\u001b[0m \u001b[38;5;66;03m# is_rule_based = isinstance(candidate, RuleSet)\u001b[39;00m\n\u001b[1;32m 197\u001b[0m \u001b[38;5;66;03m# if is_rule_based:\u001b[39;00m\n\u001b[1;32m 198\u001b[0m \u001b[38;5;66;03m# actions = self._prescribe_from_rules(candidate, context_as_nn_input)\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;66;03m# else:\u001b[39;00m\n\u001b[1;32m 200\u001b[0m \u001b[38;5;66;03m# actions = self._prescribe_from_nn(candidate, context_as_nn_input)\u001b[39;00m\n\u001b[0;32m--> 201\u001b[0m actions \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_prescribe_from_nn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcandidate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcontext_as_nn_input\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 203\u001b[0m \u001b[38;5;66;03m# Convert the prescribed actions to a DataFrame\u001b[39;00m\n\u001b[1;32m 204\u001b[0m prescribed_actions_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(actions,\n\u001b[1;32m 205\u001b[0m columns\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcao_mapping[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mactions\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[1;32m 206\u001b[0m index\u001b[38;5;241m=\u001b[39mrow_index)\n", - "File \u001b[0;32m~/workspace/mvp/use_cases/eluc/prescriptors/prescriptor.py:217\u001b[0m, in \u001b[0;36mUnileafPrescriptor._prescribe_from_nn\u001b[0;34m(self, candidate, context_as_nn_input)\u001b[0m\n\u001b[1;32m 210\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 211\u001b[0m \u001b[38;5;124;03mGenerates prescriptions using the passed neural network candidate and context\u001b[39;00m\n\u001b[1;32m 212\u001b[0m \u001b[38;5;124;03m:param candidate: a Keras neural network candidate\u001b[39;00m\n\u001b[1;32m 213\u001b[0m \u001b[38;5;124;03m:param context_as_nn_input: a numpy array containing the context to prescribe for\u001b[39;00m\n\u001b[1;32m 214\u001b[0m \u001b[38;5;124;03m:return: a dictionary of action name to action value or list of action values\u001b[39;00m\n\u001b[1;32m 215\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 216\u001b[0m \u001b[38;5;66;03m# Get the prescribed actions\u001b[39;00m\n\u001b[0;32m--> 217\u001b[0m prescribed_actions \u001b[38;5;241m=\u001b[39m \u001b[43mcandidate\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcontext_as_nn_input\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 218\u001b[0m actions \u001b[38;5;241m=\u001b[39m {}\n\u001b[1;32m 220\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_single_action_prescriptor():\n\u001b[1;32m 221\u001b[0m \u001b[38;5;66;03m# Put the single action in an array to process it like multiple actions\u001b[39;00m\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/utils/traceback_utils.py:65\u001b[0m, in \u001b[0;36mfilter_traceback..error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 63\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 64\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 65\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 66\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 67\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:2554\u001b[0m, in \u001b[0;36mModel.predict\u001b[0;34m(self, x, batch_size, verbose, steps, callbacks, max_queue_size, workers, use_multiprocessing)\u001b[0m\n\u001b[1;32m 2552\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m step \u001b[38;5;129;01min\u001b[39;00m data_handler\u001b[38;5;241m.\u001b[39msteps():\n\u001b[1;32m 2553\u001b[0m callbacks\u001b[38;5;241m.\u001b[39mon_predict_batch_begin(step)\n\u001b[0;32m-> 2554\u001b[0m tmp_batch_outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2555\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m data_handler\u001b[38;5;241m.\u001b[39mshould_sync:\n\u001b[1;32m 2556\u001b[0m context\u001b[38;5;241m.\u001b[39masync_wait()\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/tensorflow/python/util/traceback_utils.py:150\u001b[0m, in \u001b[0;36mfilter_traceback..error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 148\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 149\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 150\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 151\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 152\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py:825\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[0;34m(self, *args, **kwds)\u001b[0m\n\u001b[1;32m 822\u001b[0m compiler \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mxla\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jit_compile \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnonXla\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 824\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m OptionalXlaContext(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jit_compile):\n\u001b[0;32m--> 825\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 827\u001b[0m new_tracing_count \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexperimental_get_tracing_count()\n\u001b[1;32m 828\u001b[0m without_tracing \u001b[38;5;241m=\u001b[39m (tracing_count \u001b[38;5;241m==\u001b[39m new_tracing_count)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py:864\u001b[0m, in \u001b[0;36mFunction._call\u001b[0;34m(self, *args, **kwds)\u001b[0m\n\u001b[1;32m 861\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock\u001b[38;5;241m.\u001b[39mrelease()\n\u001b[1;32m 862\u001b[0m \u001b[38;5;66;03m# In this case we have not created variables on the first call. So we can\u001b[39;00m\n\u001b[1;32m 863\u001b[0m \u001b[38;5;66;03m# run the first trace but we should fail if variables are created.\u001b[39;00m\n\u001b[0;32m--> 864\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_variable_creation_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 865\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_created_variables \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m ALLOW_DYNAMIC_VARIABLE_CREATION:\n\u001b[1;32m 866\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCreating variables on a non-first call to a function\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 867\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m decorated with tf.function.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/tensorflow/python/eager/polymorphic_function/tracing_compiler.py:148\u001b[0m, in \u001b[0;36mTracingCompiler.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 145\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock:\n\u001b[1;32m 146\u001b[0m (concrete_function,\n\u001b[1;32m 147\u001b[0m filtered_flat_args) \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_maybe_define_function(args, kwargs)\n\u001b[0;32m--> 148\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mconcrete_function\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_flat\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 149\u001b[0m \u001b[43m \u001b[49m\u001b[43mfiltered_flat_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcaptured_inputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconcrete_function\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcaptured_inputs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/tensorflow/python/eager/polymorphic_function/monomorphic_function.py:1349\u001b[0m, in \u001b[0;36mConcreteFunction._call_flat\u001b[0;34m(self, args, captured_inputs)\u001b[0m\n\u001b[1;32m 1345\u001b[0m possible_gradient_type \u001b[38;5;241m=\u001b[39m gradients_util\u001b[38;5;241m.\u001b[39mPossibleTapeGradientTypes(args)\n\u001b[1;32m 1346\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (possible_gradient_type \u001b[38;5;241m==\u001b[39m gradients_util\u001b[38;5;241m.\u001b[39mPOSSIBLE_GRADIENT_TYPES_NONE\n\u001b[1;32m 1347\u001b[0m \u001b[38;5;129;01mand\u001b[39;00m executing_eagerly):\n\u001b[1;32m 1348\u001b[0m \u001b[38;5;66;03m# No tape is watching; skip to running the function.\u001b[39;00m\n\u001b[0;32m-> 1349\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_build_call_outputs(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_inference_function\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 1350\u001b[0m forward_backward \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_select_forward_and_backward_functions(\n\u001b[1;32m 1351\u001b[0m args,\n\u001b[1;32m 1352\u001b[0m possible_gradient_type,\n\u001b[1;32m 1353\u001b[0m executing_eagerly)\n\u001b[1;32m 1354\u001b[0m forward_function, args_with_tangents \u001b[38;5;241m=\u001b[39m forward_backward\u001b[38;5;241m.\u001b[39mforward()\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/tensorflow/python/eager/polymorphic_function/atomic_function.py:196\u001b[0m, in \u001b[0;36mAtomicFunction.__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 194\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m record\u001b[38;5;241m.\u001b[39mstop_recording():\n\u001b[1;32m 195\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_bound_context\u001b[38;5;241m.\u001b[39mexecuting_eagerly():\n\u001b[0;32m--> 196\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_bound_context\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_function\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 197\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 198\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 199\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfunction_type\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mflat_outputs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 200\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 201\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 202\u001b[0m outputs \u001b[38;5;241m=\u001b[39m make_call_op_in_graph(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28mlist\u001b[39m(args))\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/tensorflow/python/eager/context.py:1457\u001b[0m, in \u001b[0;36mContext.call_function\u001b[0;34m(self, name, tensor_inputs, num_outputs)\u001b[0m\n\u001b[1;32m 1455\u001b[0m cancellation_context \u001b[38;5;241m=\u001b[39m cancellation\u001b[38;5;241m.\u001b[39mcontext()\n\u001b[1;32m 1456\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cancellation_context \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1457\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mexecute\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1458\u001b[0m \u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mutf-8\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1459\u001b[0m \u001b[43m \u001b[49m\u001b[43mnum_outputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_outputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1460\u001b[0m \u001b[43m \u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtensor_inputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1461\u001b[0m \u001b[43m \u001b[49m\u001b[43mattrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1462\u001b[0m \u001b[43m \u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1463\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1464\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1465\u001b[0m outputs \u001b[38;5;241m=\u001b[39m execute\u001b[38;5;241m.\u001b[39mexecute_with_cancellation(\n\u001b[1;32m 1466\u001b[0m name\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mutf-8\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 1467\u001b[0m num_outputs\u001b[38;5;241m=\u001b[39mnum_outputs,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1471\u001b[0m cancellation_manager\u001b[38;5;241m=\u001b[39mcancellation_context,\n\u001b[1;32m 1472\u001b[0m )\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/tensorflow/python/eager/execute.py:53\u001b[0m, in \u001b[0;36mquick_execute\u001b[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 52\u001b[0m ctx\u001b[38;5;241m.\u001b[39mensure_initialized()\n\u001b[0;32m---> 53\u001b[0m tensors \u001b[38;5;241m=\u001b[39m \u001b[43mpywrap_tfe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTFE_Py_Execute\u001b[49m\u001b[43m(\u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_handle\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mop_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 54\u001b[0m \u001b[43m \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_outputs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 55\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m core\u001b[38;5;241m.\u001b[39m_NotOkStatusException \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 56\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + " Checkpoint id: no-overlap/3/20240219-200103\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 3 and asking ESP for generation 4...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 3 data persisted.\n", + "Evaluated candidates:\n", + "Id: 3_44 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_68'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_44', 'origin': '2_49~CUW~1_68#MGNP'} Metrics: ['ELUC: 23.581626594584574', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.30306541142304333', 'is_elite: False']\n", + "Id: 3_38 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_14', '2_77'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_38', 'origin': '1_14~CUW~2_77#MGNP'} Metrics: ['ELUC: 19.390400176472358', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.30160296593484187', 'is_elite: False']\n", + "Id: 3_94 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_76'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_94', 'origin': '2_49~CUW~2_76#MGNP'} Metrics: ['ELUC: 17.17127039515746', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2999412779647431', 'is_elite: False']\n", + "Id: 3_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_18', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_54', 'origin': '2_18~CUW~1_1#MGNP'} Metrics: ['ELUC: 14.240066893875506', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25400907591550254', 'is_elite: False']\n", + "Id: 3_92 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_88', '1_28'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_92', 'origin': '2_88~CUW~1_28#MGNP'} Metrics: ['ELUC: 14.007092343401805', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.24417516285948504', 'is_elite: False']\n", + "Id: 3_30 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_14', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_30', 'origin': '1_14~CUW~2_17#MGNP'} Metrics: ['ELUC: 13.666200804188835', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2785387667846579', 'is_elite: False']\n", + "Id: 3_63 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_63', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 10.300709783357654', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.23572715988141635', 'is_elite: False']\n", + "Id: 3_96 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_68'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_96', 'origin': '1_56~CUW~1_68#MGNP'} Metrics: ['ELUC: 9.117390641073415', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25918261830541056', 'is_elite: False']\n", + "Id: 3_75 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_56', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_75', 'origin': '1_56~CUW~2_17#MGNP'} Metrics: ['ELUC: 8.888568360267552', 'NSGA-II_crowding_distance: 0.4109854564295528', 'NSGA-II_rank: 8', 'change: 0.2553965652713243', 'is_elite: False']\n", + "Id: 3_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_14', '2_88'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_82', 'origin': '1_14~CUW~2_88#MGNP'} Metrics: ['ELUC: 8.343427610839159', 'NSGA-II_crowding_distance: 0.6434804556238343', 'NSGA-II_rank: 9', 'change: 0.25954266099758266', 'is_elite: False']\n", + "Id: 3_83 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_65', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_83', 'origin': '1_65~CUW~2_83#MGNP'} Metrics: ['ELUC: 8.069733732428888', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 12', 'change: 0.31563228754802364', 'is_elite: False']\n", + "Id: 3_11 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_65', '2_76'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_11', 'origin': '1_65~CUW~2_76#MGNP'} Metrics: ['ELUC: 7.925397894403401', 'NSGA-II_crowding_distance: 0.23145046198233749', 'NSGA-II_rank: 8', 'change: 0.25893946874021906', 'is_elite: False']\n", + "Id: 3_45 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_68', '2_49'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_45', 'origin': '1_68~CUW~2_49#MGNP'} Metrics: ['ELUC: 7.771575805178541', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.28223202190235847', 'is_elite: False']\n", + "Id: 3_28 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_65', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_28', 'origin': '1_65~CUW~2_83#MGNP'} Metrics: ['ELUC: 7.123710794106709', 'NSGA-II_crowding_distance: 0.6200323559842408', 'NSGA-II_rank: 8', 'change: 0.26101877686580094', 'is_elite: False']\n", + "Id: 3_29 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_35'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_29', 'origin': '1_97~CUW~1_35#MGNP'} Metrics: ['ELUC: 6.893599885779186', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2509938190627419', 'is_elite: False']\n", + "Id: 3_61 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_61', 'origin': '1_97~CUW~1_1#MGNP'} Metrics: ['ELUC: 5.030431915316041', 'NSGA-II_crowding_distance: 0.7383601794544097', 'NSGA-II_rank: 5', 'change: 0.23962544394410978', 'is_elite: False']\n", + "Id: 3_89 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '1_56'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_89', 'origin': '2_87~CUW~1_56#MGNP'} Metrics: ['ELUC: 4.395516811826433', 'NSGA-II_crowding_distance: 0.4847369836007015', 'NSGA-II_rank: 7', 'change: 0.2607957328384971', 'is_elite: False']\n", + "Id: 3_59 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_14', '2_87'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_59', 'origin': '1_14~CUW~2_87#MGNP'} Metrics: ['ELUC: 3.2297204571907363', 'NSGA-II_crowding_distance: 1.1899215130940337', 'NSGA-II_rank: 6', 'change: 0.24729928564242837', 'is_elite: False']\n", + "Id: 3_86 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_86', 'origin': '2_49~CUW~2_83#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 3_99 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_18', '1_68'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_99', 'origin': '2_18~CUW~1_68#MGNP'} Metrics: ['ELUC: 2.529173963995658', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3517317578167693', 'is_elite: False']\n", + "Id: 3_18 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_56', '2_77'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_18', 'origin': '1_56~CUW~2_77#MGNP'} Metrics: ['ELUC: 2.200709011540977', 'NSGA-II_crowding_distance: 0.1629668577484518', 'NSGA-II_rank: 7', 'change: 0.2610349918832048', 'is_elite: False']\n", + "Id: 3_56 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_68', '1_56'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_56', 'origin': '1_68~CUW~1_56#MGNP'} Metrics: ['ELUC: 1.9578050729133099', 'NSGA-II_crowding_distance: 0.386846480531346', 'NSGA-II_rank: 7', 'change: 0.26131237407573465', 'is_elite: False']\n", + "Id: 3_31 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_45', '2_88'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_31', 'origin': '2_45~CUW~2_88#MGNP'} Metrics: ['ELUC: 1.3715519099227642', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3312724144745223', 'is_elite: False']\n", + "Id: 3_93 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_93', 'origin': '1_35~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.3593664738497173', 'NSGA-II_crowding_distance: 1.13151669643661', 'NSGA-II_rank: 9', 'change: 0.26710515777334626', 'is_elite: False']\n", + "Id: 3_69 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_88', '1_56'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_69', 'origin': '2_88~CUW~1_56#MGNP'} Metrics: ['ELUC: 1.0026214288693809', 'NSGA-II_crowding_distance: 1.1005640374068313', 'NSGA-II_rank: 5', 'change: 0.24451882171394268', 'is_elite: False']\n", + "Id: 3_90 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_56'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_90', 'origin': '1_65~CUW~1_56#MGNP'} Metrics: ['ELUC: 0.8739658208488736', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.23481436900957178', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 3_76 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_76', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.1700983657140764', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.030794691285073398', 'is_elite: False']\n", + "Id: 3_66 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_77', '1_56'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_66', 'origin': '2_77~CUW~1_56#MGNP'} Metrics: ['ELUC: -0.2412123251512457', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.23465130810340226', 'is_elite: False']\n", + "Id: 1_14 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_14', 'origin': '(none)'} Metrics: ['ELUC: -0.5941013652776992', 'NSGA-II_crowding_distance: 1.02466079611642', 'NSGA-II_rank: 2', 'change: 0.22774267952277133', 'is_elite: False']\n", + "Id: 3_98 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_98', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6885380054758861', 'NSGA-II_crowding_distance: 0.17853442825594623', 'NSGA-II_rank: 1', 'change: 0.022059598162328286', 'is_elite: True']\n", + "Id: 3_71 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_71', 'origin': '2_87~CUW~2_17#MGNP'} Metrics: ['ELUC: -0.7637580809964356', 'NSGA-II_crowding_distance: 0.5941481183441847', 'NSGA-II_rank: 3', 'change: 0.23954549247351148', 'is_elite: False']\n", + "Id: 3_47 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_76', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_47', 'origin': '2_76~CUW~2_17#MGNP'} Metrics: ['ELUC: -1.0409795714374892', 'NSGA-II_crowding_distance: 0.787930467005407', 'NSGA-II_rank: 6', 'change: 0.25849953586877644', 'is_elite: False']\n", + "Id: 3_51 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_97', '2_76'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_51', 'origin': '1_97~CUW~2_76#MGNP'} Metrics: ['ELUC: -1.1208110610392952', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2990704338474608', 'is_elite: False']\n", + "Id: 3_55 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_55', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1269085372614474', 'NSGA-II_crowding_distance: 1.0169434244958968', 'NSGA-II_rank: 1', 'change: 0.03904482046624399', 'is_elite: True']\n", + "Id: 3_79 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_56', '2_87'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_79', 'origin': '1_56~CUW~2_87#MGNP'} Metrics: ['ELUC: -2.242361580493923', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3159230532977425', 'is_elite: False']\n", + "Id: 3_91 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_77', '1_35'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_91', 'origin': '2_77~CUW~1_35#MGNP'} Metrics: ['ELUC: -2.394303045431676', 'NSGA-II_crowding_distance: 0.9355074151015847', 'NSGA-II_rank: 8', 'change: 0.2651178223828831', 'is_elite: False']\n", + "Id: 3_97 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_35', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_97', 'origin': '1_35~CUW~2_17#MGNP'} Metrics: ['ELUC: -2.8298952151270194', 'NSGA-II_crowding_distance: 0.7361646207470379', 'NSGA-II_rank: 7', 'change: 0.2647747585356922', 'is_elite: False']\n", + "Id: 3_26 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_68', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_26', 'origin': '1_68~CUW~2_17#MGNP'} Metrics: ['ELUC: -3.309113329181717', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3142575325225733', 'is_elite: False']\n", + "Id: 3_78 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_76', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_78', 'origin': '2_76~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.070887385855641', 'NSGA-II_crowding_distance: 0.26345679122472426', 'NSGA-II_rank: 6', 'change: 0.2598447706015179', 'is_elite: False']\n", + "Id: 3_15 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_77', '2_76'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_15', 'origin': '2_77~CUW~2_76#MGNP'} Metrics: ['ELUC: -4.358339989639604', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.29503427238136987', 'is_elite: False']\n", + "Id: 1_65 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_65', 'origin': '(none)'} Metrics: ['ELUC: -4.852359001151172', 'NSGA-II_crowding_distance: 0.4042961109874737', 'NSGA-II_rank: 2', 'change: 0.234700850215592', 'is_elite: False']\n", + "Id: 3_36 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_88', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_36', 'origin': '2_88~CUW~2_83#MGNP'} Metrics: ['ELUC: -4.963988194609782', 'NSGA-II_crowding_distance: 0.8667708409797998', 'NSGA-II_rank: 9', 'change: 0.27437589809947555', 'is_elite: False']\n", + "Id: 3_88 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_18', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_88', 'origin': '2_18~CUW~2_83#MGNP'} Metrics: ['ELUC: -5.42710439535783', 'NSGA-II_crowding_distance: 0.8138895809706794', 'NSGA-II_rank: 9', 'change: 0.2876546420006148', 'is_elite: False']\n", + "Id: 3_34 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_45', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_34', 'origin': '2_45~CUW~2_17#MGNP'} Metrics: ['ELUC: -5.431947684642587', 'NSGA-II_crowding_distance: 0.817322404778859', 'NSGA-II_rank: 3', 'change: 0.2465278203123467', 'is_elite: False']\n", + "Id: 3_87 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_88', '1_56'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_87', 'origin': '2_88~CUW~1_56#MGNP'} Metrics: ['ELUC: -5.779456651572357', 'NSGA-II_crowding_distance: 0.19852981490928273', 'NSGA-II_rank: 6', 'change: 0.26005490963775535', 'is_elite: False']\n", + "Id: 3_52 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_77', '2_88'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_52', 'origin': '2_77~CUW~2_88#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.23816666711344098', 'NSGA-II_rank: 6', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 3_74 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_14'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_74', 'origin': '1_1~CUW~1_14#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.30845502856780116', 'NSGA-II_rank: 6', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 3_35 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_35', 'origin': '1_65~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.089915455861103', 'NSGA-II_crowding_distance: 1.0097351462131443', 'NSGA-II_rank: 1', 'change: 0.23382981294598923', 'is_elite: True']\n", + "Id: 3_49 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_76', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_49', 'origin': '2_76~CUW~2_83#MGNP'} Metrics: ['ELUC: -6.193637156608289', 'NSGA-II_crowding_distance: 0.6700236080630693', 'NSGA-II_rank: 8', 'change: 0.27391983611054216', 'is_elite: False']\n", + "Id: 3_43 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_77', '1_97'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_43', 'origin': '2_77~CUW~1_97#MGNP'} Metrics: ['ELUC: -6.45146597760259', 'NSGA-II_crowding_distance: 0.3311879371175288', 'NSGA-II_rank: 2', 'change: 0.2406431070720598', 'is_elite: False']\n", + "Id: 3_12 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_45', '1_65'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_12', 'origin': '2_45~CUW~1_65#MGNP'} Metrics: ['ELUC: -6.834458622787717', 'NSGA-II_crowding_distance: 1.1344542257694066', 'NSGA-II_rank: 5', 'change: 0.25619382158242043', 'is_elite: False']\n", + "Id: 3_48 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_14', '2_44'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_48', 'origin': '1_14~CUW~2_44#MGNP'} Metrics: ['ELUC: -6.90838348728902', 'NSGA-II_crowding_distance: 0.6093907000948559', 'NSGA-II_rank: 7', 'change: 0.27077965559699424', 'is_elite: False']\n", + "Id: 3_37 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_77', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_37', 'origin': '2_77~CUW~2_83#MGNP'} Metrics: ['ELUC: -7.08061164857179', 'NSGA-II_crowding_distance: 0.332898839481728', 'NSGA-II_rank: 1', 'change: 0.23929110897642963', 'is_elite: True']\n", + "Id: 3_95 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '1_35'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_95', 'origin': '2_83~CUW~1_35#MGNP'} Metrics: ['ELUC: -7.50541687896834', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30400075475196453', 'is_elite: False']\n", + "Id: 3_16 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_56', '2_45'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_16', 'origin': '1_56~CUW~2_45#MGNP'} Metrics: ['ELUC: -8.058442831106118', 'NSGA-II_crowding_distance: 0.3126795926290574', 'NSGA-II_rank: 8', 'change: 0.2805117387340608', 'is_elite: False']\n", + "Id: 3_42 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_35'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_42', 'origin': '1_56~CUW~1_35#MGNP'} Metrics: ['ELUC: -8.264021939780623', 'NSGA-II_crowding_distance: 0.18676526640874458', 'NSGA-II_rank: 8', 'change: 0.282013791337098', 'is_elite: False']\n", + "Id: 3_21 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_56', '1_35'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_21', 'origin': '1_56~CUW~1_35#MGNP'} Metrics: ['ELUC: -8.320971975203008', 'NSGA-II_crowding_distance: 0.5130427542205734', 'NSGA-II_rank: 5', 'change: 0.2666458162447725', 'is_elite: False']\n", + "Id: 3_67 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_88', '2_44'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_67', 'origin': '2_88~CUW~2_44#MGNP'} Metrics: ['ELUC: -8.398237055598578', 'NSGA-II_crowding_distance: 1.5890988510076873', 'NSGA-II_rank: 4', 'change: 0.2513234295238864', 'is_elite: False']\n", + "Id: 3_23 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_88', '2_49'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_23', 'origin': '2_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.595814365599008', 'NSGA-II_crowding_distance: 0.2487275349388347', 'NSGA-II_rank: 8', 'change: 0.2864571568059383', 'is_elite: False']\n", + "Id: 3_39 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '1_14'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_39', 'origin': '2_83~CUW~1_14#MGNP'} Metrics: ['ELUC: -8.676425721414581', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.29041342491516037', 'is_elite: False']\n", + "Id: 3_46 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_17', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_46', 'origin': '2_17~CUW~2_83#MGNP'} Metrics: ['ELUC: -8.823286850302472', 'NSGA-II_crowding_distance: 0.7567197845891394', 'NSGA-II_rank: 7', 'change: 0.2770866062206401', 'is_elite: False']\n", + "Id: 3_17 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_76'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_17', 'origin': '1_1~CUW~2_76#MGNP'} Metrics: ['ELUC: -9.016201617867651', 'NSGA-II_crowding_distance: 0.5190258357730966', 'NSGA-II_rank: 7', 'change: 0.3038038646802165', 'is_elite: False']\n", + "Id: 3_53 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_53', 'origin': '2_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 1_68 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_68', 'origin': '(none)'} Metrics: ['ELUC: -9.050669260168299', 'NSGA-II_crowding_distance: 0.4439579588528072', 'NSGA-II_rank: 3', 'change: 0.2511738280516456', 'is_elite: False']\n", + "Id: 3_40 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_45', '2_87'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_40', 'origin': '2_45~CUW~2_87#MGNP'} Metrics: ['ELUC: -9.117438120927998', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2707420792855236', 'is_elite: False']\n", + "Id: 3_24 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_24', 'origin': '2_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.147714112502587', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2695060848013632', 'is_elite: False']\n", + "Id: 3_81 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_77', '1_14'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_81', 'origin': '2_77~CUW~1_14#MGNP'} Metrics: ['ELUC: -9.517028775547065', 'NSGA-II_crowding_distance: 0.8036820131220686', 'NSGA-II_rank: 4', 'change: 0.26413643575877005', 'is_elite: False']\n", + "Id: 3_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '2_49'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_72', 'origin': '2_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.66563542848894', 'NSGA-II_crowding_distance: 0.29058627092363387', 'NSGA-II_rank: 2', 'change: 0.24501431393601159', 'is_elite: False']\n", + "Id: 3_62 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_68', '1_68'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_62', 'origin': '1_68~CUW~1_68#MGNP'} Metrics: ['ELUC: -9.692616687971018', 'NSGA-II_crowding_distance: 0.5214587806035123', 'NSGA-II_rank: 3', 'change: 0.25383275389073034', 'is_elite: False']\n", + "Id: 3_32 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '1_35'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_32', 'origin': '2_87~CUW~1_35#MGNP'} Metrics: ['ELUC: -10.470984784456704', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.27837157244004324', 'is_elite: False']\n", + "Id: 3_50 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '2_87'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_50', 'origin': '2_87~CUW~2_87#MGNP'} Metrics: ['ELUC: -10.6141639756739', 'NSGA-II_crowding_distance: 0.10737763919665622', 'NSGA-II_rank: 2', 'change: 0.2507114222357577', 'is_elite: False']\n", + "Id: 3_60 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_35', '2_77'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_60', 'origin': '1_35~CUW~2_77#MGNP'} Metrics: ['ELUC: -10.902837610572918', 'NSGA-II_crowding_distance: 0.7666145802140336', 'NSGA-II_rank: 3', 'change: 0.2727027272438718', 'is_elite: False']\n", + "Id: 2_87 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_14'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_87', 'origin': '1_28~CUW~1_14#MGNP'} Metrics: ['ELUC: -11.038544889744824', 'NSGA-II_crowding_distance: 0.16238855801710111', 'NSGA-II_rank: 2', 'change: 0.2515194286694687', 'is_elite: False']\n", + "Id: 3_13 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_13', 'origin': '2_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.317475233272496', 'NSGA-II_crowding_distance: 0.468504819923643', 'NSGA-II_rank: 1', 'change: 0.24444610739942754', 'is_elite: True']\n", + "Id: 2_17 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_20', '1_28'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_17', 'origin': '1_20~CUW~1_28#MGNP'} Metrics: ['ELUC: -11.960152905922111', 'NSGA-II_crowding_distance: 0.13806165862055947', 'NSGA-II_rank: 2', 'change: 0.27285204288836606', 'is_elite: False']\n", + "Id: 3_41 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_35', '2_45'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_41', 'origin': '1_35~CUW~2_45#MGNP'} Metrics: ['ELUC: -11.965279509002775', 'NSGA-II_crowding_distance: 0.12163773274596909', 'NSGA-II_rank: 2', 'change: 0.2740093652895525', 'is_elite: False']\n", + "Id: 3_65 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_17', '2_49'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_65', 'origin': '2_17~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.161228099476798', 'NSGA-II_crowding_distance: 0.5352140136662409', 'NSGA-II_rank: 3', 'change: 0.2865278371055059', 'is_elite: False']\n", + "Id: 3_22 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '2_76'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_22', 'origin': '2_83~CUW~2_76#MGNP'} Metrics: ['ELUC: -13.672005255673538', 'NSGA-II_crowding_distance: 0.23587116096608984', 'NSGA-II_rank: 1', 'change: 0.2672245255498373', 'is_elite: True']\n", + "Id: 3_14 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_45', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_14', 'origin': '2_45~CUW~2_83#MGNP'} Metrics: ['ELUC: -13.71025226314423', 'NSGA-II_crowding_distance: 0.19426913747034918', 'NSGA-II_rank: 2', 'change: 0.2769382418875063', 'is_elite: False']\n", + "Id: 1_35 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_35', 'origin': '(none)'} Metrics: ['ELUC: -13.843850666566142', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29052751716329306', 'is_elite: False']\n", + "Id: 3_80 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '1_35'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_80', 'origin': '2_87~CUW~1_35#MGNP'} Metrics: ['ELUC: -13.995530336654365', 'NSGA-II_crowding_distance: 0.09917860993243698', 'NSGA-II_rank: 1', 'change: 0.2693773849000996', 'is_elite: False']\n", + "Id: 3_27 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_56', '2_87'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_27', 'origin': '1_56~CUW~2_87#MGNP'} Metrics: ['ELUC: -14.57272273990727', 'NSGA-II_crowding_distance: 0.1546958244478489', 'NSGA-II_rank: 2', 'change: 0.28369698854908865', 'is_elite: False']\n", + "Id: 3_19 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_76', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_19', 'origin': '2_76~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.072644049629101', 'NSGA-II_crowding_distance: 0.15632435171906225', 'NSGA-II_rank: 1', 'change: 0.2730479405308912', 'is_elite: True']\n", + "Id: 1_56 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_56', 'origin': '(none)'} Metrics: ['ELUC: -15.35517983317119', 'NSGA-II_crowding_distance: 0.20444283147848624', 'NSGA-II_rank: 2', 'change: 0.29191965976244105', 'is_elite: False']\n", + "Id: 3_77 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_77', 'origin': '2_83~CUW~2_17#MGNP'} Metrics: ['ELUC: -15.698658431553602', 'NSGA-II_crowding_distance: 0.14567712349999168', 'NSGA-II_rank: 1', 'change: 0.2871184790470956', 'is_elite: False']\n", + "Id: 3_85 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_45', '2_49'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_85', 'origin': '2_45~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.534768367460153', 'NSGA-II_crowding_distance: 0.07699872224426427', 'NSGA-II_rank: 1', 'change: 0.2917020474239358', 'is_elite: False']\n", + "Id: 3_64 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_64', 'origin': '2_49~CUW~2_83#MGNP'} Metrics: ['ELUC: -16.538573147208794', 'NSGA-II_crowding_distance: 0.04559190138444722', 'NSGA-II_rank: 1', 'change: 0.2958395702405923', 'is_elite: False']\n", + "Id: 3_84 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_76', '2_76'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_84', 'origin': '2_76~CUW~2_76#MGNP'} Metrics: ['ELUC: -16.55194055965477', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30677593394509906', 'is_elite: False']\n", + "Id: 3_20 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_17', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_20', 'origin': '2_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.072571594196813', 'NSGA-II_crowding_distance: 0.07057842436430765', 'NSGA-II_rank: 1', 'change: 0.2961789682615571', 'is_elite: False']\n", + "Id: 3_68 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_17', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_68', 'origin': '2_17~CUW~2_83#MGNP'} Metrics: ['ELUC: -17.493688601058647', 'NSGA-II_crowding_distance: 0.05247459520316276', 'NSGA-II_rank: 1', 'change: 0.30068999559874926', 'is_elite: False']\n", + "Id: 3_33 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_68', '1_14'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_33', 'origin': '1_68~CUW~1_14#MGNP'} Metrics: ['ELUC: -17.592585431495372', 'NSGA-II_crowding_distance: 0.013708321293072279', 'NSGA-II_rank: 1', 'change: 0.30301142297041667', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 2_83 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_97', '1_88'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_83', 'origin': '1_97~CUW~1_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 3_25 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '2_17'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_25', 'origin': '2_87~CUW~2_17#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 3_57 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_65'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_57', 'origin': '2_49~CUW~1_65#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 3_58 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_58', 'origin': '2_83~CUW~2_83#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 3_70 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_70', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 3_73 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_35', '1_65'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_73', 'origin': '1_35~CUW~1_65#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 3_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_100', 'origin': '2_83~CUW~2_83#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 3.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 4...:\n", + "PopulationResponse:\n", + " Generation: 4\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/4/20240219-200819\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 4 and asking ESP for generation 5...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 4 data persisted.\n", + "Evaluated candidates:\n", + "Id: 4_52 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_100', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_52', 'origin': '3_100~CUW~3_35#MGNP'} Metrics: ['ELUC: 20.657409185367264', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.28787681830186784', 'is_elite: False']\n", + "Id: 4_77 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_35', '3_19'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_77', 'origin': '3_35~CUW~3_19#MGNP'} Metrics: ['ELUC: 11.175570656905682', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.27429122185897836', 'is_elite: False']\n", + "Id: 4_83 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_80', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_83', 'origin': '3_80~CUW~3_55#MGNP'} Metrics: ['ELUC: 8.038081337834203', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2627443518337797', 'is_elite: False']\n", + "Id: 4_56 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_77'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_56', 'origin': '3_19~CUW~3_77#MGNP'} Metrics: ['ELUC: 5.543395029926811', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2427911480607306', 'is_elite: False']\n", + "Id: 4_59 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_20'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_59', 'origin': '3_37~CUW~3_20#MGNP'} Metrics: ['ELUC: 3.927400001591632', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.240147421065101', 'is_elite: False']\n", + "Id: 4_45 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_80'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_45', 'origin': '3_19~CUW~3_80#MGNP'} Metrics: ['ELUC: 2.527915957306169', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3517139186565538', 'is_elite: False']\n", + "Id: 4_54 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_54', 'origin': '3_19~CUW~3_35#MGNP'} Metrics: ['ELUC: 1.537631014319403', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2167658640978891', 'is_elite: False']\n", + "Id: 4_40 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_13', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_40', 'origin': '3_13~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.4891117706390586', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2636724243636307', 'is_elite: False']\n", + "Id: 4_87 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_87', 'origin': '3_19~CUW~3_35#MGNP'} Metrics: ['ELUC: 1.0473286038150016', 'NSGA-II_crowding_distance: 0.20679599618077837', 'NSGA-II_rank: 4', 'change: 0.2277137544218624', 'is_elite: False']\n", + "Id: 4_19 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_19', 'origin': '3_19~CUW~3_35#MGNP'} Metrics: ['ELUC: 0.8619525622272778', 'NSGA-II_crowding_distance: 0.3730206000208713', 'NSGA-II_rank: 4', 'change: 0.23224882729966342', 'is_elite: False']\n", + "Id: 4_74 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_68', '3_22'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_74', 'origin': '3_68~CUW~3_22#MGNP'} Metrics: ['ELUC: 0.6709854748831854', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2347265934652551', 'is_elite: False']\n", + "Id: 4_70 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_70', 'origin': '1_1~CUW~3_55#MGNP'} Metrics: ['ELUC: 0.3464276222127778', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04154755673235932', 'is_elite: False']\n", + "Id: 4_50 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_55', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_50', 'origin': '3_55~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.19513989577050525', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03886340756483249', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 4_89 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_55', '2_83'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_89', 'origin': '3_55~CUW~2_83#MGNP'} Metrics: ['ELUC: -0.025517301197160207', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.2907164301069126', 'is_elite: False']\n", + "Id: 4_73 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_73', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.11647179389163016', 'NSGA-II_crowding_distance: 0.0997055534077948', 'NSGA-II_rank: 2', 'change: 0.04187723198925693', 'is_elite: False']\n", + "Id: 4_33 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_98', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_33', 'origin': '3_98~CUW~3_55#MGNP'} Metrics: ['ELUC: -0.47960605462210104', 'NSGA-II_crowding_distance: 0.9121721862700601', 'NSGA-II_rank: 2', 'change: 0.055182998262492546', 'is_elite: False']\n", + "Id: 3_98 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_98', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6885380054758861', 'NSGA-II_crowding_distance: 0.17853442825594623', 'NSGA-II_rank: 1', 'change: 0.022059598162328286', 'is_elite: False']\n", + "Id: 3_55 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_55', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1269085372614474', 'NSGA-II_crowding_distance: 0.7443810957534511', 'NSGA-II_rank: 1', 'change: 0.03904482046624399', 'is_elite: True']\n", + "Id: 4_98 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_35', '3_100'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_98', 'origin': '3_35~CUW~3_100#MGNP'} Metrics: ['ELUC: -2.504659888698139', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2721662998115822', 'is_elite: False']\n", + "Id: 4_24 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_20', '3_98'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_24', 'origin': '3_20~CUW~3_98#MGNP'} Metrics: ['ELUC: -2.66066065044801', 'NSGA-II_crowding_distance: 0.7983483381366289', 'NSGA-II_rank: 1', 'change: 0.21069879910559858', 'is_elite: True']\n", + "Id: 4_75 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_33', '3_100'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_75', 'origin': '3_33~CUW~3_100#MGNP'} Metrics: ['ELUC: -2.678592277138843', 'NSGA-II_crowding_distance: 0.8791844899826828', 'NSGA-II_rank: 12', 'change: 0.27225958279391976', 'is_elite: False']\n", + "Id: 4_22 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_35', '3_37'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_22', 'origin': '3_35~CUW~3_37#MGNP'} Metrics: ['ELUC: -2.852761979023336', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.23766937582311495', 'is_elite: False']\n", + "Id: 4_12 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_12', 'origin': '3_37~CUW~3_55#MGNP'} Metrics: ['ELUC: -2.910927064010386', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 13', 'change: 0.2767360503058449', 'is_elite: False']\n", + "Id: 4_31 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_98'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_31', 'origin': '3_37~CUW~3_98#MGNP'} Metrics: ['ELUC: -3.2838484626725584', 'NSGA-II_crowding_distance: 0.3196376002367216', 'NSGA-II_rank: 6', 'change: 0.2388119336961182', 'is_elite: False']\n", + "Id: 4_97 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_100', '3_22'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_97', 'origin': '3_100~CUW~3_22#MGNP'} Metrics: ['ELUC: -3.859293683881095', 'NSGA-II_crowding_distance: 0.5517754964911545', 'NSGA-II_rank: 6', 'change: 0.24426353217712593', 'is_elite: False']\n", + "Id: 4_42 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '3_100'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_42', 'origin': '1_1~CUW~3_100#MGNP'} Metrics: ['ELUC: -3.940040446950254', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.26836781533615084', 'is_elite: False']\n", + "Id: 4_43 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_100', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_43', 'origin': '3_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.977022430356466', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.28866795376669', 'is_elite: False']\n", + "Id: 4_88 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_80', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_88', 'origin': '3_80~CUW~3_35#MGNP'} Metrics: ['ELUC: -4.046797514916983', 'NSGA-II_crowding_distance: 1.2678573726650477', 'NSGA-II_rank: 8', 'change: 0.2566313910497456', 'is_elite: False']\n", + "Id: 4_81 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_100'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_81', 'origin': '3_19~CUW~3_100#MGNP'} Metrics: ['ELUC: -4.082998624254357', 'NSGA-II_crowding_distance: 1.9052491499119464', 'NSGA-II_rank: 12', 'change: 0.2732892101693954', 'is_elite: False']\n", + "Id: 4_51 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_35', '3_57'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_51', 'origin': '3_35~CUW~3_57#MGNP'} Metrics: ['ELUC: -4.2104367939559495', 'NSGA-II_crowding_distance: 1.2401822381742085', 'NSGA-II_rank: 7', 'change: 0.25546439697671086', 'is_elite: False']\n", + "Id: 4_82 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_80', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_82', 'origin': '3_80~CUW~3_55#MGNP'} Metrics: ['ELUC: -4.294369466201064', 'NSGA-II_crowding_distance: 0.9957721718084421', 'NSGA-II_rank: 2', 'change: 0.2208041356836636', 'is_elite: False']\n", + "Id: 4_57 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '3_100'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_57', 'origin': '2_49~CUW~3_100#MGNP'} Metrics: ['ELUC: -4.327191443170903', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2708499936291144', 'is_elite: False']\n", + "Id: 4_85 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_13'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_85', 'origin': '3_37~CUW~3_13#MGNP'} Metrics: ['ELUC: -4.343886479761472', 'NSGA-II_crowding_distance: 0.7534606473258302', 'NSGA-II_rank: 5', 'change: 0.23677406650032246', 'is_elite: False']\n", + "Id: 4_61 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_77', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_61', 'origin': '3_77~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.476395859277211', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.28643404834057423', 'is_elite: False']\n", + "Id: 4_92 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_92', 'origin': '3_37~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.532469494581038', 'NSGA-II_crowding_distance: 0.5749203429112388', 'NSGA-II_rank: 4', 'change: 0.23439514448928359', 'is_elite: False']\n", + "Id: 4_21 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_80'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_21', 'origin': '3_37~CUW~3_80#MGNP'} Metrics: ['ELUC: -4.627570960301259', 'NSGA-II_crowding_distance: 0.4159181490301276', 'NSGA-II_rank: 5', 'change: 0.25044322697610005', 'is_elite: False']\n", + "Id: 4_11 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_20', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_11', 'origin': '3_20~CUW~3_55#MGNP'} Metrics: ['ELUC: -4.761299281658512', 'NSGA-II_crowding_distance: 0.41057293996703204', 'NSGA-II_rank: 1', 'change: 0.21557744193799955', 'is_elite: True']\n", + "Id: 4_79 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_20', '3_37'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_79', 'origin': '3_20~CUW~3_37#MGNP'} Metrics: ['ELUC: -4.912593254164097', 'NSGA-II_crowding_distance: 0.734560050915291', 'NSGA-II_rank: 6', 'change: 0.25089345239515337', 'is_elite: False']\n", + "Id: 4_27 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_13', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_27', 'origin': '3_13~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.178559192643543', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27957451305341935', 'is_elite: False']\n", + "Id: 4_53 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '3_13'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_53', 'origin': '2_49~CUW~3_13#MGNP'} Metrics: ['ELUC: -5.498127026914961', 'NSGA-II_crowding_distance: 0.2682379542074965', 'NSGA-II_rank: 7', 'change: 0.26030527354970645', 'is_elite: False']\n", + "Id: 4_44 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_35', '2_49'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_44', 'origin': '3_35~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.600557197527178', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27040626104448723', 'is_elite: False']\n", + "Id: 4_60 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_68'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_60', 'origin': '3_37~CUW~3_68#MGNP'} Metrics: ['ELUC: -5.745127217732967', 'NSGA-II_crowding_distance: 0.09899820180215566', 'NSGA-II_rank: 7', 'change: 0.26211562668867394', 'is_elite: False']\n", + "Id: 4_35 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_100', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_35', 'origin': '3_100~CUW~3_55#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 4_47 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_85', '3_19'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_47', 'origin': '3_85~CUW~3_19#MGNP'} Metrics: ['ELUC: -6.044415732673555', 'NSGA-II_crowding_distance: 0.9986487640096228', 'NSGA-II_rank: 8', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 4_30 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_35', '3_80'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_30', 'origin': '3_35~CUW~3_80#MGNP'} Metrics: ['ELUC: -6.044434816544937', 'NSGA-II_crowding_distance: 0.04263898746427655', 'NSGA-II_rank: 7', 'change: 0.2628514141577488', 'is_elite: False']\n", + "Id: 4_38 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_100', '2_49'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_38', 'origin': '3_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.047338910791868', 'NSGA-II_crowding_distance: 0.6608195600236357', 'NSGA-II_rank: 7', 'change: 0.2629080215502482', 'is_elite: False']\n", + "Id: 4_95 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_35', '3_13'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_95', 'origin': '3_35~CUW~3_13#MGNP'} Metrics: ['ELUC: -6.085640973460275', 'NSGA-II_crowding_distance: 0.6597601589429982', 'NSGA-II_rank: 6', 'change: 0.2599745714063032', 'is_elite: False']\n", + "Id: 3_35 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_65', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_35', 'origin': '1_65~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.089915455861103', 'NSGA-II_crowding_distance: 1.12603219197969', 'NSGA-II_rank: 3', 'change: 0.23382981294598923', 'is_elite: False']\n", + "Id: 4_84 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_35', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_84', 'origin': '3_35~CUW~3_35#MGNP'} Metrics: ['ELUC: -6.174916231871651', 'NSGA-II_crowding_distance: 0.16885257453730565', 'NSGA-II_rank: 2', 'change: 0.2336626905289338', 'is_elite: False']\n", + "Id: 4_46 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_46', 'origin': '1_1~CUW~3_35#MGNP'} Metrics: ['ELUC: -6.2011267718526195', 'NSGA-II_crowding_distance: 0.9458023488479876', 'NSGA-II_rank: 6', 'change: 0.2695695557383046', 'is_elite: False']\n", + "Id: 4_91 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_91', 'origin': '3_37~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.206145715735089', 'NSGA-II_crowding_distance: 0.053975170243730046', 'NSGA-II_rank: 3', 'change: 0.24051990795421285', 'is_elite: False']\n", + "Id: 4_15 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_13', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_15', 'origin': '3_13~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.356913093029524', 'NSGA-II_crowding_distance: 0.6018724009983507', 'NSGA-II_rank: 5', 'change: 0.2504748738188025', 'is_elite: False']\n", + "Id: 4_49 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_35', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_49', 'origin': '3_35~CUW~3_35#MGNP'} Metrics: ['ELUC: -6.4016080209988395', 'NSGA-II_crowding_distance: 0.07221524127990761', 'NSGA-II_rank: 2', 'change: 0.23411950462755046', 'is_elite: False']\n", + "Id: 4_86 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_86', 'origin': '3_19~CUW~3_35#MGNP'} Metrics: ['ELUC: -6.513843726543443', 'NSGA-II_crowding_distance: 0.06417869404066834', 'NSGA-II_rank: 3', 'change: 0.2417659059967009', 'is_elite: False']\n", + "Id: 4_58 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_35', '3_98'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_58', 'origin': '3_35~CUW~3_98#MGNP'} Metrics: ['ELUC: -6.592909564871701', 'NSGA-II_crowding_distance: 0.32959743223393195', 'NSGA-II_rank: 4', 'change: 0.24812521263459908', 'is_elite: False']\n", + "Id: 4_90 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '3_37'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_90', 'origin': '1_1~CUW~3_37#MGNP'} Metrics: ['ELUC: -7.012544849734749', 'NSGA-II_crowding_distance: 0.14309130056217015', 'NSGA-II_rank: 3', 'change: 0.24554824560245223', 'is_elite: False']\n", + "Id: 4_20 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_20', 'origin': '3_19~CUW~3_35#MGNP'} Metrics: ['ELUC: -7.056453726966611', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3004070431405234', 'is_elite: False']\n", + "Id: 3_37 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_77', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_37', 'origin': '2_77~CUW~2_83#MGNP'} Metrics: ['ELUC: -7.08061164857179', 'NSGA-II_crowding_distance: 0.11964154004507684', 'NSGA-II_rank: 2', 'change: 0.23929110897642963', 'is_elite: False']\n", + "Id: 4_39 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_35', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_39', 'origin': '3_35~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.247600613853058', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29095682521766214', 'is_elite: False']\n", + "Id: 4_28 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_100'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_28', 'origin': '3_37~CUW~3_100#MGNP'} Metrics: ['ELUC: -7.40709856815206', 'NSGA-II_crowding_distance: 0.40854129332730127', 'NSGA-II_rank: 4', 'change: 0.2503138294681548', 'is_elite: False']\n", + "Id: 4_67 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '3_35'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_67', 'origin': '2_49~CUW~3_35#MGNP'} Metrics: ['ELUC: -7.597878126912641', 'NSGA-II_crowding_distance: 0.5987903336735905', 'NSGA-II_rank: 5', 'change: 0.26995396416408535', 'is_elite: False']\n", + "Id: 4_68 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_100', '3_57'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_68', 'origin': '3_100~CUW~3_57#MGNP'} Metrics: ['ELUC: -8.0570414520422', 'NSGA-II_crowding_distance: 0.2576662210689601', 'NSGA-II_rank: 2', 'change: 0.24114374459745663', 'is_elite: False']\n", + "Id: 4_93 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_22'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_93', 'origin': '3_37~CUW~3_22#MGNP'} Metrics: ['ELUC: -8.30271424534995', 'NSGA-II_crowding_distance: 0.27842965586370494', 'NSGA-II_rank: 5', 'change: 0.2754478800165371', 'is_elite: False']\n", + "Id: 4_29 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_98', '3_22'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_29', 'origin': '3_98~CUW~3_22#MGNP'} Metrics: ['ELUC: -8.631969900884512', 'NSGA-II_crowding_distance: 0.16021477693411568', 'NSGA-II_rank: 3', 'change: 0.24830846850070612', 'is_elite: False']\n", + "Id: 4_32 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_80', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_32', 'origin': '3_80~CUW~3_55#MGNP'} Metrics: ['ELUC: -8.662381477457489', 'NSGA-II_crowding_distance: 0.3047895918799652', 'NSGA-II_rank: 1', 'change: 0.23135356254458647', 'is_elite: True']\n", + "Id: 4_69 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_22', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_69', 'origin': '3_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.915073860402702', 'NSGA-II_crowding_distance: 0.18881687079797083', 'NSGA-II_rank: 1', 'change: 0.23602902906673193', 'is_elite: True']\n", + "Id: 4_26 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_13', '3_33'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_26', 'origin': '3_13~CUW~3_33#MGNP'} Metrics: ['ELUC: -9.21542471937894', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2785141955921837', 'is_elite: False']\n", + "Id: 4_72 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_13', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_72', 'origin': '3_13~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.219245525233008', 'NSGA-II_crowding_distance: 0.1953704894802909', 'NSGA-II_rank: 3', 'change: 0.2552779639954783', 'is_elite: False']\n", + "Id: 4_23 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_23', 'origin': '3_19~CUW~3_55#MGNP'} Metrics: ['ELUC: -9.365657711804092', 'NSGA-II_crowding_distance: 0.235073627336818', 'NSGA-II_rank: 5', 'change: 0.2768100918327249', 'is_elite: False']\n", + "Id: 4_13 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_13', '3_98'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_13', 'origin': '3_13~CUW~3_98#MGNP'} Metrics: ['ELUC: -9.780195219545364', 'NSGA-II_crowding_distance: 0.36623729581211417', 'NSGA-II_rank: 5', 'change: 0.28131920768107516', 'is_elite: False']\n", + "Id: 4_99 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_35', '2_49'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_99', 'origin': '3_35~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.146364467077365', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2943404852133131', 'is_elite: False']\n", + "Id: 4_16 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_85', '3_33'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_16', 'origin': '3_85~CUW~3_33#MGNP'} Metrics: ['ELUC: -10.15200846068551', 'NSGA-II_crowding_distance: 0.3813920932957955', 'NSGA-II_rank: 4', 'change: 0.2678764085018883', 'is_elite: False']\n", + "Id: 4_65 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_22', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_65', 'origin': '3_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.793457237249465', 'NSGA-II_crowding_distance: 0.8097423675806815', 'NSGA-II_rank: 4', 'change: 0.26844176055490937', 'is_elite: False']\n", + "Id: 4_36 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_77', '3_37'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_36', 'origin': '3_77~CUW~3_37#MGNP'} Metrics: ['ELUC: -11.2641838155334', 'NSGA-II_crowding_distance: 0.3296478810933587', 'NSGA-II_rank: 3', 'change: 0.2610290168277427', 'is_elite: False']\n", + "Id: 3_13 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_87', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_13', 'origin': '2_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.317475233272496', 'NSGA-II_crowding_distance: 0.5026824301244026', 'NSGA-II_rank: 2', 'change: 0.24444610739942754', 'is_elite: False']\n", + "Id: 4_63 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_98', '3_19'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_63', 'origin': '3_98~CUW~3_19#MGNP'} Metrics: ['ELUC: -11.619438827630509', 'NSGA-II_crowding_distance: 0.30286040623376304', 'NSGA-II_rank: 1', 'change: 0.23751013438589627', 'is_elite: True']\n", + "Id: 4_25 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_22', '3_19'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_25', 'origin': '3_22~CUW~3_19#MGNP'} Metrics: ['ELUC: -12.76599072488195', 'NSGA-II_crowding_distance: 0.21632673243870076', 'NSGA-II_rank: 1', 'change: 0.2610445789338331', 'is_elite: True']\n", + "Id: 4_94 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_100', '3_64'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_94', 'origin': '3_100~CUW~3_64#MGNP'} Metrics: ['ELUC: -13.670202796361377', 'NSGA-II_crowding_distance: 0.28519611843813264', 'NSGA-II_rank: 3', 'change: 0.27660085014484165', 'is_elite: False']\n", + "Id: 3_22 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '2_76'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_22', 'origin': '2_83~CUW~2_76#MGNP'} Metrics: ['ELUC: -13.672005255673538', 'NSGA-II_crowding_distance: 0.17142023981886723', 'NSGA-II_rank: 1', 'change: 0.2672245255498373', 'is_elite: False']\n", + "Id: 4_62 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_33', '3_13'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_62', 'origin': '3_33~CUW~3_13#MGNP'} Metrics: ['ELUC: -14.478597839372641', 'NSGA-II_crowding_distance: 0.31992645595216707', 'NSGA-II_rank: 3', 'change: 0.2887545906774823', 'is_elite: False']\n", + "Id: 4_48 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_77', '3_37'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_48', 'origin': '3_77~CUW~3_37#MGNP'} Metrics: ['ELUC: -14.633990488561862', 'NSGA-II_crowding_distance: 0.4164823295012794', 'NSGA-II_rank: 2', 'change: 0.2762763179709457', 'is_elite: False']\n", + "Id: 3_19 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_76', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_19', 'origin': '2_76~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.072644049629101', 'NSGA-II_crowding_distance: 0.15992508069395467', 'NSGA-II_rank: 1', 'change: 0.2730479405308912', 'is_elite: False']\n", + "Id: 4_18 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '2_49'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_18', 'origin': '3_19~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.225884250949598', 'NSGA-II_crowding_distance: 0.26772679606676447', 'NSGA-II_rank: 2', 'change: 0.2964315140646634', 'is_elite: False']\n", + "Id: 4_96 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_35', '3_100'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_96', 'origin': '3_35~CUW~3_100#MGNP'} Metrics: ['ELUC: -15.485363742307213', 'NSGA-II_crowding_distance: 0.13731836605905126', 'NSGA-II_rank: 1', 'change: 0.2841693532612425', 'is_elite: False']\n", + "Id: 4_76 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_19'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_76', 'origin': '3_19~CUW~3_19#MGNP'} Metrics: ['ELUC: -16.523435244696305', 'NSGA-II_crowding_distance: 0.1396606774471684', 'NSGA-II_rank: 1', 'change: 0.28940030706951797', 'is_elite: False']\n", + "Id: 4_80 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_55', '3_64'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_80', 'origin': '3_55~CUW~3_64#MGNP'} Metrics: ['ELUC: -17.097199697812407', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.30755527879929195', 'is_elite: False']\n", + "Id: 4_71 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_13', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_71', 'origin': '3_13~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.12846252193876', 'NSGA-II_crowding_distance: 0.07559981685451952', 'NSGA-II_rank: 1', 'change: 0.2979570943451353', 'is_elite: False']\n", + "Id: 4_64 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_100', '3_64'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_64', 'origin': '3_100~CUW~3_64#MGNP'} Metrics: ['ELUC: -17.29550314102826', 'NSGA-II_crowding_distance: 0.03850356357642481', 'NSGA-II_rank: 1', 'change: 0.29885537750232194', 'is_elite: False']\n", + "Id: 4_41 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_35', '3_37'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_41', 'origin': '3_35~CUW~3_37#MGNP'} Metrics: ['ELUC: -17.529846572818194', 'NSGA-II_crowding_distance: 0.02853108595834873', 'NSGA-II_rank: 1', 'change: 0.30263408860319646', 'is_elite: False']\n", + "Id: 4_55 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '3_20'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_55', 'origin': '3_19~CUW~3_20#MGNP'} Metrics: ['ELUC: -17.573935355135657', 'NSGA-II_crowding_distance: 0.004344622415101208', 'NSGA-II_rank: 1', 'change: 0.30264333724189113', 'is_elite: False']\n", + "Id: 4_14 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_83', '3_100'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_14', 'origin': '2_83~CUW~3_100#MGNP'} Metrics: ['ELUC: -17.592188370006262', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3030935729681807', 'is_elite: False']\n", + "Id: 4_100 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_80', '3_77'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_100', 'origin': '3_80~CUW~3_77#MGNP'} Metrics: ['ELUC: -17.59270796827749', 'NSGA-II_crowding_distance: 0.0025965384373321833', 'NSGA-II_rank: 1', 'change: 0.30286364985642245', 'is_elite: False']\n", + "Id: 4_37 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_37', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_37', 'origin': '3_37~CUW~3_55#MGNP'} Metrics: ['ELUC: -17.595462987084762', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302654921096134', 'is_elite: False']\n", + "Id: 4_66 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '3_80'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_66', 'origin': '2_49~CUW~3_80#MGNP'} Metrics: ['ELUC: -17.597368851263088', 'NSGA-II_crowding_distance: 0.0007916614746171578', 'NSGA-II_rank: 1', 'change: 0.303020412795371', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 3_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_83', '2_83'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_100', 'origin': '2_83~CUW~2_83#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 4_17 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '2_49'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_17', 'origin': '3_19~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 4_34 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '3_13'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_34', 'origin': '2_49~CUW~3_13#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 4_78 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '3_13'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_78', 'origin': '2_49~CUW~3_13#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 4.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 5...:\n", + "PopulationResponse:\n", + " Generation: 5\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/5/20240219-201536\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 5 and asking ESP for generation 6...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 5 data persisted.\n", + "Evaluated candidates:\n", + "Id: 5_55 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_55', 'origin': '4_32~CUW~4_25#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 5_21 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_98', '3_19'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_21', 'origin': '3_98~CUW~3_19#MGNP'} Metrics: ['ELUC: 12.55757159392459', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24297222536428795', 'is_elite: False']\n", + "Id: 5_45 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_45', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 12.286893373178092', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2577849210177904', 'is_elite: False']\n", + "Id: 5_82 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_82', 'origin': '4_78~CUW~1_1#MGNP'} Metrics: ['ELUC: 11.813416399532272', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2867865621682198', 'is_elite: False']\n", + "Id: 5_93 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_22', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_93', 'origin': '3_22~CUW~4_63#MGNP'} Metrics: ['ELUC: 9.64624363462342', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27132810026528703', 'is_elite: False']\n", + "Id: 5_94 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_94', 'origin': '4_78~CUW~1_1#MGNP'} Metrics: ['ELUC: 9.300555888577243', 'NSGA-II_crowding_distance: 0.863728565915022', 'NSGA-II_rank: 9', 'change: 0.26706618533306953', 'is_elite: False']\n", + "Id: 5_66 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_66', 'origin': '1_1~CUW~4_24#MGNP'} Metrics: ['ELUC: 7.024201982690772', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2135883876405549', 'is_elite: False']\n", + "Id: 5_32 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '4_11'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_32', 'origin': '4_32~CUW~4_11#MGNP'} Metrics: ['ELUC: 4.130528861671804', 'NSGA-II_crowding_distance: 0.9750021498117774', 'NSGA-II_rank: 8', 'change: 0.25505850886016973', 'is_elite: False']\n", + "Id: 5_48 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_96', '3_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_48', 'origin': '4_96~CUW~3_55#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 5_98 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_24', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_98', 'origin': '4_24~CUW~4_63#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 5_12 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_69', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_12', 'origin': '4_69~CUW~4_63#MGNP'} Metrics: ['ELUC: 2.331302652809594', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.29632020672081677', 'is_elite: False']\n", + "Id: 5_73 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_73', 'origin': '1_1~CUW~4_63#MGNP'} Metrics: ['ELUC: 1.3144475144386472', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.20970185704990615', 'is_elite: False']\n", + "Id: 5_70 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_19', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_70', 'origin': '3_19~CUW~4_24#MGNP'} Metrics: ['ELUC: 1.1839786566818968', 'NSGA-II_crowding_distance: 1.6783567786063984', 'NSGA-II_rank: 9', 'change: 0.2743785799734042', 'is_elite: False']\n", + "Id: 5_57 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_98', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_57', 'origin': '3_98~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.1395913502524462', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04546247898794363', 'is_elite: False']\n", + "Id: 5_54 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_54', 'origin': '4_63~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.43972424819590317', 'NSGA-II_crowding_distance: 0.9527818583341179', 'NSGA-II_rank: 3', 'change: 0.15177345178099477', 'is_elite: False']\n", + "Id: 5_35 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_55', '4_32'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_35', 'origin': '3_55~CUW~4_32#MGNP'} Metrics: ['ELUC: 0.33212516164597966', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24106371099711768', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 5_33 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '3_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_33', 'origin': '1_1~CUW~3_55#MGNP'} Metrics: ['ELUC: -0.11394960802851775', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03998707305061772', 'is_elite: False']\n", + "Id: 5_89 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_24', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_89', 'origin': '4_24~CUW~4_25#MGNP'} Metrics: ['ELUC: -0.23843416219191982', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3120026621147407', 'is_elite: False']\n", + "Id: 5_95 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_95', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.31563037330744464', 'NSGA-II_crowding_distance: 0.17853442825594623', 'NSGA-II_rank: 1', 'change: 0.03390363481915837', 'is_elite: True']\n", + "Id: 5_11 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_98', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_11', 'origin': '3_98~CUW~4_25#MGNP'} Metrics: ['ELUC: -0.5518156173444251', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.22812614274828194', 'is_elite: False']\n", + "Id: 5_13 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_55', '4_78'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_13', 'origin': '3_55~CUW~4_78#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.491621945026283', 'NSGA-II_rank: 6', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 5_67 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_67', 'origin': '1_1~CUW~4_63#MGNP'} Metrics: ['ELUC: -0.6907384914344454', 'NSGA-II_crowding_distance: 0.5462219032452065', 'NSGA-II_rank: 4', 'change: 0.21479539622206759', 'is_elite: False']\n", + "Id: 3_55 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 3, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '3_55', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1269085372614474', 'NSGA-II_crowding_distance: 0.08797365528588236', 'NSGA-II_rank: 1', 'change: 0.03904482046624399', 'is_elite: False']\n", + "Id: 5_84 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_55', '3_98'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_84', 'origin': '3_55~CUW~3_98#MGNP'} Metrics: ['ELUC: -1.2063409912477865', 'NSGA-II_crowding_distance: 1.017176635257446', 'NSGA-II_rank: 1', 'change: 0.04503737933356499', 'is_elite: True']\n", + "Id: 5_49 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_11'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_49', 'origin': '1_1~CUW~4_11#MGNP'} Metrics: ['ELUC: -1.2357993621948333', 'NSGA-II_crowding_distance: 0.57508161902083', 'NSGA-II_rank: 7', 'change: 0.2519637642778109', 'is_elite: False']\n", + "Id: 5_40 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '3_19'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_40', 'origin': '4_32~CUW~3_19#MGNP'} Metrics: ['ELUC: -1.8300456621475742', 'NSGA-II_crowding_distance: 0.6708825114249475', 'NSGA-II_rank: 8', 'change: 0.26174664058426717', 'is_elite: False']\n", + "Id: 5_68 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_64', '4_11'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_68', 'origin': '4_64~CUW~4_11#MGNP'} Metrics: ['ELUC: -2.157311630129579', 'NSGA-II_crowding_distance: 0.4269378223357424', 'NSGA-II_rank: 6', 'change: 0.24875462628351028', 'is_elite: False']\n", + "Id: 5_47 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_11', '3_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_47', 'origin': '4_11~CUW~3_55#MGNP'} Metrics: ['ELUC: -2.234868491187087', 'NSGA-II_crowding_distance: 0.8863088403861918', 'NSGA-II_rank: 5', 'change: 0.22531808445018653', 'is_elite: False']\n", + "Id: 4_24 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_20', '3_98'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_24', 'origin': '3_20~CUW~3_98#MGNP'} Metrics: ['ELUC: -2.66066065044801', 'NSGA-II_crowding_distance: 0.6324707357074273', 'NSGA-II_rank: 3', 'change: 0.21069879910559858', 'is_elite: False']\n", + "Id: 5_85 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_41', '4_71'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_85', 'origin': '4_41~CUW~4_71#MGNP'} Metrics: ['ELUC: -2.853565940542712', 'NSGA-II_crowding_distance: 0.9480584770835414', 'NSGA-II_rank: 8', 'change: 0.27621015847060837', 'is_elite: False']\n", + "Id: 5_42 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_24', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_42', 'origin': '4_24~CUW~4_25#MGNP'} Metrics: ['ELUC: -2.9735087569455563', 'NSGA-II_crowding_distance: 0.4983786932652557', 'NSGA-II_rank: 6', 'change: 0.24951179926507588', 'is_elite: False']\n", + "Id: 5_74 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_11', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_74', 'origin': '4_11~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.1498134966770754', 'NSGA-II_crowding_distance: 0.44879784269261747', 'NSGA-II_rank: 7', 'change: 0.25406099007027905', 'is_elite: False']\n", + "Id: 5_20 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_96', '4_71'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_20', 'origin': '4_96~CUW~4_71#MGNP'} Metrics: ['ELUC: -3.3736675890950765', 'NSGA-II_crowding_distance: 0.7201792188677589', 'NSGA-II_rank: 7', 'change: 0.265538917948616', 'is_elite: False']\n", + "Id: 5_26 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_55', '4_11'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_26', 'origin': '3_55~CUW~4_11#MGNP'} Metrics: ['ELUC: -3.5667653433829076', 'NSGA-II_crowding_distance: 1.054999631390069', 'NSGA-II_rank: 2', 'change: 0.20337188805840425', 'is_elite: False']\n", + "Id: 5_39 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '4_69'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_39', 'origin': '4_25~CUW~4_69#MGNP'} Metrics: ['ELUC: -3.5717027625964826', 'NSGA-II_crowding_distance: 0.4354907581891669', 'NSGA-II_rank: 5', 'change: 0.2385479941899136', 'is_elite: False']\n", + "Id: 5_29 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_29', 'origin': '4_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.6569699751542557', 'NSGA-II_crowding_distance: 0.8371296730535769', 'NSGA-II_rank: 4', 'change: 0.22392551271697836', 'is_elite: False']\n", + "Id: 4_11 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_20', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_11', 'origin': '3_20~CUW~3_55#MGNP'} Metrics: ['ELUC: -4.761299281658512', 'NSGA-II_crowding_distance: 0.31409011678443083', 'NSGA-II_rank: 3', 'change: 0.21557744193799955', 'is_elite: False']\n", + "Id: 5_92 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '4_32'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_92', 'origin': '4_63~CUW~4_32#MGNP'} Metrics: ['ELUC: -6.28849917040056', 'NSGA-II_crowding_distance: 0.6824029082345556', 'NSGA-II_rank: 7', 'change: 0.27757379211661903', 'is_elite: False']\n", + "Id: 5_71 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '3_98'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_71', 'origin': '4_63~CUW~3_98#MGNP'} Metrics: ['ELUC: -6.333770868324022', 'NSGA-II_crowding_distance: 0.3789364845340364', 'NSGA-II_rank: 3', 'change: 0.22370775101105356', 'is_elite: False']\n", + "Id: 5_28 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_55', '4_78'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_28', 'origin': '3_55~CUW~4_78#MGNP'} Metrics: ['ELUC: -6.390572634136633', 'NSGA-II_crowding_distance: 0.6345813204554711', 'NSGA-II_rank: 6', 'change: 0.25141073080275544', 'is_elite: False']\n", + "Id: 5_50 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '3_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_50', 'origin': '4_78~CUW~3_55#MGNP'} Metrics: ['ELUC: -6.401449678693581', 'NSGA-II_crowding_distance: 0.3158016442605418', 'NSGA-II_rank: 6', 'change: 0.26664147918458214', 'is_elite: False']\n", + "Id: 5_76 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_76', '3_98'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_76', 'origin': '4_76~CUW~3_98#MGNP'} Metrics: ['ELUC: -6.595579413638783', 'NSGA-II_crowding_distance: 0.30082370707710665', 'NSGA-II_rank: 2', 'change: 0.20591602775107837', 'is_elite: False']\n", + "Id: 5_61 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_55', '4_32'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_61', 'origin': '3_55~CUW~4_32#MGNP'} Metrics: ['ELUC: -6.691340694191023', 'NSGA-II_crowding_distance: 0.26752845374927714', 'NSGA-II_rank: 5', 'change: 0.2407880645019391', 'is_elite: False']\n", + "Id: 5_52 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_69', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_52', 'origin': '4_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.717768683962291', 'NSGA-II_crowding_distance: 0.23050204109730674', 'NSGA-II_rank: 2', 'change: 0.22902900346042274', 'is_elite: False']\n", + "Id: 5_38 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_38', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.0857262497397135', 'NSGA-II_crowding_distance: 0.16529201254130155', 'NSGA-II_rank: 6', 'change: 0.2670169954206595', 'is_elite: False']\n", + "Id: 5_44 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_44', 'origin': '3_19~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.2175599950843905', 'NSGA-II_crowding_distance: 0.1620011724454744', 'NSGA-II_rank: 5', 'change: 0.24416854889693007', 'is_elite: False']\n", + "Id: 5_79 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '3_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_79', 'origin': '4_78~CUW~3_55#MGNP'} Metrics: ['ELUC: -7.266501501744565', 'NSGA-II_crowding_distance: 0.3689488448995382', 'NSGA-II_rank: 6', 'change: 0.27129835499239685', 'is_elite: False']\n", + "Id: 5_60 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '3_22'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_60', 'origin': '4_32~CUW~3_22#MGNP'} Metrics: ['ELUC: -7.42795621124742', 'NSGA-II_crowding_distance: 0.35903094174998745', 'NSGA-II_rank: 7', 'change: 0.28142043375444037', 'is_elite: False']\n", + "Id: 5_65 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_65', 'origin': '4_32~CUW~4_24#MGNP'} Metrics: ['ELUC: -7.435262768831019', 'NSGA-II_crowding_distance: 0.18060178948140193', 'NSGA-II_rank: 5', 'change: 0.2504500650075654', 'is_elite: False']\n", + "Id: 5_81 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_69', '2_49'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_81', 'origin': '4_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.679409386390815', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.31172244642937', 'is_elite: False']\n", + "Id: 5_19 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_11', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_19', 'origin': '4_11~CUW~4_25#MGNP'} Metrics: ['ELUC: -7.834631613356997', 'NSGA-II_crowding_distance: 0.328474028195145', 'NSGA-II_rank: 5', 'change: 0.2558474528014719', 'is_elite: False']\n", + "Id: 5_88 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_41', '3_22'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_88', 'origin': '4_41~CUW~3_22#MGNP'} Metrics: ['ELUC: -8.137127657660853', 'NSGA-II_crowding_distance: 0.7929557863159037', 'NSGA-II_rank: 4', 'change: 0.23757267821001427', 'is_elite: False']\n", + "Id: 5_16 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_16', 'origin': '1_1~CUW~4_24#MGNP'} Metrics: ['ELUC: -8.366982691746513', 'NSGA-II_crowding_distance: 0.36719827663366', 'NSGA-II_rank: 7', 'change: 0.28625281066127845', 'is_elite: False']\n", + "Id: 5_77 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_24', '4_96'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_77', 'origin': '4_24~CUW~4_96#MGNP'} Metrics: ['ELUC: -8.458637901286744', 'NSGA-II_crowding_distance: 0.3457082203614237', 'NSGA-II_rank: 7', 'change: 0.296782746736788', 'is_elite: False']\n", + "Id: 5_41 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '4_69'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_41', 'origin': '4_78~CUW~4_69#MGNP'} Metrics: ['ELUC: -8.47360500450392', 'NSGA-II_crowding_distance: 0.4900635875321897', 'NSGA-II_rank: 6', 'change: 0.2812160006829352', 'is_elite: False']\n", + "Id: 5_22 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '4_69'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_22', 'origin': '4_78~CUW~4_69#MGNP'} Metrics: ['ELUC: -8.624917099966435', 'NSGA-II_crowding_distance: 0.6891749587577858', 'NSGA-II_rank: 8', 'change: 0.30031918177067046', 'is_elite: False']\n", + "Id: 4_32 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_80', '3_55'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_32', 'origin': '3_80~CUW~3_55#MGNP'} Metrics: ['ELUC: -8.662381477457489', 'NSGA-II_crowding_distance: 0.24341678938129216', 'NSGA-II_rank: 2', 'change: 0.23135356254458647', 'is_elite: False']\n", + "Id: 5_78 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_98', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_78', 'origin': '3_98~CUW~4_25#MGNP'} Metrics: ['ELUC: -8.838737705706935', 'NSGA-II_crowding_distance: 0.07693937310468127', 'NSGA-II_rank: 8', 'change: 0.30129691005356485', 'is_elite: False']\n", + "Id: 5_56 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '4_69'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_56', 'origin': '4_78~CUW~4_69#MGNP'} Metrics: ['ELUC: -8.87396545823183', 'NSGA-II_crowding_distance: 0.3767652976873527', 'NSGA-II_rank: 5', 'change: 0.27033865989565253', 'is_elite: False']\n", + "Id: 4_69 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_22', '1_1'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_69', 'origin': '3_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.915073860402702', 'NSGA-II_crowding_distance: 0.32664630402909645', 'NSGA-II_rank: 3', 'change: 0.23602902906673193', 'is_elite: False']\n", + "Id: 5_25 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_25', 'origin': '4_32~CUW~4_25#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 5_75 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_24', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_75', 'origin': '4_24~CUW~4_25#MGNP'} Metrics: ['ELUC: -9.189592987106181', 'NSGA-II_crowding_distance: 0.3252488725483813', 'NSGA-II_rank: 6', 'change: 0.2896006764093223', 'is_elite: False']\n", + "Id: 5_64 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_64', 'origin': '4_32~CUW~4_63#MGNP'} Metrics: ['ELUC: -9.253219093608125', 'NSGA-II_crowding_distance: 0.35042724525058266', 'NSGA-II_rank: 5', 'change: 0.27965032906371695', 'is_elite: False']\n", + "Id: 5_17 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '4_69'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_17', 'origin': '4_25~CUW~4_69#MGNP'} Metrics: ['ELUC: -9.528231672172799', 'NSGA-II_crowding_distance: 0.503478023677207', 'NSGA-II_rank: 4', 'change: 0.25219761540541036', 'is_elite: False']\n", + "Id: 5_80 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '4_78'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_80', 'origin': '4_32~CUW~4_78#MGNP'} Metrics: ['ELUC: -9.533618021038714', 'NSGA-II_crowding_distance: 0.30122821813499395', 'NSGA-II_rank: 4', 'change: 0.268730319497204', 'is_elite: False']\n", + "Id: 5_97 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '4_11'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_97', 'origin': '4_78~CUW~4_11#MGNP'} Metrics: ['ELUC: -9.5385102723568', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29952460656648405', 'is_elite: False']\n", + "Id: 5_53 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '3_19'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_53', 'origin': '4_63~CUW~3_19#MGNP'} Metrics: ['ELUC: -9.683619990708184', 'NSGA-II_crowding_distance: 0.44737006854546635', 'NSGA-II_rank: 4', 'change: 0.2746917451040696', 'is_elite: False']\n", + "Id: 5_87 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_11', '4_69'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_87', 'origin': '4_11~CUW~4_69#MGNP'} Metrics: ['ELUC: -9.703488203048412', 'NSGA-II_crowding_distance: 0.18849813191572534', 'NSGA-II_rank: 3', 'change: 0.2449495437616989', 'is_elite: False']\n", + "Id: 5_99 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_96', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_99', 'origin': '4_96~CUW~4_25#MGNP'} Metrics: ['ELUC: -9.806569242256582', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2929662344771511', 'is_elite: False']\n", + "Id: 5_91 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_91', 'origin': '4_32~CUW~4_24#MGNP'} Metrics: ['ELUC: -10.070173322719388', 'NSGA-II_crowding_distance: 0.2717568624262638', 'NSGA-II_rank: 3', 'change: 0.2618112188768546', 'is_elite: False']\n", + "Id: 5_63 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_19', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_63', 'origin': '3_19~CUW~4_24#MGNP'} Metrics: ['ELUC: -10.182119596266494', 'NSGA-II_crowding_distance: 0.2379685399495639', 'NSGA-II_rank: 2', 'change: 0.23458606612306626', 'is_elite: False']\n", + "Id: 5_24 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_98', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_24', 'origin': '3_98~CUW~4_63#MGNP'} Metrics: ['ELUC: -10.627600610150036', 'NSGA-II_crowding_distance: 1.1675101426396164', 'NSGA-II_rank: 1', 'change: 0.18131798772309257', 'is_elite: True']\n", + "Id: 5_86 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_86', 'origin': '1_1~CUW~4_63#MGNP'} Metrics: ['ELUC: -10.876645409116017', 'NSGA-II_crowding_distance: 0.24473659844064044', 'NSGA-II_rank: 1', 'change: 0.22928834115337476', 'is_elite: True']\n", + "Id: 5_90 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '4_78'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_90', 'origin': '4_32~CUW~4_78#MGNP'} Metrics: ['ELUC: -10.98828564129667', 'NSGA-II_crowding_distance: 0.2887956186957764', 'NSGA-II_rank: 5', 'change: 0.28907901797236624', 'is_elite: False']\n", + "Id: 5_30 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_11', '3_22'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_30', 'origin': '4_11~CUW~3_22#MGNP'} Metrics: ['ELUC: -11.150546132892671', 'NSGA-II_crowding_distance: 0.2648029771446141', 'NSGA-II_rank: 2', 'change: 0.2517238743942503', 'is_elite: False']\n", + "Id: 5_15 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_22', '3_19'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_15', 'origin': '3_22~CUW~3_19#MGNP'} Metrics: ['ELUC: -11.517625683508124', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2928631657155293', 'is_elite: False']\n", + "Id: 4_63 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_98', '3_19'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_63', 'origin': '3_98~CUW~3_19#MGNP'} Metrics: ['ELUC: -11.619438827630509', 'NSGA-II_crowding_distance: 0.10845388048749834', 'NSGA-II_rank: 1', 'change: 0.23751013438589627', 'is_elite: False']\n", + "Id: 5_58 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_58', 'origin': '4_25~CUW~4_24#MGNP'} Metrics: ['ELUC: -11.69654142121448', 'NSGA-II_crowding_distance: 0.3107505205646767', 'NSGA-II_rank: 3', 'change: 0.27650496808314706', 'is_elite: False']\n", + "Id: 5_34 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_11', '3_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_34', 'origin': '4_11~CUW~3_55#MGNP'} Metrics: ['ELUC: -12.13886209499842', 'NSGA-II_crowding_distance: 0.14408510255227053', 'NSGA-II_rank: 1', 'change: 0.24022835599408052', 'is_elite: False']\n", + "Id: 5_46 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_24', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_46', 'origin': '4_24~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.28808566429132', 'NSGA-II_crowding_distance: 0.21590268390638562', 'NSGA-II_rank: 2', 'change: 0.2682703346416254', 'is_elite: False']\n", + "Id: 5_27 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '3_19'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_27', 'origin': '2_49~CUW~3_19#MGNP'} Metrics: ['ELUC: -12.383941363909642', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28729868068755215', 'is_elite: False']\n", + "Id: 4_25 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_22', '3_19'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_25', 'origin': '3_22~CUW~3_19#MGNP'} Metrics: ['ELUC: -12.76599072488195', 'NSGA-II_crowding_distance: 0.1839614510970632', 'NSGA-II_rank: 1', 'change: 0.2610445789338331', 'is_elite: True']\n", + "Id: 5_37 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '3_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_37', 'origin': '4_78~CUW~3_55#MGNP'} Metrics: ['ELUC: -12.972606180455735', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.28721510096757574', 'is_elite: False']\n", + "Id: 5_100 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_78'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_100', 'origin': '1_1~CUW~4_78#MGNP'} Metrics: ['ELUC: -13.490697488369992', 'NSGA-II_crowding_distance: 0.33984978210729433', 'NSGA-II_rank: 2', 'change: 0.2688305912078551', 'is_elite: False']\n", + "Id: 5_96 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_71', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_96', 'origin': '4_71~CUW~4_63#MGNP'} Metrics: ['ELUC: -13.79339038254712', 'NSGA-II_crowding_distance: 0.10030869757467258', 'NSGA-II_rank: 1', 'change: 0.267040498393014', 'is_elite: False']\n", + "Id: 5_51 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_55', '4_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_51', 'origin': '3_55~CUW~4_55#MGNP'} Metrics: ['ELUC: -13.802458624199245', 'NSGA-II_crowding_distance: 0.03014650565750579', 'NSGA-II_rank: 1', 'change: 0.27338527919038724', 'is_elite: False']\n", + "Id: 5_36 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_36', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.924512332555354', 'NSGA-II_crowding_distance: 0.18417066825900136', 'NSGA-II_rank: 1', 'change: 0.273810363948219', 'is_elite: True']\n", + "Id: 5_23 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '4_25'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_23', 'origin': '4_78~CUW~4_25#MGNP'} Metrics: ['ELUC: -15.719541450315704', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2993891069490948', 'is_elite: False']\n", + "Id: 5_62 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '4_11'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_62', 'origin': '4_25~CUW~4_11#MGNP'} Metrics: ['ELUC: -16.588633123347925', 'NSGA-II_crowding_distance: 0.23830476194048952', 'NSGA-II_rank: 1', 'change: 0.2810554623800883', 'is_elite: True']\n", + "Id: 5_69 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_78', '3_19'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_69', 'origin': '4_78~CUW~3_19#MGNP'} Metrics: ['ELUC: -16.629904838615555', 'NSGA-II_crowding_distance: 0.11576332666972482', 'NSGA-II_rank: 1', 'change: 0.2990038495973682', 'is_elite: False']\n", + "Id: 5_31 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_32', '2_49'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_31', 'origin': '4_32~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.455241192127477', 'NSGA-II_crowding_distance: 0.06768983272545734', 'NSGA-II_rank: 1', 'change: 0.3008900532120656', 'is_elite: False']\n", + "Id: 5_43 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_98', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_43', 'origin': '3_98~CUW~4_24#MGNP'} Metrics: ['ELUC: -17.587971103380458', 'NSGA-II_crowding_distance: 0.015193534493417631', 'NSGA-II_rank: 1', 'change: 0.30294230741399525', 'is_elite: False']\n", + "Id: 5_14 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_76', '2_49'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_14', 'origin': '4_76~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597026224800718', 'NSGA-II_crowding_distance: 0.0007974544658360422', 'NSGA-II_rank: 1', 'change: 0.30301732960940353', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 4_78 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '3_13'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_78', 'origin': '2_49~CUW~3_13#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 5_18 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '3_19'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_18', 'origin': '2_49~CUW~3_19#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 5_59 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_55'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_59', 'origin': '1_1~CUW~4_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 5_72 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_19', '2_49'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_72', 'origin': '3_19~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 5_83 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_83', 'origin': '4_25~CUW~4_24#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 5.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 6...:\n", + "PopulationResponse:\n", + " Generation: 6\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/6/20240219-202254\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 6 and asking ESP for generation 7...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 6 data persisted.\n", + "Evaluated candidates:\n", + "Id: 6_58 Identity: {'ancestor_count': 3, 'ancestor_ids': ['5_84', '2_49'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_58', 'origin': '5_84~CUW~2_49#MGNP'} Metrics: ['ELUC: 22.575256030713476', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.30086771314152716', 'is_elite: False']\n", + "Id: 6_41 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '5_96'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_41', 'origin': '2_49~CUW~5_96#MGNP'} Metrics: ['ELUC: 21.66145162049628', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.30150100213930786', 'is_elite: False']\n", + "Id: 6_52 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_52', 'origin': '5_83~CUW~1_1#MGNP'} Metrics: ['ELUC: 18.391654228942684', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2563716951063326', 'is_elite: False']\n", + "Id: 6_68 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_68', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 14.670375005673714', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2725230420051687', 'is_elite: False']\n", + "Id: 6_66 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_51', '5_96'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_66', 'origin': '5_51~CUW~5_96#MGNP'} Metrics: ['ELUC: 12.330610380597232', 'NSGA-II_crowding_distance: 0.7918940182892882', 'NSGA-II_rank: 9', 'change: 0.25671759269814504', 'is_elite: False']\n", + "Id: 6_44 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_69', '5_36'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_44', 'origin': '5_69~CUW~5_36#MGNP'} Metrics: ['ELUC: 11.231041510875482', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26276407501507326', 'is_elite: False']\n", + "Id: 6_99 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_99', 'origin': '5_86~CUW~1_1#MGNP'} Metrics: ['ELUC: 10.427962142686766', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.17088035164459597', 'is_elite: False']\n", + "Id: 6_73 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_62', '5_84'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_73', 'origin': '5_62~CUW~5_84#MGNP'} Metrics: ['ELUC: 9.991306878420243', 'NSGA-II_crowding_distance: 1.612271882454671', 'NSGA-II_rank: 9', 'change: 0.25938355254578577', 'is_elite: False']\n", + "Id: 6_53 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_14'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_53', 'origin': '1_1~CUW~5_14#MGNP'} Metrics: ['ELUC: 6.313766198899194', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.31677156821996466', 'is_elite: False']\n", + "Id: 6_33 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_33', 'origin': '1_1~CUW~5_86#MGNP'} Metrics: ['ELUC: 5.5843779111962855', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.1918781367772692', 'is_elite: False']\n", + "Id: 6_48 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_96', '5_34'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_48', 'origin': '5_96~CUW~5_34#MGNP'} Metrics: ['ELUC: 4.392720461351509', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2261458869148506', 'is_elite: False']\n", + "Id: 6_19 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_19', 'origin': '4_25~CUW~1_1#MGNP'} Metrics: ['ELUC: 4.253083542783541', 'NSGA-II_crowding_distance: 0.2095880813365876', 'NSGA-II_rank: 7', 'change: 0.2342952391457897', 'is_elite: False']\n", + "Id: 6_67 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_36', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_67', 'origin': '5_36~CUW~5_86#MGNP'} Metrics: ['ELUC: 3.2134626966212534', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3328217725099805', 'is_elite: False']\n", + "Id: 6_60 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '5_95'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_60', 'origin': '4_63~CUW~5_95#MGNP'} Metrics: ['ELUC: 2.7923246763137466', 'NSGA-II_crowding_distance: 0.8156797441472228', 'NSGA-II_rank: 6', 'change: 0.19893068666185065', 'is_elite: False']\n", + "Id: 6_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_55', '2_49'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_54', 'origin': '3_55~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.5970028692883753', 'NSGA-II_crowding_distance: 0.369542613246995', 'NSGA-II_rank: 7', 'change: 0.23677949312973884', 'is_elite: False']\n", + "Id: 6_21 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_21', 'origin': '5_24~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.9195033900048657', 'NSGA-II_crowding_distance: 0.6057656532058411', 'NSGA-II_rank: 5', 'change: 0.1900257238723717', 'is_elite: False']\n", + "Id: 6_88 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_95', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_88', 'origin': '5_95~CUW~5_86#MGNP'} Metrics: ['ELUC: 1.5714696558348342', 'NSGA-II_crowding_distance: 0.40024452252981685', 'NSGA-II_rank: 5', 'change: 0.20969977441186197', 'is_elite: False']\n", + "Id: 6_50 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_69'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_50', 'origin': '1_1~CUW~5_69#MGNP'} Metrics: ['ELUC: 1.4827386575385946', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.27665876342379225', 'is_elite: False']\n", + "Id: 6_17 Identity: {'ancestor_count': 5, 'ancestor_ids': ['4_25', '5_24'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_17', 'origin': '4_25~CUW~5_24#MGNP'} Metrics: ['ELUC: 1.373189469143937', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2853925045934634', 'is_elite: False']\n", + "Id: 6_23 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_31', '5_96'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_23', 'origin': '5_31~CUW~5_96#MGNP'} Metrics: ['ELUC: 1.219826538064193', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26632165474096614', 'is_elite: False']\n", + "Id: 6_22 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_22', 'origin': '1_1~CUW~5_86#MGNP'} Metrics: ['ELUC: 1.2192335248319432', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.10049969741252342', 'is_elite: False']\n", + "Id: 6_25 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '5_95'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_25', 'origin': '1_1~CUW~5_95#MGNP'} Metrics: ['ELUC: 0.7439644168479314', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.049976037445885794', 'is_elite: False']\n", + "Id: 6_91 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_91', 'origin': '5_24~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.520228743495417', 'NSGA-II_crowding_distance: 0.9183565522035044', 'NSGA-II_rank: 3', 'change: 0.18281940202727795', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 5_95 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_95', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.31563037330744464', 'NSGA-II_crowding_distance: 0.15972454947576226', 'NSGA-II_rank: 1', 'change: 0.03390363481915837', 'is_elite: False']\n", + "Id: 6_26 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '5_83'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_26', 'origin': '2_49~CUW~5_83#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.25766105500835196', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 6_51 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '2_49'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_51', 'origin': '5_24~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.2449617263810185', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 6_71 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_34', '5_83'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_71', 'origin': '5_34~CUW~5_83#MGNP'} Metrics: ['ELUC: -0.6571607147155265', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24732928230609466', 'is_elite: False']\n", + "Id: 6_79 Identity: {'ancestor_count': 3, 'ancestor_ids': ['5_84', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_79', 'origin': '5_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7119460276849363', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04943823609618821', 'is_elite: False']\n", + "Id: 6_47 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_47', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7182614142594622', 'NSGA-II_crowding_distance: 0.08797365528588236', 'NSGA-II_rank: 1', 'change: 0.04036723943742811', 'is_elite: False']\n", + "Id: 5_84 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_55', '3_98'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_84', 'origin': '3_55~CUW~3_98#MGNP'} Metrics: ['ELUC: -1.2063409912477865', 'NSGA-II_crowding_distance: 0.47210760013416253', 'NSGA-II_rank: 1', 'change: 0.04503737933356499', 'is_elite: True']\n", + "Id: 6_35 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '5_84'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_35', 'origin': '5_83~CUW~5_84#MGNP'} Metrics: ['ELUC: -1.3722961312136548', 'NSGA-II_crowding_distance: 0.8600702703378575', 'NSGA-II_rank: 6', 'change: 0.22627189677749548', 'is_elite: False']\n", + "Id: 6_30 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_34'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_30', 'origin': '1_1~CUW~5_34#MGNP'} Metrics: ['ELUC: -1.906782718708443', 'NSGA-II_crowding_distance: 0.5678770064398938', 'NSGA-II_rank: 1', 'change: 0.16106405330293716', 'is_elite: True']\n", + "Id: 6_77 Identity: {'ancestor_count': 5, 'ancestor_ids': ['4_25', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_77', 'origin': '4_25~CUW~5_86#MGNP'} Metrics: ['ELUC: -4.051833870375474', 'NSGA-II_crowding_distance: 0.45477790346334235', 'NSGA-II_rank: 7', 'change: 0.2419387181013569', 'is_elite: False']\n", + "Id: 6_83 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '5_36'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_83', 'origin': '4_63~CUW~5_36#MGNP'} Metrics: ['ELUC: -4.110314699092244', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2638666233313075', 'is_elite: False']\n", + "Id: 6_74 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_84', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_74', 'origin': '5_84~CUW~5_86#MGNP'} Metrics: ['ELUC: -4.253977844489553', 'NSGA-II_crowding_distance: 0.5985052413862817', 'NSGA-II_rank: 5', 'change: 0.21345584292054604', 'is_elite: False']\n", + "Id: 6_15 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_24'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_15', 'origin': '1_1~CUW~5_24#MGNP'} Metrics: ['ELUC: -4.322231104289276', 'NSGA-II_crowding_distance: 1.1217342942829576', 'NSGA-II_rank: 4', 'change: 0.19702368988880675', 'is_elite: False']\n", + "Id: 6_81 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_24'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_81', 'origin': '1_1~CUW~5_24#MGNP'} Metrics: ['ELUC: -4.352363265593337', 'NSGA-II_crowding_distance: 0.24974252341700195', 'NSGA-II_rank: 1', 'change: 0.1610902550614279', 'is_elite: True']\n", + "Id: 6_80 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '5_69'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_80', 'origin': '2_49~CUW~5_69#MGNP'} Metrics: ['ELUC: -4.503445258983733', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3171114054178901', 'is_elite: False']\n", + "Id: 6_89 Identity: {'ancestor_count': 5, 'ancestor_ids': ['4_63', '5_31'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_89', 'origin': '4_63~CUW~5_31#MGNP'} Metrics: ['ELUC: -4.538993749944678', 'NSGA-II_crowding_distance: 0.48156622189183196', 'NSGA-II_rank: 6', 'change: 0.23521967402344132', 'is_elite: False']\n", + "Id: 6_57 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_84', '5_43'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_57', 'origin': '5_84~CUW~5_43#MGNP'} Metrics: ['ELUC: -5.692056673336152', 'NSGA-II_crowding_distance: 0.5423217474087354', 'NSGA-II_rank: 3', 'change: 0.1936676164774503', 'is_elite: False']\n", + "Id: 6_59 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_62', '3_55'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_59', 'origin': '5_62~CUW~3_55#MGNP'} Metrics: ['ELUC: -5.695364272984882', 'NSGA-II_crowding_distance: 0.5724744058194546', 'NSGA-II_rank: 7', 'change: 0.25105755239041494', 'is_elite: False']\n", + "Id: 6_42 Identity: {'ancestor_count': 5, 'ancestor_ids': ['4_25', '5_96'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_42', 'origin': '4_25~CUW~5_96#MGNP'} Metrics: ['ELUC: -5.898069321975069', 'NSGA-II_crowding_distance: 0.3184733712743891', 'NSGA-II_rank: 6', 'change: 0.24408928478349975', 'is_elite: False']\n", + "Id: 6_45 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_95', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_45', 'origin': '5_95~CUW~5_86#MGNP'} Metrics: ['ELUC: -6.0145084412763135', 'NSGA-II_crowding_distance: 0.17694128524509262', 'NSGA-II_rank: 6', 'change: 0.2560220793462595', 'is_elite: False']\n", + "Id: 6_55 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_55', 'origin': '5_24~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.051883813402863', 'NSGA-II_crowding_distance: 0.42469808608696535', 'NSGA-II_rank: 1', 'change: 0.165238013657982', 'is_elite: True']\n", + "Id: 6_96 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '5_84'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_96', 'origin': '4_25~CUW~5_84#MGNP'} Metrics: ['ELUC: -6.346529256935124', 'NSGA-II_crowding_distance: 0.33720018173812394', 'NSGA-II_rank: 6', 'change: 0.2578538926817303', 'is_elite: False']\n", + "Id: 6_24 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_62', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_24', 'origin': '5_62~CUW~5_86#MGNP'} Metrics: ['ELUC: -6.869844099719642', 'NSGA-II_crowding_distance: 0.47311127415155485', 'NSGA-II_rank: 4', 'change: 0.230378894894737', 'is_elite: False']\n", + "Id: 6_38 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_95', '5_24'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_38', 'origin': '5_95~CUW~5_24#MGNP'} Metrics: ['ELUC: -7.408894618367615', 'NSGA-II_crowding_distance: 0.9915235925594097', 'NSGA-II_rank: 2', 'change: 0.18729605868445146', 'is_elite: False']\n", + "Id: 6_85 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '5_24'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_85', 'origin': '5_86~CUW~5_24#MGNP'} Metrics: ['ELUC: -7.665527120031261', 'NSGA-II_crowding_distance: 0.08751753422218146', 'NSGA-II_rank: 2', 'change: 0.1964466761860662', 'is_elite: False']\n", + "Id: 6_31 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_31', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_31', 'origin': '5_31~CUW~5_86#MGNP'} Metrics: ['ELUC: -7.701969450920494', 'NSGA-II_crowding_distance: 0.5657186132104639', 'NSGA-II_rank: 7', 'change: 0.2818797086030293', 'is_elite: False']\n", + "Id: 6_56 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_56', 'origin': '4_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.021476277539874', 'NSGA-II_crowding_distance: 0.26414392466309006', 'NSGA-II_rank: 3', 'change: 0.20040541933908876', 'is_elite: False']\n", + "Id: 6_12 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_34', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_12', 'origin': '5_34~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.22683470391928', 'NSGA-II_crowding_distance: 0.21145600051595187', 'NSGA-II_rank: 2', 'change: 0.1972047302344119', 'is_elite: False']\n", + "Id: 6_61 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_62', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_61', 'origin': '5_62~CUW~5_86#MGNP'} Metrics: ['ELUC: -8.405881927210519', 'NSGA-II_crowding_distance: 0.7153147314545872', 'NSGA-II_rank: 7', 'change: 0.2983127458290174', 'is_elite: False']\n", + "Id: 6_28 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '5_24'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_28', 'origin': '5_83~CUW~5_24#MGNP'} Metrics: ['ELUC: -9.273883995124327', 'NSGA-II_crowding_distance: 0.561891044080134', 'NSGA-II_rank: 5', 'change: 0.23360748818137234', 'is_elite: False']\n", + "Id: 6_70 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '5_36'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_70', 'origin': '5_86~CUW~5_36#MGNP'} Metrics: ['ELUC: -9.32011537308785', 'NSGA-II_crowding_distance: 0.4436866581781646', 'NSGA-II_rank: 6', 'change: 0.26768627388096283', 'is_elite: False']\n", + "Id: 6_90 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '5_43'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_90', 'origin': '5_86~CUW~5_43#MGNP'} Metrics: ['ELUC: -9.340723306396098', 'NSGA-II_crowding_distance: 0.1870457237496361', 'NSGA-II_rank: 3', 'change: 0.20949299206273275', 'is_elite: False']\n", + "Id: 6_18 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '4_63'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_18', 'origin': '5_86~CUW~4_63#MGNP'} Metrics: ['ELUC: -9.493964846753586', 'NSGA-II_crowding_distance: 0.3172998116153986', 'NSGA-II_rank: 4', 'change: 0.2308552702666432', 'is_elite: False']\n", + "Id: 6_97 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_97', 'origin': '5_83~CUW~5_86#MGNP'} Metrics: ['ELUC: -9.781119582763544', 'NSGA-II_crowding_distance: 0.22959193118024762', 'NSGA-II_rank: 6', 'change: 0.2786393604687759', 'is_elite: False']\n", + "Id: 6_86 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_86', 'origin': '2_49~CUW~5_86#MGNP'} Metrics: ['ELUC: -9.828936666886293', 'NSGA-II_crowding_distance: 0.2836855889097767', 'NSGA-II_rank: 5', 'change: 0.2676686261133782', 'is_elite: False']\n", + "Id: 6_94 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_94', 'origin': '2_49~CUW~5_86#MGNP'} Metrics: ['ELUC: -10.01758098822059', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.3512845064813819', 'is_elite: False']\n", + "Id: 6_14 Identity: {'ancestor_count': 5, 'ancestor_ids': ['4_25', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_14', 'origin': '4_25~CUW~5_86#MGNP'} Metrics: ['ELUC: -10.038771291685007', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.28473389502090773', 'is_elite: False']\n", + "Id: 6_93 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '5_62'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_93', 'origin': '5_86~CUW~5_62#MGNP'} Metrics: ['ELUC: -10.068007454488672', 'NSGA-II_crowding_distance: 0.1809291688658008', 'NSGA-II_rank: 5', 'change: 0.274911179498108', 'is_elite: False']\n", + "Id: 6_34 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_34', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.076388416772234', 'NSGA-II_crowding_distance: 0.5120435164981004', 'NSGA-II_rank: 5', 'change: 0.2957974612301612', 'is_elite: False']\n", + "Id: 6_64 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_31', '5_95'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_64', 'origin': '5_31~CUW~5_95#MGNP'} Metrics: ['ELUC: -10.224133609138176', 'NSGA-II_crowding_distance: 0.7209924262641796', 'NSGA-II_rank: 4', 'change: 0.2544279899453421', 'is_elite: False']\n", + "Id: 6_62 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_43', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_62', 'origin': '5_43~CUW~5_86#MGNP'} Metrics: ['ELUC: -10.235999828691805', 'NSGA-II_crowding_distance: 0.29406146388111315', 'NSGA-II_rank: 3', 'change: 0.2168497745263839', 'is_elite: False']\n", + "Id: 6_69 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_95', '5_34'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_69', 'origin': '5_95~CUW~5_34#MGNP'} Metrics: ['ELUC: -10.465054127144093', 'NSGA-II_crowding_distance: 0.37038551208352266', 'NSGA-II_rank: 2', 'change: 0.2080206900597354', 'is_elite: False']\n", + "Id: 5_24 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_98', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_24', 'origin': '3_98~CUW~4_63#MGNP'} Metrics: ['ELUC: -10.627600610150036', 'NSGA-II_crowding_distance: 0.4890714405992229', 'NSGA-II_rank: 1', 'change: 0.18131798772309257', 'is_elite: True']\n", + "Id: 5_86 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_86', 'origin': '1_1~CUW~4_63#MGNP'} Metrics: ['ELUC: -10.876645409116017', 'NSGA-II_crowding_distance: 0.3149727702738535', 'NSGA-II_rank: 1', 'change: 0.22928834115337476', 'is_elite: True']\n", + "Id: 6_27 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '4_25'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_27', 'origin': '5_86~CUW~4_25#MGNP'} Metrics: ['ELUC: -10.983647984089576', 'NSGA-II_crowding_distance: 0.3401237330714793', 'NSGA-II_rank: 3', 'change: 0.26143329989575287', 'is_elite: False']\n", + "Id: 6_78 Identity: {'ancestor_count': 5, 'ancestor_ids': ['4_25', '5_86'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_78', 'origin': '4_25~CUW~5_86#MGNP'} Metrics: ['ELUC: -11.297619860170858', 'NSGA-II_crowding_distance: 0.25603661096367103', 'NSGA-II_rank: 2', 'change: 0.24501071558929294', 'is_elite: False']\n", + "Id: 6_100 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_84', '5_83'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_100', 'origin': '5_84~CUW~5_83#MGNP'} Metrics: ['ELUC: -11.705825661841445', 'NSGA-II_crowding_distance: 0.15019502273352103', 'NSGA-II_rank: 2', 'change: 0.25431646311548506', 'is_elite: False']\n", + "Id: 6_36 Identity: {'ancestor_count': 2, 'ancestor_ids': ['5_95', '2_49'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_36', 'origin': '5_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.831188180809306', 'NSGA-II_crowding_distance: 0.4086491842566599', 'NSGA-II_rank: 3', 'change: 0.2812548908156084', 'is_elite: False']\n", + "Id: 6_98 Identity: {'ancestor_count': 4, 'ancestor_ids': ['5_95', '4_25'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_98', 'origin': '5_95~CUW~4_25#MGNP'} Metrics: ['ELUC: -12.576872619747272', 'NSGA-II_crowding_distance: 0.2453705183939509', 'NSGA-II_rank: 1', 'change: 0.24221909630126015', 'is_elite: True']\n", + "Id: 4_25 Identity: {'ancestor_count': 3, 'ancestor_ids': ['3_22', '3_19'], 'birth_generation': 4, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '4_25', 'origin': '3_22~CUW~3_19#MGNP'} Metrics: ['ELUC: -12.76599072488195', 'NSGA-II_crowding_distance: 0.15323166357394602', 'NSGA-II_rank: 2', 'change: 0.2610445789338331', 'is_elite: False']\n", + "Id: 6_84 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '5_62'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_84', 'origin': '5_83~CUW~5_62#MGNP'} Metrics: ['ELUC: -13.41178157234282', 'NSGA-II_crowding_distance: 0.07718213707614625', 'NSGA-II_rank: 2', 'change: 0.26755148103425247', 'is_elite: False']\n", + "Id: 6_13 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_62', '5_36'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_13', 'origin': '5_62~CUW~5_36#MGNP'} Metrics: ['ELUC: -13.465236832951895', 'NSGA-II_crowding_distance: 0.05336627103532876', 'NSGA-II_rank: 2', 'change: 0.27011505668628716', 'is_elite: False']\n", + "Id: 6_92 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_36', '5_51'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_92', 'origin': '5_36~CUW~5_51#MGNP'} Metrics: ['ELUC: -13.48566453462559', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.33578009271847553', 'is_elite: False']\n", + "Id: 6_72 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_69', '5_62'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_72', 'origin': '5_69~CUW~5_62#MGNP'} Metrics: ['ELUC: -13.619503947159528', 'NSGA-II_crowding_distance: 0.18252411708097102', 'NSGA-II_rank: 1', 'change: 0.25595428095483963', 'is_elite: False']\n", + "Id: 6_39 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_63', '2_49'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_39', 'origin': '4_63~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.719534968261337', 'NSGA-II_crowding_distance: 0.24118120189211437', 'NSGA-II_rank: 2', 'change: 0.27646288375580597', 'is_elite: False']\n", + "Id: 5_36 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_36', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.924512332555354', 'NSGA-II_crowding_distance: 0.12057250556908654', 'NSGA-II_rank: 1', 'change: 0.273810363948219', 'is_elite: False']\n", + "Id: 6_75 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_62', '4_63'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_75', 'origin': '5_62~CUW~4_63#MGNP'} Metrics: ['ELUC: -14.663538829728823', 'NSGA-II_crowding_distance: 0.17580417947176036', 'NSGA-II_rank: 1', 'change: 0.27421283588756856', 'is_elite: False']\n", + "Id: 6_43 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_51', '5_83'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_43', 'origin': '5_51~CUW~5_83#MGNP'} Metrics: ['ELUC: -15.720367152445363', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.3021098524948486', 'is_elite: False']\n", + "Id: 6_63 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '5_36'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_63', 'origin': '2_49~CUW~5_36#MGNP'} Metrics: ['ELUC: -16.135138289780475', 'NSGA-II_crowding_distance: 0.3989883154563309', 'NSGA-II_rank: 3', 'change: 0.2929148999176946', 'is_elite: False']\n", + "Id: 6_49 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '5_84'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_49', 'origin': '5_83~CUW~5_84#MGNP'} Metrics: ['ELUC: -16.325001303201883', 'NSGA-II_crowding_distance: 0.3343858613516928', 'NSGA-II_rank: 2', 'change: 0.2883229231250243', 'is_elite: False']\n", + "Id: 5_62 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '4_11'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_62', 'origin': '4_25~CUW~4_11#MGNP'} Metrics: ['ELUC: -16.588633123347925', 'NSGA-II_crowding_distance: 0.18943279426041904', 'NSGA-II_rank: 1', 'change: 0.2810554623800883', 'is_elite: False']\n", + "Id: 6_16 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_62', '4_63'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_16', 'origin': '5_62~CUW~4_63#MGNP'} Metrics: ['ELUC: -16.843924652301524', 'NSGA-II_crowding_distance: 0.08635017876078072', 'NSGA-II_rank: 1', 'change: 0.2937335407323959', 'is_elite: False']\n", + "Id: 6_76 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_43', '5_69'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_76', 'origin': '5_43~CUW~5_69#MGNP'} Metrics: ['ELUC: -17.06481024085145', 'NSGA-II_crowding_distance: 0.03408741819615671', 'NSGA-II_rank: 1', 'change: 0.298739558927903', 'is_elite: False']\n", + "Id: 6_40 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_83'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_40', 'origin': '1_1~CUW~5_83#MGNP'} Metrics: ['ELUC: -17.099414993798053', 'NSGA-II_crowding_distance: 0.03313486923692022', 'NSGA-II_rank: 1', 'change: 0.29956871683353176', 'is_elite: False']\n", + "Id: 6_11 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_69'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_11', 'origin': '1_1~CUW~5_69#MGNP'} Metrics: ['ELUC: -17.291713872068527', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30587942191375717', 'is_elite: False']\n", + "Id: 6_82 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '5_34'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_82', 'origin': '5_83~CUW~5_34#MGNP'} Metrics: ['ELUC: -17.443076199899487', 'NSGA-II_crowding_distance: 0.0346127518660709', 'NSGA-II_rank: 1', 'change: 0.3022069755824079', 'is_elite: False']\n", + "Id: 6_32 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_34', '5_62'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_32', 'origin': '5_34~CUW~5_62#MGNP'} Metrics: ['ELUC: -17.534652206561855', 'NSGA-II_crowding_distance: 0.011438908476041896', 'NSGA-II_rank: 1', 'change: 0.3025102809967692', 'is_elite: False']\n", + "Id: 6_46 Identity: {'ancestor_count': 4, 'ancestor_ids': ['2_49', '4_25'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_46', 'origin': '2_49~CUW~4_25#MGNP'} Metrics: ['ELUC: -17.594903252289548', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030524712633272', 'is_elite: False']\n", + "Id: 6_65 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '4_25'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_65', 'origin': '5_86~CUW~4_25#MGNP'} Metrics: ['ELUC: -17.5969957176467', 'NSGA-II_crowding_distance: 0.005277898088166125', 'NSGA-II_rank: 1', 'change: 0.30300802929919335', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 5_83 Identity: {'ancestor_count': 4, 'ancestor_ids': ['4_25', '4_24'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_83', 'origin': '4_25~CUW~4_24#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 6_20 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_20', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 6_29 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '5_69'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_29', 'origin': '5_83~CUW~5_69#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 6_37 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_83', '5_69'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_37', 'origin': '5_83~CUW~5_69#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 6_87 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_87', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 6_95 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_96', '5_83'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_95', 'origin': '5_96~CUW~5_83#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 6.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 7...:\n", + "PopulationResponse:\n", + " Generation: 7\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/7/20240219-203013\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 7 and asking ESP for generation 8...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 7 data persisted.\n", + "Evaluated candidates:\n", + "Id: 7_62 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '2_49'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_62', 'origin': '5_24~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 7_79 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_79', 'origin': '2_49~CUW~6_55#MGNP'} Metrics: ['ELUC: 20.14387528024776', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.281303852606476', 'is_elite: False']\n", + "Id: 7_29 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_86'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_29', 'origin': '1_1~CUW~5_86#MGNP'} Metrics: ['ELUC: 10.23559070469387', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.21330597268497445', 'is_elite: False']\n", + "Id: 7_87 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_16', '6_30'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_87', 'origin': '6_16~CUW~6_30#MGNP'} Metrics: ['ELUC: 10.235332455675335', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23845172735808265', 'is_elite: False']\n", + "Id: 7_12 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_81'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_12', 'origin': '1_1~CUW~6_81#MGNP'} Metrics: ['ELUC: 9.428109882475212', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.13474509033514726', 'is_elite: False']\n", + "Id: 7_18 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_98', '6_81'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_18', 'origin': '6_98~CUW~6_81#MGNP'} Metrics: ['ELUC: 7.94823899879432', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23141038867621924', 'is_elite: False']\n", + "Id: 7_39 Identity: {'ancestor_count': 5, 'ancestor_ids': ['6_47', '5_62'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_39', 'origin': '6_47~CUW~5_62#MGNP'} Metrics: ['ELUC: 7.423059167578343', 'NSGA-II_crowding_distance: 0.4285081449327095', 'NSGA-II_rank: 9', 'change: 0.2359636548598037', 'is_elite: False']\n", + "Id: 7_56 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_56', 'origin': '5_86~CUW~1_1#MGNP'} Metrics: ['ELUC: 6.933180752383442', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.21292766679359018', 'is_elite: False']\n", + "Id: 7_53 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_16', '5_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_53', 'origin': '6_16~CUW~5_95#MGNP'} Metrics: ['ELUC: 6.316853758142231', 'NSGA-II_crowding_distance: 1.2411582628372062', 'NSGA-II_rank: 9', 'change: 0.24350943755686708', 'is_elite: False']\n", + "Id: 7_98 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_30', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_98', 'origin': '6_30~CUW~1_1#MGNP'} Metrics: ['ELUC: 3.5389764820541254', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.12950332655037552', 'is_elite: False']\n", + "Id: 7_70 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_70', 'origin': '2_49~CUW~5_24#MGNP'} Metrics: ['ELUC: 3.462490613607816', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.34354234561690206', 'is_elite: False']\n", + "Id: 7_22 Identity: {'ancestor_count': 5, 'ancestor_ids': ['6_98', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_22', 'origin': '6_98~CUW~5_24#MGNP'} Metrics: ['ELUC: 3.447567284089476', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3394711166136909', 'is_elite: False']\n", + "Id: 7_40 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_30', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_40', 'origin': '6_30~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.4804901341959122', 'NSGA-II_crowding_distance: 0.3523930242813886', 'NSGA-II_rank: 5', 'change: 0.13731092670728462', 'is_elite: False']\n", + "Id: 7_58 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '6_47'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_58', 'origin': '5_24~CUW~6_47#MGNP'} Metrics: ['ELUC: 1.6033311281277716', 'NSGA-II_crowding_distance: 0.6409890813307808', 'NSGA-II_rank: 6', 'change: 0.167376807436336', 'is_elite: False']\n", + "Id: 7_55 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_81'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_55', 'origin': '1_1~CUW~6_81#MGNP'} Metrics: ['ELUC: 1.5968583514404053', 'NSGA-II_crowding_distance: 0.2897638019201501', 'NSGA-II_rank: 6', 'change: 0.16823456715266524', 'is_elite: False']\n", + "Id: 7_28 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_55', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_28', 'origin': '6_55~CUW~6_95#MGNP'} Metrics: ['ELUC: 1.294062570207649', 'NSGA-II_crowding_distance: 1.217163471761332', 'NSGA-II_rank: 8', 'change: 0.21978212204951852', 'is_elite: False']\n", + "Id: 7_51 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_51', 'origin': '6_95~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.1239886383653497', 'NSGA-II_crowding_distance: 0.6798375147261545', 'NSGA-II_rank: 7', 'change: 0.2145864976896729', 'is_elite: False']\n", + "Id: 7_60 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_81', '5_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_60', 'origin': '6_81~CUW~5_95#MGNP'} Metrics: ['ELUC: 0.34041429697380554', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07720641703781876', 'is_elite: False']\n", + "Id: 7_41 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_30', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_41', 'origin': '6_30~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.27272297248803956', 'NSGA-II_crowding_distance: 0.4001453081482731', 'NSGA-II_rank: 5', 'change: 0.14570944170435995', 'is_elite: False']\n", + "Id: 7_31 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '6_47'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_31', 'origin': '1_1~CUW~6_47#MGNP'} Metrics: ['ELUC: 0.16126415081557421', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04487647684703198', 'is_elite: False']\n", + "Id: 7_93 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_93', 'origin': '1_1~CUW~6_95#MGNP'} Metrics: ['ELUC: 0.039528917001747876', 'NSGA-II_crowding_distance: 0.6509522064126497', 'NSGA-II_rank: 6', 'change: 0.19989064545505936', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 7_65 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '5_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_65', 'origin': '1_1~CUW~5_95#MGNP'} Metrics: ['ELUC: -0.026038688360007365', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03906309829822916', 'is_elite: False']\n", + "Id: 7_24 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_84', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_24', 'origin': '5_84~CUW~6_55#MGNP'} Metrics: ['ELUC: -0.2395355648801436', 'NSGA-II_crowding_distance: 0.6565008081909629', 'NSGA-II_rank: 5', 'change: 0.16930890890533026', 'is_elite: False']\n", + "Id: 7_83 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '5_84'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_83', 'origin': '1_1~CUW~5_84#MGNP'} Metrics: ['ELUC: -0.3929285901013026', 'NSGA-II_crowding_distance: 0.20313597098653324', 'NSGA-II_rank: 1', 'change: 0.03138828367811136', 'is_elite: False']\n", + "Id: 7_45 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_30', '6_30'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_45', 'origin': '6_30~CUW~6_30#MGNP'} Metrics: ['ELUC: -0.46376322701505723', 'NSGA-II_crowding_distance: 0.9336356500663752', 'NSGA-II_rank: 4', 'change: 0.14424287030016575', 'is_elite: False']\n", + "Id: 7_44 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '6_30'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_44', 'origin': '2_49~CUW~6_30#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.4357656194770193', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 7_75 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_36', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_75', 'origin': '5_36~CUW~6_95#MGNP'} Metrics: ['ELUC: -0.5731810767378624', 'NSGA-II_crowding_distance: 0.30641985478487255', 'NSGA-II_rank: 8', 'change: 0.2388280478715676', 'is_elite: False']\n", + "Id: 7_89 Identity: {'ancestor_count': 3, 'ancestor_ids': ['5_84', '5_84'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_89', 'origin': '5_84~CUW~5_84#MGNP'} Metrics: ['ELUC: -0.7286698419356162', 'NSGA-II_crowding_distance: 0.5470234827472613', 'NSGA-II_rank: 3', 'change: 0.05349193034122042', 'is_elite: False']\n", + "Id: 7_43 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_43', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8693521098257426', 'NSGA-II_crowding_distance: 1.5714918550672907', 'NSGA-II_rank: 9', 'change: 0.25098404829157966', 'is_elite: False']\n", + "Id: 7_80 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_55', '6_47'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_80', 'origin': '6_55~CUW~6_47#MGNP'} Metrics: ['ELUC: -0.8720814199009451', 'NSGA-II_crowding_distance: 0.5583045508911594', 'NSGA-II_rank: 3', 'change: 0.15282111010185143', 'is_elite: False']\n", + "Id: 7_84 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_72'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_84', 'origin': '1_1~CUW~6_72#MGNP'} Metrics: ['ELUC: -0.8888305003732712', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2810167603797222', 'is_elite: False']\n", + "Id: 7_47 Identity: {'ancestor_count': 3, 'ancestor_ids': ['5_84', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_47', 'origin': '5_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.0862566155177313', 'NSGA-II_crowding_distance: 0.2601850512264659', 'NSGA-II_rank: 2', 'change: 0.04606555847138773', 'is_elite: False']\n", + "Id: 5_84 Identity: {'ancestor_count': 2, 'ancestor_ids': ['3_55', '3_98'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_84', 'origin': '3_55~CUW~3_98#MGNP'} Metrics: ['ELUC: -1.2063409912477865', 'NSGA-II_crowding_distance: 0.1649416311799845', 'NSGA-II_rank: 1', 'change: 0.04503737933356499', 'is_elite: False']\n", + "Id: 7_11 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '5_86'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_11', 'origin': '6_95~CUW~5_86#MGNP'} Metrics: ['ELUC: -1.5940498965214218', 'NSGA-II_crowding_distance: 0.6581727276942125', 'NSGA-II_rank: 7', 'change: 0.22393941866219513', 'is_elite: False']\n", + "Id: 6_30 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_34'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_30', 'origin': '1_1~CUW~5_34#MGNP'} Metrics: ['ELUC: -1.906782718708443', 'NSGA-II_crowding_distance: 0.20991366940397416', 'NSGA-II_rank: 3', 'change: 0.16106405330293716', 'is_elite: False']\n", + "Id: 7_95 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_81', '5_84'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_95', 'origin': '6_81~CUW~5_84#MGNP'} Metrics: ['ELUC: -1.9876941732807047', 'NSGA-II_crowding_distance: 0.6217534245958551', 'NSGA-II_rank: 2', 'change: 0.07825362813530909', 'is_elite: False']\n", + "Id: 7_20 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_86', '6_75'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_20', 'origin': '5_86~CUW~6_75#MGNP'} Metrics: ['ELUC: -2.19863150224019', 'NSGA-II_crowding_distance: 0.7803738499606105', 'NSGA-II_rank: 8', 'change: 0.2505055361009437', 'is_elite: False']\n", + "Id: 7_72 Identity: {'ancestor_count': 3, 'ancestor_ids': ['5_84', '5_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_72', 'origin': '5_84~CUW~5_95#MGNP'} Metrics: ['ELUC: -2.3512242917556505', 'NSGA-II_crowding_distance: 0.5189648003918443', 'NSGA-II_rank: 1', 'change: 0.04737030905368466', 'is_elite: True']\n", + "Id: 7_50 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_30'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_50', 'origin': '1_1~CUW~6_30#MGNP'} Metrics: ['ELUC: -2.472140188880872', 'NSGA-II_crowding_distance: 0.3474687381102755', 'NSGA-II_rank: 3', 'change: 0.16891088609368654', 'is_elite: False']\n", + "Id: 7_32 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_32', 'origin': '6_95~CUW~6_55#MGNP'} Metrics: ['ELUC: -2.831531894696106', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.27833814038081794', 'is_elite: False']\n", + "Id: 7_64 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_84', '5_86'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_64', 'origin': '5_84~CUW~5_86#MGNP'} Metrics: ['ELUC: -3.2326923244829127', 'NSGA-II_crowding_distance: 0.7346125119041371', 'NSGA-II_rank: 7', 'change: 0.24735522027766246', 'is_elite: False']\n", + "Id: 7_46 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_30', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_46', 'origin': '6_30~CUW~6_55#MGNP'} Metrics: ['ELUC: -3.677391081637058', 'NSGA-II_crowding_distance: 0.7677561559307791', 'NSGA-II_rank: 4', 'change: 0.18075523520491849', 'is_elite: False']\n", + "Id: 7_33 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_47', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_33', 'origin': '6_47~CUW~6_95#MGNP'} Metrics: ['ELUC: -3.7871797459789964', 'NSGA-II_crowding_distance: 0.6675265595274766', 'NSGA-II_rank: 5', 'change: 0.2037443083224427', 'is_elite: False']\n", + "Id: 7_49 Identity: {'ancestor_count': 5, 'ancestor_ids': ['6_98', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_49', 'origin': '6_98~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.9849175741488487', 'NSGA-II_crowding_distance: 0.43665254404076426', 'NSGA-II_rank: 6', 'change: 0.22309026173806654', 'is_elite: False']\n", + "Id: 6_81 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_24'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_81', 'origin': '1_1~CUW~5_24#MGNP'} Metrics: ['ELUC: -4.352363265593337', 'NSGA-II_crowding_distance: 0.5609847905172913', 'NSGA-II_rank: 2', 'change: 0.1610902550614279', 'is_elite: False']\n", + "Id: 7_73 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_55', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_73', 'origin': '6_55~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.107704741006599', 'NSGA-II_crowding_distance: 0.6453450035727122', 'NSGA-II_rank: 1', 'change: 0.1336775652061672', 'is_elite: True']\n", + "Id: 7_21 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_62', '6_98'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_21', 'origin': '5_62~CUW~6_98#MGNP'} Metrics: ['ELUC: -5.156653227199534', 'NSGA-II_crowding_distance: 0.25151263655428835', 'NSGA-II_rank: 6', 'change: 0.22392268357174203', 'is_elite: False']\n", + "Id: 7_97 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_97', 'origin': '5_86~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.285054614435543', 'NSGA-II_crowding_distance: 0.41873711482961684', 'NSGA-II_rank: 3', 'change: 0.17233798851025373', 'is_elite: False']\n", + "Id: 7_71 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_47', '6_16'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_71', 'origin': '6_47~CUW~6_16#MGNP'} Metrics: ['ELUC: -5.376142705079062', 'NSGA-II_crowding_distance: 0.2524846632696296', 'NSGA-II_rank: 6', 'change: 0.2510143626396134', 'is_elite: False']\n", + "Id: 7_76 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_62', '6_30'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_76', 'origin': '5_62~CUW~6_30#MGNP'} Metrics: ['ELUC: -5.9272061912743945', 'NSGA-II_crowding_distance: 0.6630947981888635', 'NSGA-II_rank: 5', 'change: 0.20687522720088541', 'is_elite: False']\n", + "Id: 7_23 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_84', '5_62'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_23', 'origin': '5_84~CUW~5_62#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.9455993285290515', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 6_55 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '1_1'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_55', 'origin': '5_24~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.051883813402863', 'NSGA-II_crowding_distance: 0.26905876353624697', 'NSGA-II_rank: 2', 'change: 0.165238013657982', 'is_elite: False']\n", + "Id: 7_27 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_55', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_27', 'origin': '6_55~CUW~6_55#MGNP'} Metrics: ['ELUC: -6.4628878575819755', 'NSGA-II_crowding_distance: 0.7785423362953301', 'NSGA-II_rank: 4', 'change: 0.18143945033867076', 'is_elite: False']\n", + "Id: 7_19 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_19', 'origin': '6_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.517522287716019', 'NSGA-II_crowding_distance: 0.13636594865998566', 'NSGA-II_rank: 6', 'change: 0.2522688371583228', 'is_elite: False']\n", + "Id: 7_77 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '5_84'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_77', 'origin': '5_24~CUW~5_84#MGNP'} Metrics: ['ELUC: -6.643952714842163', 'NSGA-II_crowding_distance: 0.2515016628289327', 'NSGA-II_rank: 3', 'change: 0.18037900337343787', 'is_elite: False']\n", + "Id: 7_66 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_30', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_66', 'origin': '6_30~CUW~5_24#MGNP'} Metrics: ['ELUC: -7.193845876840465', 'NSGA-II_crowding_distance: 0.3181106918418508', 'NSGA-II_rank: 3', 'change: 0.1917895438032242', 'is_elite: False']\n", + "Id: 7_100 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_100', 'origin': '1_1~CUW~6_55#MGNP'} Metrics: ['ELUC: -7.224173299592141', 'NSGA-II_crowding_distance: 0.4271161535264346', 'NSGA-II_rank: 1', 'change: 0.1572314298524543', 'is_elite: True']\n", + "Id: 7_34 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '6_30'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_34', 'origin': '6_95~CUW~6_30#MGNP'} Metrics: ['ELUC: -7.575426217331219', 'NSGA-II_crowding_distance: 0.0988535425858052', 'NSGA-II_rank: 6', 'change: 0.25345120255961917', 'is_elite: False']\n", + "Id: 7_68 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_72', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_68', 'origin': '6_72~CUW~5_24#MGNP'} Metrics: ['ELUC: -7.738592786906153', 'NSGA-II_crowding_distance: 0.162029618508633', 'NSGA-II_rank: 6', 'change: 0.2573163876294377', 'is_elite: False']\n", + "Id: 7_16 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_84', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_16', 'origin': '5_84~CUW~5_24#MGNP'} Metrics: ['ELUC: -7.807885630828381', 'NSGA-II_crowding_distance: 0.2682451954305738', 'NSGA-II_rank: 2', 'change: 0.18016373804617977', 'is_elite: False']\n", + "Id: 7_14 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_55', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_14', 'origin': '6_55~CUW~5_24#MGNP'} Metrics: ['ELUC: -8.104631439410925', 'NSGA-II_crowding_distance: 0.13949829523083623', 'NSGA-II_rank: 2', 'change: 0.20518671735292054', 'is_elite: False']\n", + "Id: 7_17 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_30', '5_86'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_17', 'origin': '6_30~CUW~5_86#MGNP'} Metrics: ['ELUC: -8.318876199513133', 'NSGA-II_crowding_distance: 0.4093757392421895', 'NSGA-II_rank: 3', 'change: 0.2205456912487705', 'is_elite: False']\n", + "Id: 7_26 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '5_84'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_26', 'origin': '2_49~CUW~5_84#MGNP'} Metrics: ['ELUC: -8.345495465874375', 'NSGA-II_crowding_distance: 0.2869854528146914', 'NSGA-II_rank: 6', 'change: 0.272549814501854', 'is_elite: False']\n", + "Id: 7_42 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_72', '5_84'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_42', 'origin': '6_72~CUW~5_84#MGNP'} Metrics: ['ELUC: -8.373803887455628', 'NSGA-II_crowding_distance: 0.6602981235798787', 'NSGA-II_rank: 4', 'change: 0.24315295772148296', 'is_elite: False']\n", + "Id: 7_54 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_54', 'origin': '1_1~CUW~5_24#MGNP'} Metrics: ['ELUC: -8.429578134951747', 'NSGA-II_crowding_distance: 0.24917808898249472', 'NSGA-II_rank: 2', 'change: 0.20764132474784042', 'is_elite: False']\n", + "Id: 7_63 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_72', '5_62'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_63', 'origin': '6_72~CUW~5_62#MGNP'} Metrics: ['ELUC: -8.466371773505811', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.3002496512044687', 'is_elite: False']\n", + "Id: 7_91 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_81', '6_72'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_91', 'origin': '6_81~CUW~6_72#MGNP'} Metrics: ['ELUC: -8.732395003907614', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29439763643708355', 'is_elite: False']\n", + "Id: 7_38 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_76', '2_49'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_38', 'origin': '6_76~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.741731259373502', 'NSGA-II_crowding_distance: 0.7056130814341024', 'NSGA-II_rank: 5', 'change: 0.2506219337836314', 'is_elite: False']\n", + "Id: 7_94 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '6_98'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_94', 'origin': '2_49~CUW~6_98#MGNP'} Metrics: ['ELUC: -8.975914424633604', 'NSGA-II_crowding_distance: 0.3280113693387851', 'NSGA-II_rank: 5', 'change: 0.28733080396093674', 'is_elite: False']\n", + "Id: 7_69 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '5_84'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_69', 'origin': '2_49~CUW~5_84#MGNP'} Metrics: ['ELUC: -9.07460208225303', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.3029316400066044', 'is_elite: False']\n", + "Id: 7_86 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_86', 'origin': '1_1~CUW~5_24#MGNP'} Metrics: ['ELUC: -9.395952939760912', 'NSGA-II_crowding_distance: 0.2832167688843282', 'NSGA-II_rank: 3', 'change: 0.24249795660786413', 'is_elite: False']\n", + "Id: 7_35 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_30', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_35', 'origin': '6_30~CUW~5_24#MGNP'} Metrics: ['ELUC: -9.624108594314587', 'NSGA-II_crowding_distance: 0.2607844256898995', 'NSGA-II_rank: 4', 'change: 0.2489843183757444', 'is_elite: False']\n", + "Id: 7_88 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_86', '6_72'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_88', 'origin': '5_86~CUW~6_72#MGNP'} Metrics: ['ELUC: -10.091476262515059', 'NSGA-II_crowding_distance: 0.1380566793468515', 'NSGA-II_rank: 4', 'change: 0.2614822577160259', 'is_elite: False']\n", + "Id: 7_99 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_95', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_99', 'origin': '5_95~CUW~5_24#MGNP'} Metrics: ['ELUC: -10.154600498113554', 'NSGA-II_crowding_distance: 0.2742958478976511', 'NSGA-II_rank: 1', 'change: 0.1754721305780146', 'is_elite: True']\n", + "Id: 7_37 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_82', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_37', 'origin': '6_82~CUW~6_95#MGNP'} Metrics: ['ELUC: -10.19634194572545', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.26468537684558174', 'is_elite: False']\n", + "Id: 7_36 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_55', '5_86'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_36', 'origin': '6_55~CUW~5_86#MGNP'} Metrics: ['ELUC: -10.431635668552172', 'NSGA-II_crowding_distance: 0.3180043675764743', 'NSGA-II_rank: 3', 'change: 0.243223392492376', 'is_elite: False']\n", + "Id: 5_24 Identity: {'ancestor_count': 4, 'ancestor_ids': ['3_98', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_24', 'origin': '3_98~CUW~4_63#MGNP'} Metrics: ['ELUC: -10.627600610150036', 'NSGA-II_crowding_distance: 0.17602120838661037', 'NSGA-II_rank: 1', 'change: 0.18131798772309257', 'is_elite: False']\n", + "Id: 5_86 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '4_63'], 'birth_generation': 5, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '5_86', 'origin': '1_1~CUW~4_63#MGNP'} Metrics: ['ELUC: -10.876645409116017', 'NSGA-II_crowding_distance: 0.24845194953102384', 'NSGA-II_rank: 2', 'change: 0.22928834115337476', 'is_elite: False']\n", + "Id: 7_59 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_84', '5_86'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_59', 'origin': '5_84~CUW~5_86#MGNP'} Metrics: ['ELUC: -10.957720716077398', 'NSGA-II_crowding_distance: 0.190695779404853', 'NSGA-II_rank: 2', 'change: 0.23521774283693112', 'is_elite: False']\n", + "Id: 7_96 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_95', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_96', 'origin': '5_95~CUW~6_95#MGNP'} Metrics: ['ELUC: -11.102721686805586', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.281969133282084', 'is_elite: False']\n", + "Id: 7_81 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_95', '6_82'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_81', 'origin': '5_95~CUW~6_82#MGNP'} Metrics: ['ELUC: -11.25003704136919', 'NSGA-II_crowding_distance: 0.3149727702738535', 'NSGA-II_rank: 1', 'change: 0.209403040700186', 'is_elite: True']\n", + "Id: 7_30 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_72', '5_86'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_30', 'origin': '6_72~CUW~5_86#MGNP'} Metrics: ['ELUC: -11.509391290841933', 'NSGA-II_crowding_distance: 0.2217707166192068', 'NSGA-II_rank: 2', 'change: 0.2701147288989871', 'is_elite: False']\n", + "Id: 7_78 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_24', '6_75'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_78', 'origin': '5_24~CUW~6_75#MGNP'} Metrics: ['ELUC: -12.369142571934626', 'NSGA-II_crowding_distance: 0.1147762478079227', 'NSGA-II_rank: 2', 'change: 0.2725402282421162', 'is_elite: False']\n", + "Id: 6_98 Identity: {'ancestor_count': 4, 'ancestor_ids': ['5_95', '4_25'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_98', 'origin': '5_95~CUW~4_25#MGNP'} Metrics: ['ELUC: -12.576872619747272', 'NSGA-II_crowding_distance: 0.5453987952665894', 'NSGA-II_rank: 1', 'change: 0.24221909630126015', 'is_elite: True']\n", + "Id: 7_92 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '2_49'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_92', 'origin': '6_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.605738498008016', 'NSGA-II_crowding_distance: 0.2583567475718031', 'NSGA-II_rank: 2', 'change: 0.2839300666977884', 'is_elite: False']\n", + "Id: 7_74 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_16', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_74', 'origin': '6_16~CUW~6_95#MGNP'} Metrics: ['ELUC: -16.130637831248894', 'NSGA-II_crowding_distance: 0.3557608949817194', 'NSGA-II_rank: 2', 'change: 0.28418847763616617', 'is_elite: False']\n", + "Id: 7_67 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_67', 'origin': '5_86~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.720979465924962', 'NSGA-II_crowding_distance: 0.4443542062944511', 'NSGA-II_rank: 1', 'change: 0.27929430774028374', 'is_elite: True']\n", + "Id: 7_57 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_36', '6_98'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_57', 'origin': '5_36~CUW~6_98#MGNP'} Metrics: ['ELUC: -17.194197316589204', 'NSGA-II_crowding_distance: 0.10843637467890058', 'NSGA-II_rank: 1', 'change: 0.2964470657309485', 'is_elite: False']\n", + "Id: 7_90 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_81', '6_75'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_90', 'origin': '6_81~CUW~6_75#MGNP'} Metrics: ['ELUC: -17.400138446140993', 'NSGA-II_crowding_distance: 0.037367522625563546', 'NSGA-II_rank: 1', 'change: 0.3001237681826233', 'is_elite: False']\n", + "Id: 7_52 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_62', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_52', 'origin': '5_62~CUW~6_95#MGNP'} Metrics: ['ELUC: -17.48192556871074', 'NSGA-II_crowding_distance: 0.018863345003451343', 'NSGA-II_rank: 1', 'change: 0.3027138646166412', 'is_elite: False']\n", + "Id: 7_13 Identity: {'ancestor_count': 5, 'ancestor_ids': ['6_98', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_13', 'origin': '6_98~CUW~5_24#MGNP'} Metrics: ['ELUC: -17.577858702448403', 'NSGA-II_crowding_distance: 0.007594437292739294', 'NSGA-II_rank: 1', 'change: 0.3027362024329743', 'is_elite: False']\n", + "Id: 7_25 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_86', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_25', 'origin': '5_86~CUW~6_95#MGNP'} Metrics: ['ELUC: -17.582426787589544', 'NSGA-II_crowding_distance: 0.1542001052253076', 'NSGA-II_rank: 2', 'change: 0.3030210258476442', 'is_elite: False']\n", + "Id: 7_48 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_48', 'origin': '2_49~CUW~5_24#MGNP'} Metrics: ['ELUC: -17.584180626732522', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.303040577111273', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 6_95 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_96', '5_83'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_95', 'origin': '5_96~CUW~5_83#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 7_15 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_15', 'origin': '6_95~CUW~6_95#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 7_61 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '6_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_61', 'origin': '6_95~CUW~6_95#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 7_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '5_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_82', 'origin': '2_49~CUW~5_95#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 7_85 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_85', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 7.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 8...:\n", + "PopulationResponse:\n", + " Generation: 8\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/8/20240219-203729\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 8 and asking ESP for generation 9...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 8 data persisted.\n", + "Evaluated candidates:\n", + "Id: 8_15 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '2_49'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_15', 'origin': '7_100~CUW~2_49#MGNP'} Metrics: ['ELUC: 21.79828288944762', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2939717289222936', 'is_elite: False']\n", + "Id: 8_80 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_80', 'origin': '5_24~CUW~7_85#MGNP'} Metrics: ['ELUC: 9.537111594571996', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.27155212546102897', 'is_elite: False']\n", + "Id: 8_70 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_52', '7_67'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_70', 'origin': '7_52~CUW~7_67#MGNP'} Metrics: ['ELUC: 7.816999731889701', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2610037702553727', 'is_elite: False']\n", + "Id: 8_20 Identity: {'ancestor_count': 5, 'ancestor_ids': ['7_72', '6_98'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_20', 'origin': '7_72~CUW~6_98#MGNP'} Metrics: ['ELUC: 6.0908368251825795', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23768100941669584', 'is_elite: False']\n", + "Id: 8_44 Identity: {'ancestor_count': 5, 'ancestor_ids': ['6_98', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_44', 'origin': '6_98~CUW~7_85#MGNP'} Metrics: ['ELUC: 5.668232800692353', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23991515486397802', 'is_elite: False']\n", + "Id: 8_69 Identity: {'ancestor_count': 5, 'ancestor_ids': ['6_98', '7_72'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_69', 'origin': '6_98~CUW~7_72#MGNP'} Metrics: ['ELUC: 5.331677837777278', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.21815256081146658', 'is_elite: False']\n", + "Id: 8_43 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '7_67'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_43', 'origin': '2_49~CUW~7_67#MGNP'} Metrics: ['ELUC: 5.075152025304512', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 13', 'change: 0.2985639514720306', 'is_elite: False']\n", + "Id: 8_34 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_81', '7_99'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_34', 'origin': '7_81~CUW~7_99#MGNP'} Metrics: ['ELUC: 4.922383882663163', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23212714698423859', 'is_elite: False']\n", + "Id: 8_72 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_24', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_72', 'origin': '5_24~CUW~7_85#MGNP'} Metrics: ['ELUC: 3.9777479911420164', 'NSGA-II_crowding_distance: 0.935846954259333', 'NSGA-II_rank: 11', 'change: 0.26996520305647986', 'is_elite: False']\n", + "Id: 8_45 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '7_100'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_45', 'origin': '1_1~CUW~7_100#MGNP'} Metrics: ['ELUC: 3.0797609108952204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.14667070689032422', 'is_elite: False']\n", + "Id: 8_56 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_56', 'origin': '7_100~CUW~7_85#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 8_24 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_72', '7_73'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_24', 'origin': '7_72~CUW~7_73#MGNP'} Metrics: ['ELUC: 2.2540819050241088', 'NSGA-II_crowding_distance: 0.9405260422556893', 'NSGA-II_rank: 5', 'change: 0.14933588408759854', 'is_elite: False']\n", + "Id: 8_42 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '7_100'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_42', 'origin': '1_1~CUW~7_100#MGNP'} Metrics: ['ELUC: 1.1130804811437784', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.10415407406435907', 'is_elite: False']\n", + "Id: 8_73 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_73', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.7449133693999727', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3352117780069957', 'is_elite: False']\n", + "Id: 8_97 Identity: {'ancestor_count': 4, 'ancestor_ids': ['7_83', '7_72'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_97', 'origin': '7_83~CUW~7_72#MGNP'} Metrics: ['ELUC: 0.3965060965000096', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05137395422195905', 'is_elite: False']\n", + "Id: 8_13 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_13', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.367601443383257', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04106305235128674', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 8_50 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '7_100'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_50', 'origin': '1_1~CUW~7_100#MGNP'} Metrics: ['ELUC: -0.031453046230910366', 'NSGA-II_crowding_distance: 0.9802922978477422', 'NSGA-II_rank: 4', 'change: 0.13538863905183002', 'is_elite: False']\n", + "Id: 8_67 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_67', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 1.2828445018899655', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 8_83 Identity: {'ancestor_count': 4, 'ancestor_ids': ['7_72', '5_84'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_83', 'origin': '7_72~CUW~5_84#MGNP'} Metrics: ['ELUC: -1.2156548267158382', 'NSGA-II_crowding_distance: 0.5354678319656474', 'NSGA-II_rank: 3', 'change: 0.0651433587216276', 'is_elite: False']\n", + "Id: 8_47 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_83', '7_100'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_47', 'origin': '7_83~CUW~7_100#MGNP'} Metrics: ['ELUC: -1.4350502367835296', 'NSGA-II_crowding_distance: 0.22464256639540336', 'NSGA-II_rank: 2', 'change: 0.05968501718248571', 'is_elite: False']\n", + "Id: 8_19 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '7_73'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_19', 'origin': '1_1~CUW~7_73#MGNP'} Metrics: ['ELUC: -1.4569753792333768', 'NSGA-II_crowding_distance: 0.488832096740164', 'NSGA-II_rank: 2', 'change: 0.07301708644178095', 'is_elite: False']\n", + "Id: 8_62 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_84', '5_24'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_62', 'origin': '5_84~CUW~5_24#MGNP'} Metrics: ['ELUC: -1.7062183305209497', 'NSGA-II_crowding_distance: 0.5969450740477056', 'NSGA-II_rank: 3', 'change: 0.1358277054388946', 'is_elite: False']\n", + "Id: 8_60 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '7_72'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_60', 'origin': '1_1~CUW~7_72#MGNP'} Metrics: ['ELUC: -1.715672688295017', 'NSGA-II_crowding_distance: 0.2760702120430292', 'NSGA-II_rank: 1', 'change: 0.039302720306517665', 'is_elite: True']\n", + "Id: 8_29 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_98', '7_13'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_29', 'origin': '6_98~CUW~7_13#MGNP'} Metrics: ['ELUC: -2.0296256458728466', 'NSGA-II_crowding_distance: 0.7588076482937552', 'NSGA-II_rank: 11', 'change: 0.2759712693269847', 'is_elite: False']\n", + "Id: 8_53 Identity: {'ancestor_count': 4, 'ancestor_ids': ['7_85', '7_83'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_53', 'origin': '7_85~CUW~7_83#MGNP'} Metrics: ['ELUC: -2.2790008621442386', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3250182420837454', 'is_elite: False']\n", + "Id: 7_72 Identity: {'ancestor_count': 3, 'ancestor_ids': ['5_84', '5_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_72', 'origin': '5_84~CUW~5_95#MGNP'} Metrics: ['ELUC: -2.3512242917556505', 'NSGA-II_crowding_distance: 0.40123549707302747', 'NSGA-II_rank: 1', 'change: 0.04737030905368466', 'is_elite: True']\n", + "Id: 8_91 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_99', '7_83'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_91', 'origin': '7_99~CUW~7_83#MGNP'} Metrics: ['ELUC: -3.088544583983554', 'NSGA-II_crowding_distance: 0.6505997543732145', 'NSGA-II_rank: 3', 'change: 0.1671885281098981', 'is_elite: False']\n", + "Id: 8_74 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_57', '7_81'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_74', 'origin': '7_57~CUW~7_81#MGNP'} Metrics: ['ELUC: -3.7557867603515396', 'NSGA-II_crowding_distance: 1.4538346030504168', 'NSGA-II_rank: 10', 'change: 0.26279285112641027', 'is_elite: False']\n", + "Id: 8_32 Identity: {'ancestor_count': 3, 'ancestor_ids': ['7_85', '1_1'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_32', 'origin': '7_85~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.948501912692243', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.28878850875724493', 'is_elite: False']\n", + "Id: 8_54 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_90', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_54', 'origin': '7_90~CUW~7_85#MGNP'} Metrics: ['ELUC: -4.092333521721964', 'NSGA-II_crowding_distance: 1.0641530457406672', 'NSGA-II_rank: 11', 'change: 0.2816633735892364', 'is_elite: False']\n", + "Id: 8_88 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_67', '7_52'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_88', 'origin': '7_67~CUW~7_52#MGNP'} Metrics: ['ELUC: -4.248569898859136', 'NSGA-II_crowding_distance: 1.4104109408150993', 'NSGA-II_rank: 9', 'change: 0.24852534257247058', 'is_elite: False']\n", + "Id: 8_93 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '7_67'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_93', 'origin': '1_1~CUW~7_67#MGNP'} Metrics: ['ELUC: -4.594656855402642', 'NSGA-II_crowding_distance: 1.3418378004667282', 'NSGA-II_rank: 5', 'change: 0.19401364041349195', 'is_elite: False']\n", + "Id: 8_63 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_63', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.863945112366333', 'NSGA-II_crowding_distance: 0.7182512925463458', 'NSGA-II_rank: 10', 'change: 0.2665162348002175', 'is_elite: False']\n", + "Id: 8_84 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_73', '5_84'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_84', 'origin': '7_73~CUW~5_84#MGNP'} Metrics: ['ELUC: -5.007294972204233', 'NSGA-II_crowding_distance: 0.43614029009459176', 'NSGA-II_rank: 1', 'change: 0.10316260631832895', 'is_elite: True']\n", + "Id: 7_73 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_55', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_73', 'origin': '6_55~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.107704741006599', 'NSGA-II_crowding_distance: 0.46940147703112756', 'NSGA-II_rank: 2', 'change: 0.1336775652061672', 'is_elite: False']\n", + "Id: 8_99 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '1_1'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_99', 'origin': '7_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.31236566854442', 'NSGA-II_crowding_distance: 0.34902087589621134', 'NSGA-II_rank: 2', 'change: 0.1391447687232281', 'is_elite: False']\n", + "Id: 8_87 Identity: {'ancestor_count': 7, 'ancestor_ids': ['5_24', '7_73'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_87', 'origin': '5_24~CUW~7_73#MGNP'} Metrics: ['ELUC: -5.514161446817875', 'NSGA-II_crowding_distance: 0.9199200180733579', 'NSGA-II_rank: 4', 'change: 0.18323135844660707', 'is_elite: False']\n", + "Id: 8_14 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_57', '7_100'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_14', 'origin': '7_57~CUW~7_100#MGNP'} Metrics: ['ELUC: -5.853187984044676', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.33044313714555745', 'is_elite: False']\n", + "Id: 8_55 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_73', '7_100'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_55', 'origin': '7_73~CUW~7_100#MGNP'} Metrics: ['ELUC: -5.905358943315342', 'NSGA-II_crowding_distance: 0.3072948397411071', 'NSGA-II_rank: 1', 'change: 0.11719009165102766', 'is_elite: True']\n", + "Id: 8_82 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '6_98'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_82', 'origin': '1_1~CUW~6_98#MGNP'} Metrics: ['ELUC: -5.982716940658888', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23553292849414392', 'is_elite: False']\n", + "Id: 8_37 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_72', '7_81'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_37', 'origin': '7_72~CUW~7_81#MGNP'} Metrics: ['ELUC: -5.985836235948117', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2882719057150233', 'is_elite: False']\n", + "Id: 8_46 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_72', '7_52'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_46', 'origin': '7_72~CUW~7_52#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 8_85 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_95', '1_1'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_85', 'origin': '6_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.232294296421473', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.25270137306949636', 'is_elite: False']\n", + "Id: 8_66 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_72', '7_81'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_66', 'origin': '7_72~CUW~7_81#MGNP'} Metrics: ['ELUC: -6.584339636489008', 'NSGA-II_crowding_distance: 1.298649927050875', 'NSGA-II_rank: 7', 'change: 0.2338247324878503', 'is_elite: False']\n", + "Id: 8_25 Identity: {'ancestor_count': 7, 'ancestor_ids': ['6_98', '7_73'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_25', 'origin': '6_98~CUW~7_73#MGNP'} Metrics: ['ELUC: -6.844976862123781', 'NSGA-II_crowding_distance: 1.102976872935931', 'NSGA-II_rank: 6', 'change: 0.22804629716479793', 'is_elite: False']\n", + "Id: 7_100 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_100', 'origin': '1_1~CUW~6_55#MGNP'} Metrics: ['ELUC: -7.224173299592141', 'NSGA-II_crowding_distance: 0.29603757917285467', 'NSGA-II_rank: 1', 'change: 0.1572314298524543', 'is_elite: True']\n", + "Id: 8_76 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '6_98'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_76', 'origin': '7_100~CUW~6_98#MGNP'} Metrics: ['ELUC: -7.357975379703899', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2729027263379347', 'is_elite: False']\n", + "Id: 8_94 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_99', '5_24'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_94', 'origin': '7_99~CUW~5_24#MGNP'} Metrics: ['ELUC: -7.5417212132198514', 'NSGA-II_crowding_distance: 0.3998363089744721', 'NSGA-II_rank: 4', 'change: 0.1937507575685935', 'is_elite: False']\n", + "Id: 8_40 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_73', '2_49'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_40', 'origin': '7_73~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.624851025339489', 'NSGA-II_crowding_distance: 0.7410658036031383', 'NSGA-II_rank: 7', 'change: 0.2629804051310488', 'is_elite: False']\n", + "Id: 8_71 Identity: {'ancestor_count': 6, 'ancestor_ids': ['6_98', '7_99'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_71', 'origin': '6_98~CUW~7_99#MGNP'} Metrics: ['ELUC: -7.662510572885705', 'NSGA-II_crowding_distance: 0.3765976961292695', 'NSGA-II_rank: 6', 'change: 0.23613171188744786', 'is_elite: False']\n", + "Id: 8_27 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_90', '7_67'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_27', 'origin': '7_90~CUW~7_67#MGNP'} Metrics: ['ELUC: -7.974802809770063', 'NSGA-II_crowding_distance: 0.33583577133347864', 'NSGA-II_rank: 6', 'change: 0.24521895445577677', 'is_elite: False']\n", + "Id: 8_81 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '5_24'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_81', 'origin': '7_100~CUW~5_24#MGNP'} Metrics: ['ELUC: -8.041643396173374', 'NSGA-II_crowding_distance: 0.5568280938024536', 'NSGA-II_rank: 3', 'change: 0.17510044148138298', 'is_elite: False']\n", + "Id: 8_39 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_57', '6_98'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_39', 'origin': '7_57~CUW~6_98#MGNP'} Metrics: ['ELUC: -8.159511726483746', 'NSGA-II_crowding_distance: 0.4409599127312681', 'NSGA-II_rank: 6', 'change: 0.2531491260687112', 'is_elite: False']\n", + "Id: 8_92 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_90', '1_1'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_92', 'origin': '7_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.441681096028184', 'NSGA-II_crowding_distance: 0.23642346198680658', 'NSGA-II_rank: 4', 'change: 0.2127307175357888', 'is_elite: False']\n", + "Id: 8_28 Identity: {'ancestor_count': 7, 'ancestor_ids': ['6_98', '7_81'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_28', 'origin': '6_98~CUW~7_81#MGNP'} Metrics: ['ELUC: -8.471929886330345', 'NSGA-II_crowding_distance: 0.900106630923233', 'NSGA-II_rank: 5', 'change: 0.2185726737643667', 'is_elite: False']\n", + "Id: 8_65 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_83', '7_100'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_65', 'origin': '7_83~CUW~7_100#MGNP'} Metrics: ['ELUC: -8.504028018607505', 'NSGA-II_crowding_distance: 0.40977711316365295', 'NSGA-II_rank: 2', 'change: 0.1749128007383111', 'is_elite: False']\n", + "Id: 8_22 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '7_72'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_22', 'origin': '7_67~CUW~7_72#MGNP'} Metrics: ['ELUC: -8.507353168284258', 'NSGA-II_crowding_distance: 0.22780170928907092', 'NSGA-II_rank: 1', 'change: 0.1613644640444154', 'is_elite: False']\n", + "Id: 8_59 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '5_84'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_59', 'origin': '7_100~CUW~5_84#MGNP'} Metrics: ['ELUC: -8.58716451516034', 'NSGA-II_crowding_distance: 0.2779666273003106', 'NSGA-II_rank: 3', 'change: 0.19952207305866768', 'is_elite: False']\n", + "Id: 8_89 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_99', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_89', 'origin': '7_99~CUW~7_85#MGNP'} Metrics: ['ELUC: -8.653866410004971', 'NSGA-II_crowding_distance: 0.3058004655683916', 'NSGA-II_rank: 7', 'change: 0.27150815675052636', 'is_elite: False']\n", + "Id: 8_79 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_67', '7_73'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_79', 'origin': '7_67~CUW~7_73#MGNP'} Metrics: ['ELUC: -8.816463612273676', 'NSGA-II_crowding_distance: 0.27010390870742707', 'NSGA-II_rank: 4', 'change: 0.2167934319369654', 'is_elite: False']\n", + "Id: 8_33 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '5_24'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_33', 'origin': '7_100~CUW~5_24#MGNP'} Metrics: ['ELUC: -8.830025594389626', 'NSGA-II_crowding_distance: 0.2865515869590274', 'NSGA-II_rank: 2', 'change: 0.19459620322792445', 'is_elite: False']\n", + "Id: 8_100 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '5_24'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_100', 'origin': '1_1~CUW~5_24#MGNP'} Metrics: ['ELUC: -9.279938222873742', 'NSGA-II_crowding_distance: 0.30569496439940724', 'NSGA-II_rank: 3', 'change: 0.21648258550168845', 'is_elite: False']\n", + "Id: 8_30 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '7_90'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_30', 'origin': '1_1~CUW~7_90#MGNP'} Metrics: ['ELUC: -9.548239820348792', 'NSGA-II_crowding_distance: 0.43150810581308224', 'NSGA-II_rank: 4', 'change: 0.2433484829291576', 'is_elite: False']\n", + "Id: 8_78 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '7_90'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_78', 'origin': '2_49~CUW~7_90#MGNP'} Metrics: ['ELUC: -9.939581825370173', 'NSGA-II_crowding_distance: 0.1299187369136805', 'NSGA-II_rank: 7', 'change: 0.27276916926007316', 'is_elite: False']\n", + "Id: 8_26 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_81', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_26', 'origin': '7_81~CUW~7_85#MGNP'} Metrics: ['ELUC: -10.088842493919106', 'NSGA-II_crowding_distance: 0.3955496073807335', 'NSGA-II_rank: 7', 'change: 0.27388587650645974', 'is_elite: False']\n", + "Id: 7_99 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_95', '5_24'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_99', 'origin': '5_95~CUW~5_24#MGNP'} Metrics: ['ELUC: -10.154600498113554', 'NSGA-II_crowding_distance: 0.15447589804908515', 'NSGA-II_rank: 1', 'change: 0.1754721305780146', 'is_elite: False']\n", + "Id: 8_51 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_73', '7_81'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_51', 'origin': '7_73~CUW~7_81#MGNP'} Metrics: ['ELUC: -10.228023039687352', 'NSGA-II_crowding_distance: 0.5395149722566742', 'NSGA-II_rank: 5', 'change: 0.2523153084327235', 'is_elite: False']\n", + "Id: 8_21 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_99', '7_72'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_21', 'origin': '7_99~CUW~7_72#MGNP'} Metrics: ['ELUC: -10.273537569652127', 'NSGA-II_crowding_distance: 0.2683443836525493', 'NSGA-II_rank: 1', 'change: 0.17748393585754124', 'is_elite: False']\n", + "Id: 8_64 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_85', '6_95'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_64', 'origin': '7_85~CUW~6_95#MGNP'} Metrics: ['ELUC: -10.76306524571793', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2939918375595533', 'is_elite: False']\n", + "Id: 8_12 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '7_81'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_12', 'origin': '7_100~CUW~7_81#MGNP'} Metrics: ['ELUC: -10.957282320342046', 'NSGA-II_crowding_distance: 0.287946626778817', 'NSGA-II_rank: 3', 'change: 0.22813935252635803', 'is_elite: False']\n", + "Id: 8_68 Identity: {'ancestor_count': 5, 'ancestor_ids': ['6_98', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_68', 'origin': '6_98~CUW~7_85#MGNP'} Metrics: ['ELUC: -11.000728543391068', 'NSGA-II_crowding_distance: 0.5611873557305902', 'NSGA-II_rank: 6', 'change: 0.2596441512826984', 'is_elite: False']\n", + "Id: 8_90 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '2_49'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_90', 'origin': '7_67~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.223915689221405', 'NSGA-II_crowding_distance: 0.15936732682107776', 'NSGA-II_rank: 5', 'change: 0.25826063511917313', 'is_elite: False']\n", + "Id: 7_81 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_95', '6_82'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_81', 'origin': '5_95~CUW~6_82#MGNP'} Metrics: ['ELUC: -11.25003704136919', 'NSGA-II_crowding_distance: 0.3365897921761847', 'NSGA-II_rank: 2', 'change: 0.209403040700186', 'is_elite: False']\n", + "Id: 8_57 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_81', '2_49'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_57', 'origin': '7_81~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.334645107307267', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2737622836574726', 'is_elite: False']\n", + "Id: 8_11 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_52', '7_73'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_11', 'origin': '7_52~CUW~7_73#MGNP'} Metrics: ['ELUC: -11.709368505414782', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2589633526790606', 'is_elite: False']\n", + "Id: 8_16 Identity: {'ancestor_count': 5, 'ancestor_ids': ['6_98', '6_98'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_16', 'origin': '6_98~CUW~6_98#MGNP'} Metrics: ['ELUC: -11.84966858444337', 'NSGA-II_crowding_distance: 0.18439499683430371', 'NSGA-II_rank: 3', 'change: 0.23778864349768628', 'is_elite: False']\n", + "Id: 8_61 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_24', '7_67'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_61', 'origin': '5_24~CUW~7_67#MGNP'} Metrics: ['ELUC: -11.937675719470262', 'NSGA-II_crowding_distance: 0.34976748447035844', 'NSGA-II_rank: 4', 'change: 0.2490983016866032', 'is_elite: False']\n", + "Id: 8_36 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_83', '7_52'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_36', 'origin': '7_83~CUW~7_52#MGNP'} Metrics: ['ELUC: -12.220714969070011', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.26778491562002465', 'is_elite: False']\n", + "Id: 6_98 Identity: {'ancestor_count': 4, 'ancestor_ids': ['5_95', '4_25'], 'birth_generation': 6, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '6_98', 'origin': '5_95~CUW~4_25#MGNP'} Metrics: ['ELUC: -12.576872619747272', 'NSGA-II_crowding_distance: 0.2480191595820106', 'NSGA-II_rank: 3', 'change: 0.24221909630126015', 'is_elite: False']\n", + "Id: 8_77 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '7_67'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_77', 'origin': '1_1~CUW~7_67#MGNP'} Metrics: ['ELUC: -12.607503804206983', 'NSGA-II_crowding_distance: 0.20250027790645203', 'NSGA-II_rank: 2', 'change: 0.2268417413130679', 'is_elite: False']\n", + "Id: 8_38 Identity: {'ancestor_count': 3, 'ancestor_ids': ['7_85', '5_84'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_38', 'origin': '7_85~CUW~5_84#MGNP'} Metrics: ['ELUC: -12.94429556185876', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2748842158503681', 'is_elite: False']\n", + "Id: 8_48 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_99', '5_24'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_48', 'origin': '7_99~CUW~5_24#MGNP'} Metrics: ['ELUC: -13.118067739939354', 'NSGA-II_crowding_distance: 0.31467823136992384', 'NSGA-II_rank: 1', 'change: 0.20524916209795535', 'is_elite: True']\n", + "Id: 8_31 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_99', '7_67'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_31', 'origin': '7_99~CUW~7_67#MGNP'} Metrics: ['ELUC: -13.421357242791062', 'NSGA-II_crowding_distance: 0.29981305964961524', 'NSGA-II_rank: 2', 'change: 0.2303200125123965', 'is_elite: False']\n", + "Id: 8_18 Identity: {'ancestor_count': 6, 'ancestor_ids': ['5_24', '7_99'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_18', 'origin': '5_24~CUW~7_99#MGNP'} Metrics: ['ELUC: -13.977962443144609', 'NSGA-II_crowding_distance: 0.2370593041297732', 'NSGA-II_rank: 1', 'change: 0.208511675608793', 'is_elite: False']\n", + "Id: 8_98 Identity: {'ancestor_count': 5, 'ancestor_ids': ['7_83', '6_98'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_98', 'origin': '7_83~CUW~6_98#MGNP'} Metrics: ['ELUC: -14.02532192491731', 'NSGA-II_crowding_distance: 0.19528836633250435', 'NSGA-II_rank: 1', 'change: 0.2605859923293615', 'is_elite: False']\n", + "Id: 8_35 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_83', '7_57'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_35', 'origin': '7_83~CUW~7_57#MGNP'} Metrics: ['ELUC: -14.154687170221639', 'NSGA-II_crowding_distance: 0.21601631587087727', 'NSGA-II_rank: 1', 'change: 0.26378229891930555', 'is_elite: False']\n", + "Id: 8_52 Identity: {'ancestor_count': 7, 'ancestor_ids': ['6_98', '7_81'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_52', 'origin': '6_98~CUW~7_81#MGNP'} Metrics: ['ELUC: -14.367170549857477', 'NSGA-II_crowding_distance: 0.41650913819803714', 'NSGA-II_rank: 2', 'change: 0.2796056047974602', 'is_elite: False']\n", + "Id: 8_17 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_85', '7_73'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_17', 'origin': '7_85~CUW~7_73#MGNP'} Metrics: ['ELUC: -16.197032269220422', 'NSGA-II_crowding_distance: 0.259775991584016', 'NSGA-II_rank: 2', 'change: 0.29866184049458705', 'is_elite: False']\n", + "Id: 7_67 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_67', 'origin': '5_86~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.720979465924962', 'NSGA-II_crowding_distance: 0.30098022912180616', 'NSGA-II_rank: 1', 'change: 0.27929430774028374', 'is_elite: True']\n", + "Id: 8_23 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_57', '6_98'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_23', 'origin': '7_57~CUW~6_98#MGNP'} Metrics: ['ELUC: -17.251083576064598', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30496414379124615', 'is_elite: False']\n", + "Id: 8_49 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_15', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_49', 'origin': '7_15~CUW~7_85#MGNP'} Metrics: ['ELUC: -17.27649003168862', 'NSGA-II_crowding_distance: 0.11733145808563125', 'NSGA-II_rank: 1', 'change: 0.30061013515772983', 'is_elite: False']\n", + "Id: 8_58 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_58', 'origin': '7_100~CUW~7_85#MGNP'} Metrics: ['ELUC: -17.41264288588486', 'NSGA-II_crowding_distance: 0.026314794657544174', 'NSGA-II_rank: 1', 'change: 0.30256565864275925', 'is_elite: False']\n", + "Id: 8_86 Identity: {'ancestor_count': 3, 'ancestor_ids': ['7_85', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_86', 'origin': '7_85~CUW~7_85#MGNP'} Metrics: ['ELUC: -17.597224637968832', 'NSGA-II_crowding_distance: 0.01203161335635658', 'NSGA-II_rank: 1', 'change: 0.30301891833317124', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 7_85 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_85', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 8_41 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_13', '6_98'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_41', 'origin': '7_13~CUW~6_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 8_75 Identity: {'ancestor_count': 3, 'ancestor_ids': ['7_85', '5_84'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_75', 'origin': '7_85~CUW~5_84#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 8_95 Identity: {'ancestor_count': 3, 'ancestor_ids': ['7_85', '1_1'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_95', 'origin': '7_85~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 8_96 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_96', 'origin': '2_49~CUW~7_85#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 8.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 9...:\n", + "PopulationResponse:\n", + " Generation: 9\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/9/20240219-204447\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 9 and asking ESP for generation 10...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 9 data persisted.\n", + "Evaluated candidates:\n", + "Id: 9_16 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '2_49'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_16', 'origin': '7_67~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.732213895632082', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 16', 'change: 0.3033907215225191', 'is_elite: False']\n", + "Id: 9_66 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_66', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 21.96210853985355', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.2935762631706019', 'is_elite: False']\n", + "Id: 9_75 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_75', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 18.84761149215332', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.2741776817163123', 'is_elite: False']\n", + "Id: 9_31 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_86', '8_84'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_31', 'origin': '8_86~CUW~8_84#MGNP'} Metrics: ['ELUC: 7.751707523175299', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.24995405228802142', 'is_elite: False']\n", + "Id: 9_45 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '8_98'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_45', 'origin': '2_49~CUW~8_98#MGNP'} Metrics: ['ELUC: 5.737851227444576', 'NSGA-II_crowding_distance: 0.9734039998124268', 'NSGA-II_rank: 12', 'change: 0.25135384321312926', 'is_elite: False']\n", + "Id: 9_68 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_60', '8_21'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_68', 'origin': '8_60~CUW~8_21#MGNP'} Metrics: ['ELUC: 4.938182206550369', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.14210706752293936', 'is_elite: False']\n", + "Id: 9_76 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_72', '8_84'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_76', 'origin': '7_72~CUW~8_84#MGNP'} Metrics: ['ELUC: 2.238184400258366', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.1024300114145688', 'is_elite: False']\n", + "Id: 9_100 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_84', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_100', 'origin': '8_84~CUW~7_72#MGNP'} Metrics: ['ELUC: 2.1096666127309', 'NSGA-II_crowding_distance: 0.21697910880290386', 'NSGA-II_rank: 4', 'change: 0.11678405458253655', 'is_elite: False']\n", + "Id: 9_23 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_72', '7_67'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_23', 'origin': '7_72~CUW~7_67#MGNP'} Metrics: ['ELUC: 1.794063484380054', 'NSGA-II_crowding_distance: 0.1858936400223173', 'NSGA-II_rank: 4', 'change: 0.141159678252407', 'is_elite: False']\n", + "Id: 9_57 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '8_21'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_57', 'origin': '1_1~CUW~8_21#MGNP'} Metrics: ['ELUC: 1.373784439632766', 'NSGA-II_crowding_distance: 0.2574278370537348', 'NSGA-II_rank: 4', 'change: 0.14566551691383184', 'is_elite: False']\n", + "Id: 9_67 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_67', 'origin': '8_48~CUW~7_72#MGNP'} Metrics: ['ELUC: 0.9003883363120463', 'NSGA-II_crowding_distance: 0.5505019710507665', 'NSGA-II_rank: 5', 'change: 0.16870761375317608', 'is_elite: False']\n", + "Id: 9_19 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '8_96'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_19', 'origin': '1_1~CUW~8_96#MGNP'} Metrics: ['ELUC: 0.12188383075796634', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2707948364336908', 'is_elite: False']\n", + "Id: 9_50 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_18', '2_49'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_50', 'origin': '8_18~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.015220566638817918', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.22439278727655845', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 9_25 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_99', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_25', 'origin': '7_99~CUW~7_72#MGNP'} Metrics: ['ELUC: -0.05417939551704059', 'NSGA-II_crowding_distance: 0.6080121851538187', 'NSGA-II_rank: 5', 'change: 0.17033295444389565', 'is_elite: False']\n", + "Id: 9_72 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '7_100'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_72', 'origin': '1_1~CUW~7_100#MGNP'} Metrics: ['ELUC: -0.3134723106214497', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.08007715800420015', 'is_elite: False']\n", + "Id: 9_27 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_84', '8_96'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_27', 'origin': '8_84~CUW~8_96#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 9_63 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '8_96'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_63', 'origin': '8_48~CUW~8_96#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 9_94 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_22', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_94', 'origin': '8_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1452736987013081', 'NSGA-II_crowding_distance: 0.5905109552718757', 'NSGA-II_rank: 4', 'change: 0.15792290906241818', 'is_elite: False']\n", + "Id: 9_20 Identity: {'ancestor_count': 4, 'ancestor_ids': ['8_96', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_20', 'origin': '8_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4776369402814635', 'NSGA-II_crowding_distance: 0.9550516931153394', 'NSGA-II_rank: 12', 'change: 0.2642091956342481', 'is_elite: False']\n", + "Id: 9_87 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_55', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_87', 'origin': '8_55~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5474395372787417', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.0446514999091543', 'is_elite: False']\n", + "Id: 9_88 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_60', '8_55'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_88', 'origin': '8_60~CUW~8_55#MGNP'} Metrics: ['ELUC: -1.6949021906213713', 'NSGA-II_crowding_distance: 0.5303076730481876', 'NSGA-II_rank: 2', 'change: 0.08347176790600512', 'is_elite: False']\n", + "Id: 8_60 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '7_72'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_60', 'origin': '1_1~CUW~7_72#MGNP'} Metrics: ['ELUC: -1.715672688295017', 'NSGA-II_crowding_distance: 0.2760702120430292', 'NSGA-II_rank: 1', 'change: 0.039302720306517665', 'is_elite: True']\n", + "Id: 9_96 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_55', '8_98'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_96', 'origin': '8_55~CUW~8_98#MGNP'} Metrics: ['ELUC: -1.897087815756614', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23285863518485797', 'is_elite: False']\n", + "Id: 9_91 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_49', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_91', 'origin': '8_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.14382113842204', 'NSGA-II_crowding_distance: 1.0265960001875731', 'NSGA-II_rank: 12', 'change: 0.26982917776655446', 'is_elite: False']\n", + "Id: 7_72 Identity: {'ancestor_count': 3, 'ancestor_ids': ['5_84', '5_95'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_72', 'origin': '5_84~CUW~5_95#MGNP'} Metrics: ['ELUC: -2.3512242917556505', 'NSGA-II_crowding_distance: 0.1157009605608992', 'NSGA-II_rank: 1', 'change: 0.04737030905368466', 'is_elite: False']\n", + "Id: 9_11 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_11', 'origin': '1_1~CUW~8_48#MGNP'} Metrics: ['ELUC: -2.4333642881461164', 'NSGA-II_crowding_distance: 0.8038105482248512', 'NSGA-II_rank: 3', 'change: 0.14940811703728976', 'is_elite: False']\n", + "Id: 9_70 Identity: {'ancestor_count': 5, 'ancestor_ids': ['8_60', '8_60'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_70', 'origin': '8_60~CUW~8_60#MGNP'} Metrics: ['ELUC: -2.5994397184712144', 'NSGA-II_crowding_distance: 0.22769201299498787', 'NSGA-II_rank: 1', 'change: 0.058827509618748136', 'is_elite: False']\n", + "Id: 9_26 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_100', '8_55'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_26', 'origin': '7_100~CUW~8_55#MGNP'} Metrics: ['ELUC: -3.477165514872989', 'NSGA-II_crowding_distance: 0.2855345365121283', 'NSGA-II_rank: 1', 'change: 0.09620096193689191', 'is_elite: True']\n", + "Id: 9_39 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_72', '8_58'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_39', 'origin': '7_72~CUW~8_58#MGNP'} Metrics: ['ELUC: -3.533098861214167', 'NSGA-II_crowding_distance: 1.1476869321426946', 'NSGA-II_rank: 11', 'change: 0.24002609447177578', 'is_elite: False']\n", + "Id: 9_24 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_55', '8_21'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_24', 'origin': '8_55~CUW~8_21#MGNP'} Metrics: ['ELUC: -4.030522632690716', 'NSGA-II_crowding_distance: 0.4863230148317382', 'NSGA-II_rank: 2', 'change: 0.14103600087882134', 'is_elite: False']\n", + "Id: 9_62 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_22', '8_98'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_62', 'origin': '8_22~CUW~8_98#MGNP'} Metrics: ['ELUC: -4.283456929595892', 'NSGA-II_crowding_distance: 1.4040314214943832', 'NSGA-II_rank: 11', 'change: 0.25003641994131653', 'is_elite: False']\n", + "Id: 8_84 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_73', '5_84'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_84', 'origin': '7_73~CUW~5_84#MGNP'} Metrics: ['ELUC: -5.007294972204233', 'NSGA-II_crowding_distance: 0.20844827709960384', 'NSGA-II_rank: 1', 'change: 0.10316260631832895', 'is_elite: False']\n", + "Id: 9_77 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_18', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_77', 'origin': '8_18~CUW~7_72#MGNP'} Metrics: ['ELUC: -5.139768275837529', 'NSGA-II_crowding_distance: 0.9417451376942474', 'NSGA-II_rank: 5', 'change: 0.1955998376203481', 'is_elite: False']\n", + "Id: 9_81 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_55', '8_18'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_81', 'origin': '8_55~CUW~8_18#MGNP'} Metrics: ['ELUC: -5.185827931426749', 'NSGA-II_crowding_distance: 0.40057809200311945', 'NSGA-II_rank: 4', 'change: 0.1863313189195532', 'is_elite: False']\n", + "Id: 9_21 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_55', '8_35'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_21', 'origin': '8_55~CUW~8_35#MGNP'} Metrics: ['ELUC: -5.414122189157924', 'NSGA-II_crowding_distance: 1.0721635050441132', 'NSGA-II_rank: 10', 'change: 0.23607824719421208', 'is_elite: False']\n", + "Id: 9_46 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '7_67'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_46', 'origin': '7_100~CUW~7_67#MGNP'} Metrics: ['ELUC: -5.426012526616787', 'NSGA-II_crowding_distance: 0.39085539435720174', 'NSGA-II_rank: 4', 'change: 0.18755387672049692', 'is_elite: False']\n", + "Id: 9_35 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_55', '8_96'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_35', 'origin': '8_55~CUW~8_96#MGNP'} Metrics: ['ELUC: -5.558735763912634', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3008629543009472', 'is_elite: False']\n", + "Id: 9_51 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_84', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_51', 'origin': '8_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.567677326180487', 'NSGA-II_crowding_distance: 0.30320102861847836', 'NSGA-II_rank: 2', 'change: 0.14589358500707192', 'is_elite: False']\n", + "Id: 9_79 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_72', '8_21'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_79', 'origin': '7_72~CUW~8_21#MGNP'} Metrics: ['ELUC: -5.584291894732309', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.22034160776200662', 'is_elite: False']\n", + "Id: 8_55 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_73', '7_100'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_55', 'origin': '7_73~CUW~7_100#MGNP'} Metrics: ['ELUC: -5.905358943315342', 'NSGA-II_crowding_distance: 0.11543004120340244', 'NSGA-II_rank: 1', 'change: 0.11719009165102766', 'is_elite: False']\n", + "Id: 9_69 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_55', '8_55'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_69', 'origin': '8_55~CUW~8_55#MGNP'} Metrics: ['ELUC: -5.923401829296897', 'NSGA-II_crowding_distance: 0.06389883298276998', 'NSGA-II_rank: 1', 'change: 0.12205774250302318', 'is_elite: False']\n", + "Id: 9_34 Identity: {'ancestor_count': 4, 'ancestor_ids': ['7_72', '8_96'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_34', 'origin': '7_72~CUW~8_96#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 9_42 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_72', '8_84'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_42', 'origin': '7_72~CUW~8_84#MGNP'} Metrics: ['ELUC: -6.197283690416284', 'NSGA-II_crowding_distance: 0.19186479853770466', 'NSGA-II_rank: 1', 'change: 0.1313020264673932', 'is_elite: False']\n", + "Id: 9_97 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '8_58'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_97', 'origin': '7_67~CUW~8_58#MGNP'} Metrics: ['ELUC: -6.436614131613425', 'NSGA-II_crowding_distance: 0.9094282314381659', 'NSGA-II_rank: 10', 'change: 0.24909338761907956', 'is_elite: False']\n", + "Id: 9_89 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '8_60'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_89', 'origin': '8_48~CUW~8_60#MGNP'} Metrics: ['ELUC: -6.909624142933166', 'NSGA-II_crowding_distance: 0.5922391091206303', 'NSGA-II_rank: 3', 'change: 0.17176513453967393', 'is_elite: False']\n", + "Id: 9_84 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_84', 'origin': '7_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.0960549934972486', 'NSGA-II_crowding_distance: 0.3819416638994161', 'NSGA-II_rank: 2', 'change: 0.16935808317418272', 'is_elite: False']\n", + "Id: 9_14 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_14', 'origin': '2_49~CUW~8_48#MGNP'} Metrics: ['ELUC: -7.2155917307502975', 'NSGA-II_crowding_distance: 0.9278364949558868', 'NSGA-II_rank: 10', 'change: 0.2698249978776714', 'is_elite: False']\n", + "Id: 7_100 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_100', 'origin': '1_1~CUW~6_55#MGNP'} Metrics: ['ELUC: -7.224173299592141', 'NSGA-II_crowding_distance: 0.3954564185709489', 'NSGA-II_rank: 1', 'change: 0.1572314298524543', 'is_elite: True']\n", + "Id: 9_93 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_96', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_93', 'origin': '8_96~CUW~8_48#MGNP'} Metrics: ['ELUC: -7.684258955664983', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.28927797781027403', 'is_elite: False']\n", + "Id: 9_98 Identity: {'ancestor_count': 6, 'ancestor_ids': ['8_98', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_98', 'origin': '8_98~CUW~7_72#MGNP'} Metrics: ['ELUC: -8.557814872078227', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2289938690349358', 'is_elite: False']\n", + "Id: 9_86 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '7_100'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_86', 'origin': '8_21~CUW~7_100#MGNP'} Metrics: ['ELUC: -8.977411764093096', 'NSGA-II_crowding_distance: 0.38058322381153575', 'NSGA-II_rank: 3', 'change: 0.18791329947352972', 'is_elite: False']\n", + "Id: 9_28 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '8_60'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_28', 'origin': '8_48~CUW~8_60#MGNP'} Metrics: ['ELUC: -9.061860416757227', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.22379530985923157', 'is_elite: False']\n", + "Id: 9_99 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_48', '8_55'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_99', 'origin': '8_48~CUW~8_55#MGNP'} Metrics: ['ELUC: -9.159795522911157', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.20729130607233304', 'is_elite: False']\n", + "Id: 9_78 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_84', '8_22'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_78', 'origin': '8_84~CUW~8_22#MGNP'} Metrics: ['ELUC: -9.323805058768563', 'NSGA-II_crowding_distance: 0.342987176874636', 'NSGA-II_rank: 2', 'change: 0.18328808466084764', 'is_elite: False']\n", + "Id: 9_33 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_60', '7_100'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_33', 'origin': '8_60~CUW~7_100#MGNP'} Metrics: ['ELUC: -9.590519782553194', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2059674373674397', 'is_elite: False']\n", + "Id: 9_61 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '8_35'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_61', 'origin': '7_100~CUW~8_35#MGNP'} Metrics: ['ELUC: -10.053810728886853', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.2666537142758742', 'is_elite: False']\n", + "Id: 9_65 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '8_35'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_65', 'origin': '2_49~CUW~8_35#MGNP'} Metrics: ['ELUC: -10.178335313874001', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29402192563664364', 'is_elite: False']\n", + "Id: 9_36 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '7_67'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_36', 'origin': '8_21~CUW~7_67#MGNP'} Metrics: ['ELUC: -10.275871117862462', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2341375445483867', 'is_elite: False']\n", + "Id: 9_53 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_72', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_53', 'origin': '7_72~CUW~8_48#MGNP'} Metrics: ['ELUC: -10.319943981510438', 'NSGA-II_crowding_distance: 0.9165890449217848', 'NSGA-II_rank: 5', 'change: 0.2045791779863195', 'is_elite: False']\n", + "Id: 9_54 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '8_18'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_54', 'origin': '2_49~CUW~8_18#MGNP'} Metrics: ['ELUC: -10.431349936064501', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2671774588872158', 'is_elite: False']\n", + "Id: 9_13 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '7_100'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_13', 'origin': '8_48~CUW~7_100#MGNP'} Metrics: ['ELUC: -10.48618879663678', 'NSGA-II_crowding_distance: 0.4463000704425583', 'NSGA-II_rank: 4', 'change: 0.20165033459084236', 'is_elite: False']\n", + "Id: 9_44 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '8_60'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_44', 'origin': '8_21~CUW~8_60#MGNP'} Metrics: ['ELUC: -10.649288859520745', 'NSGA-II_crowding_distance: 0.35525663768000665', 'NSGA-II_rank: 4', 'change: 0.21507507468291392', 'is_elite: False']\n", + "Id: 9_15 Identity: {'ancestor_count': 4, 'ancestor_ids': ['2_49', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_15', 'origin': '2_49~CUW~7_72#MGNP'} Metrics: ['ELUC: -10.798872586174763', 'NSGA-II_crowding_distance: 0.3685726421027421', 'NSGA-II_rank: 4', 'change: 0.2700762199840816', 'is_elite: False']\n", + "Id: 9_29 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '8_84'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_29', 'origin': '7_67~CUW~8_84#MGNP'} Metrics: ['ELUC: -11.014755612850314', 'NSGA-II_crowding_distance: 0.21831816242169078', 'NSGA-II_rank: 3', 'change: 0.1982374411417158', 'is_elite: False']\n", + "Id: 9_12 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_99', '8_55'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_12', 'origin': '7_99~CUW~8_55#MGNP'} Metrics: ['ELUC: -11.10368833187712', 'NSGA-II_crowding_distance: 0.12115647690916867', 'NSGA-II_rank: 3', 'change: 0.20704207630357835', 'is_elite: False']\n", + "Id: 9_74 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_74', 'origin': '8_48~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.352828169690808', 'NSGA-II_crowding_distance: 0.26615169087813817', 'NSGA-II_rank: 2', 'change: 0.18855629335677898', 'is_elite: False']\n", + "Id: 9_92 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '8_60'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_92', 'origin': '8_21~CUW~8_60#MGNP'} Metrics: ['ELUC: -11.619260633154786', 'NSGA-II_crowding_distance: 0.45736019270837425', 'NSGA-II_rank: 1', 'change: 0.15728478917744898', 'is_elite: True']\n", + "Id: 9_83 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '8_98'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_83', 'origin': '2_49~CUW~8_98#MGNP'} Metrics: ['ELUC: -11.678822283343203', 'NSGA-II_crowding_distance: 0.11763486450293265', 'NSGA-II_rank: 4', 'change: 0.277534857511122', 'is_elite: False']\n", + "Id: 9_40 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '8_96'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_40', 'origin': '7_100~CUW~8_96#MGNP'} Metrics: ['ELUC: -12.01556385308655', 'NSGA-II_crowding_distance: 0.3101422495949416', 'NSGA-II_rank: 4', 'change: 0.27926653188610273', 'is_elite: False']\n", + "Id: 9_95 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '8_22'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_95', 'origin': '8_48~CUW~8_22#MGNP'} Metrics: ['ELUC: -12.027680411770763', 'NSGA-II_crowding_distance: 0.10881174772858979', 'NSGA-II_rank: 3', 'change: 0.2117347474163686', 'is_elite: False']\n", + "Id: 9_41 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '8_84'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_41', 'origin': '7_67~CUW~8_84#MGNP'} Metrics: ['ELUC: -12.22398708235263', 'NSGA-II_crowding_distance: 0.10952651869539562', 'NSGA-II_rank: 3', 'change: 0.21553168567758413', 'is_elite: False']\n", + "Id: 9_49 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '8_21'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_49', 'origin': '8_48~CUW~8_21#MGNP'} Metrics: ['ELUC: -12.606660536818199', 'NSGA-II_crowding_distance: 0.13300138372954576', 'NSGA-II_rank: 2', 'change: 0.19851626471700184', 'is_elite: False']\n", + "Id: 9_71 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_72', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_71', 'origin': '7_72~CUW~8_48#MGNP'} Metrics: ['ELUC: -12.74337468102024', 'NSGA-II_crowding_distance: 0.46911341615315716', 'NSGA-II_rank: 3', 'change: 0.2273863238151825', 'is_elite: False']\n", + "Id: 9_85 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_85', 'origin': '1_1~CUW~8_48#MGNP'} Metrics: ['ELUC: -12.835343825804099', 'NSGA-II_crowding_distance: 0.35606433478550026', 'NSGA-II_rank: 2', 'change: 0.19873739874611698', 'is_elite: False']\n", + "Id: 9_52 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_52', 'origin': '7_100~CUW~8_48#MGNP'} Metrics: ['ELUC: -13.035800244164475', 'NSGA-II_crowding_distance: 0.2459955548660218', 'NSGA-II_rank: 1', 'change: 0.19507241859196478', 'is_elite: True']\n", + "Id: 8_48 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_99', '5_24'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_48', 'origin': '7_99~CUW~5_24#MGNP'} Metrics: ['ELUC: -13.118067739939354', 'NSGA-II_crowding_distance: 0.16600310333783092', 'NSGA-II_rank: 1', 'change: 0.20524916209795535', 'is_elite: False']\n", + "Id: 9_82 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_98', '8_35'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_82', 'origin': '8_98~CUW~8_35#MGNP'} Metrics: ['ELUC: -14.041191471566226', 'NSGA-II_crowding_distance: 0.47601277358199934', 'NSGA-II_rank: 2', 'change: 0.26701852582572316', 'is_elite: False']\n", + "Id: 9_90 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '7_67'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_90', 'origin': '2_49~CUW~7_67#MGNP'} Metrics: ['ELUC: -14.562323099396831', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.30568825452425885', 'is_elite: False']\n", + "Id: 9_56 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '8_18'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_56', 'origin': '8_21~CUW~8_18#MGNP'} Metrics: ['ELUC: -14.642231008397209', 'NSGA-II_crowding_distance: 0.4530756200006505', 'NSGA-II_rank: 1', 'change: 0.2173424200253688', 'is_elite: True']\n", + "Id: 9_55 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '8_35'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_55', 'origin': '1_1~CUW~8_35#MGNP'} Metrics: ['ELUC: -14.996993238176909', 'NSGA-II_crowding_distance: 0.584923232359049', 'NSGA-II_rank: 3', 'change: 0.28761255205932856', 'is_elite: False']\n", + "Id: 9_17 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '2_49'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_17', 'origin': '7_67~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.132294415719578', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.33569565130306106', 'is_elite: False']\n", + "Id: 9_38 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_96', '8_22'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_38', 'origin': '8_96~CUW~8_22#MGNP'} Metrics: ['ELUC: -15.342163266096717', 'NSGA-II_crowding_distance: 0.21863733967977333', 'NSGA-II_rank: 2', 'change: 0.2807299550942237', 'is_elite: False']\n", + "Id: 9_37 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_18', '8_96'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_37', 'origin': '8_18~CUW~8_96#MGNP'} Metrics: ['ELUC: -15.647833183711835', 'NSGA-II_crowding_distance: 0.21448996414715293', 'NSGA-II_rank: 2', 'change: 0.297269766690566', 'is_elite: False']\n", + "Id: 7_67 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_67', 'origin': '5_86~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.720979465924962', 'NSGA-II_crowding_distance: 0.34524035837831324', 'NSGA-II_rank: 1', 'change: 0.27929430774028374', 'is_elite: True']\n", + "Id: 9_22 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '7_67'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_22', 'origin': '7_67~CUW~7_67#MGNP'} Metrics: ['ELUC: -16.808265578319823', 'NSGA-II_crowding_distance: 0.10056705886781339', 'NSGA-II_rank: 1', 'change: 0.2835961749137504', 'is_elite: False']\n", + "Id: 9_60 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_67', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_60', 'origin': '7_67~CUW~8_48#MGNP'} Metrics: ['ELUC: -17.354212126690427', 'NSGA-II_crowding_distance: 0.10647891855625298', 'NSGA-II_rank: 1', 'change: 0.29855512351132424', 'is_elite: False']\n", + "Id: 9_18 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_18', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.397650450357833', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30260659979871984', 'is_elite: False']\n", + "Id: 9_30 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '8_35'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_30', 'origin': '7_100~CUW~8_35#MGNP'} Metrics: ['ELUC: -17.57463427721184', 'NSGA-II_crowding_distance: 0.028796012574174443', 'NSGA-II_rank: 1', 'change: 0.30236159827106734', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 8_96 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '7_85'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_96', 'origin': '2_49~CUW~7_85#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_32 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '8_22'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_32', 'origin': '2_49~CUW~8_22#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_43 Identity: {'ancestor_count': 4, 'ancestor_ids': ['8_96', '8_96'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_43', 'origin': '8_96~CUW~8_96#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_47 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_47', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_48 Identity: {'ancestor_count': 4, 'ancestor_ids': ['8_96', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_48', 'origin': '8_96~CUW~7_72#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_58 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '7_100'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_58', 'origin': '2_49~CUW~7_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_59 Identity: {'ancestor_count': 6, 'ancestor_ids': ['8_96', '7_99'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_59', 'origin': '8_96~CUW~7_99#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_64 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_64', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_73 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '8_35'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_73', 'origin': '2_49~CUW~8_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 9_80 Identity: {'ancestor_count': 4, 'ancestor_ids': ['8_96', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_80', 'origin': '8_96~CUW~7_72#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 9.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 10...:\n", + "PopulationResponse:\n", + " Generation: 10\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/10/20240219-205207\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 10 and asking ESP for generation 11...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 10 data persisted.\n", + "Evaluated candidates:\n", + "Id: 10_83 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '2_49'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_83', 'origin': '7_100~CUW~2_49#MGNP'} Metrics: ['ELUC: 22.751819707327233', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.29924311288491334', 'is_elite: False']\n", + "Id: 10_66 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_80', '8_84'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_66', 'origin': '9_80~CUW~8_84#MGNP'} Metrics: ['ELUC: 19.328337225115547', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26754640935359997', 'is_elite: False']\n", + "Id: 10_46 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '8_48'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_46', 'origin': '9_26~CUW~8_48#MGNP'} Metrics: ['ELUC: 7.838950322267432', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.16832428345438608', 'is_elite: False']\n", + "Id: 10_50 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_70', '9_42'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_50', 'origin': '9_70~CUW~9_42#MGNP'} Metrics: ['ELUC: 5.066062336164321', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.12511934191665397', 'is_elite: False']\n", + "Id: 10_82 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_82', 'origin': '8_48~CUW~1_1#MGNP'} Metrics: ['ELUC: 3.9672783147045703', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10205292037972258', 'is_elite: False']\n", + "Id: 10_70 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '8_60'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_70', 'origin': '9_92~CUW~8_60#MGNP'} Metrics: ['ELUC: 3.8913482900513903', 'NSGA-II_crowding_distance: 0.6645521932887152', 'NSGA-II_rank: 6', 'change: 0.1324709463670199', 'is_elite: False']\n", + "Id: 10_23 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_56', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_23', 'origin': '9_56~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.8162852638928015', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08434474829704607', 'is_elite: False']\n", + "Id: 10_97 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_97', 'origin': '1_1~CUW~9_80#MGNP'} Metrics: ['ELUC: 2.533541970703056', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2547442913862929', 'is_elite: False']\n", + "Id: 10_72 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_84', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_72', 'origin': '8_84~CUW~9_80#MGNP'} Metrics: ['ELUC: 2.5287121854547823', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.351722446169353', 'is_elite: False']\n", + "Id: 10_49 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '8_84'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_49', 'origin': '9_92~CUW~8_84#MGNP'} Metrics: ['ELUC: 2.368397077551161', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09643323495482982', 'is_elite: False']\n", + "Id: 10_65 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_56', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_65', 'origin': '9_56~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.9868338139077741', 'NSGA-II_crowding_distance: 0.281003076475327', 'NSGA-II_rank: 5', 'change: 0.10307343301574773', 'is_elite: False']\n", + "Id: 10_33 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_33', 'origin': '1_1~CUW~9_56#MGNP'} Metrics: ['ELUC: 1.6428036022467607', 'NSGA-II_crowding_distance: 0.9656260309021124', 'NSGA-II_rank: 5', 'change: 0.1302083224101047', 'is_elite: False']\n", + "Id: 10_31 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '7_67'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_31', 'origin': '7_100~CUW~7_67#MGNP'} Metrics: ['ELUC: 0.7660224179246133', 'NSGA-II_crowding_distance: 1.106797513771172', 'NSGA-II_rank: 6', 'change: 0.18443620636498037', 'is_elite: False']\n", + "Id: 10_78 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_56', '2_49'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_78', 'origin': '9_56~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.2227284772037819', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2794680853276243', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 10_18 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '7_72'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_18', 'origin': '1_1~CUW~7_72#MGNP'} Metrics: ['ELUC: -0.39769157846600006', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04080480567732779', 'is_elite: False']\n", + "Id: 10_79 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_60', '8_84'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_79', 'origin': '8_60~CUW~8_84#MGNP'} Metrics: ['ELUC: -0.49746981227769993', 'NSGA-II_crowding_distance: 0.10756985078436937', 'NSGA-II_rank: 3', 'change: 0.04553266570188018', 'is_elite: False']\n", + "Id: 10_67 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_52', '8_60'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_67', 'origin': '9_52~CUW~8_60#MGNP'} Metrics: ['ELUC: -0.7678530899146119', 'NSGA-II_crowding_distance: 0.7737148017077373', 'NSGA-II_rank: 4', 'change: 0.08808575403016042', 'is_elite: False']\n", + "Id: 10_92 Identity: {'ancestor_count': 8, 'ancestor_ids': ['2_49', '9_52'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_92', 'origin': '2_49~CUW~9_52#MGNP'} Metrics: ['ELUC: -0.8289099006238868', 'NSGA-II_crowding_distance: 1.2368116720679678', 'NSGA-II_rank: 8', 'change: 0.2265668064790469', 'is_elite: False']\n", + "Id: 10_32 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_32', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1278863127729122', 'NSGA-II_crowding_distance: 0.7155240475298735', 'NSGA-II_rank: 8', 'change: 0.24323330659263276', 'is_elite: False']\n", + "Id: 10_21 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '9_70'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_21', 'origin': '1_1~CUW~9_70#MGNP'} Metrics: ['ELUC: -1.1283496973191507', 'NSGA-II_crowding_distance: 0.8750052696197488', 'NSGA-II_rank: 3', 'change: 0.05225456972478767', 'is_elite: False']\n", + "Id: 10_62 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_62', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5532665672647405', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04064802450968653', 'is_elite: False']\n", + "Id: 10_43 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_43', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5784930716608523', 'NSGA-II_crowding_distance: 0.055317080358366785', 'NSGA-II_rank: 2', 'change: 0.0469310811840359', 'is_elite: False']\n", + "Id: 8_60 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '7_72'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_60', 'origin': '1_1~CUW~7_72#MGNP'} Metrics: ['ELUC: -1.715672688295017', 'NSGA-II_crowding_distance: 0.3065721012726798', 'NSGA-II_rank: 1', 'change: 0.039302720306517665', 'is_elite: True']\n", + "Id: 10_25 Identity: {'ancestor_count': 4, 'ancestor_ids': ['7_72', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_25', 'origin': '7_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.78711420518159', 'NSGA-II_crowding_distance: 0.106966558207895', 'NSGA-II_rank: 2', 'change: 0.049732168804367614', 'is_elite: False']\n", + "Id: 10_90 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_48', '8_84'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_90', 'origin': '8_48~CUW~8_84#MGNP'} Metrics: ['ELUC: -2.193036727817302', 'NSGA-II_crowding_distance: 1.2743178794051149', 'NSGA-II_rank: 7', 'change: 0.20934391672767083', 'is_elite: False']\n", + "Id: 10_29 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_84', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_29', 'origin': '8_84~CUW~9_80#MGNP'} Metrics: ['ELUC: -2.4027518013862386', 'NSGA-II_crowding_distance: 0.5935551864729574', 'NSGA-II_rank: 7', 'change: 0.2493344245941966', 'is_elite: False']\n", + "Id: 10_15 Identity: {'ancestor_count': 5, 'ancestor_ids': ['7_72', '8_60'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_15', 'origin': '7_72~CUW~8_60#MGNP'} Metrics: ['ELUC: -2.5121212422239605', 'NSGA-II_crowding_distance: 0.3979626238678927', 'NSGA-II_rank: 2', 'change: 0.05547713666627176', 'is_elite: False']\n", + "Id: 10_16 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_70', '9_92'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_16', 'origin': '9_70~CUW~9_92#MGNP'} Metrics: ['ELUC: -2.765006864348396', 'NSGA-II_crowding_distance: 0.2908773462364103', 'NSGA-II_rank: 1', 'change: 0.049449375274699475', 'is_elite: True']\n", + "Id: 10_93 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_93', 'origin': '7_67~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.999610892708218', 'NSGA-II_crowding_distance: 0.6113815277894027', 'NSGA-II_rank: 4', 'change: 0.1506527131411604', 'is_elite: False']\n", + "Id: 9_26 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_100', '8_55'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_26', 'origin': '7_100~CUW~8_55#MGNP'} Metrics: ['ELUC: -3.477165514872989', 'NSGA-II_crowding_distance: 0.301787352793018', 'NSGA-II_rank: 1', 'change: 0.09620096193689191', 'is_elite: True']\n", + "Id: 10_51 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_60', '9_60'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_51', 'origin': '8_60~CUW~9_60#MGNP'} Metrics: ['ELUC: -3.8073819945415357', 'NSGA-II_crowding_distance: 1.0983212814748236', 'NSGA-II_rank: 5', 'change: 0.1819833518292192', 'is_elite: False']\n", + "Id: 10_37 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '9_26'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_37', 'origin': '9_26~CUW~9_26#MGNP'} Metrics: ['ELUC: -3.8213081906881605', 'NSGA-II_crowding_distance: 0.6644586619574249', 'NSGA-II_rank: 2', 'change: 0.1084934227549718', 'is_elite: False']\n", + "Id: 10_17 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_56', '9_26'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_17', 'origin': '9_56~CUW~9_26#MGNP'} Metrics: ['ELUC: -4.14742744335686', 'NSGA-II_crowding_distance: 0.1727103692150571', 'NSGA-II_rank: 4', 'change: 0.15432243323003986', 'is_elite: False']\n", + "Id: 10_42 Identity: {'ancestor_count': 9, 'ancestor_ids': ['8_84', '9_26'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_42', 'origin': '8_84~CUW~9_26#MGNP'} Metrics: ['ELUC: -4.74713875715557', 'NSGA-II_crowding_distance: 0.22436082402996166', 'NSGA-II_rank: 1', 'change: 0.10585860677745258', 'is_elite: False']\n", + "Id: 10_58 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_58', 'origin': '7_67~CUW~9_80#MGNP'} Metrics: ['ELUC: -5.0013428271805775', 'NSGA-II_crowding_distance: 0.7631883279320323', 'NSGA-II_rank: 8', 'change: 0.27804652578324496', 'is_elite: False']\n", + "Id: 10_75 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '8_84'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_75', 'origin': '7_67~CUW~8_84#MGNP'} Metrics: ['ELUC: -5.190172371807828', 'NSGA-II_crowding_distance: 0.2426658602888368', 'NSGA-II_rank: 4', 'change: 0.1552982114659957', 'is_elite: False']\n", + "Id: 10_61 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '2_49'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_61', 'origin': '9_26~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.532942966360704', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3083098119026216', 'is_elite: False']\n", + "Id: 10_88 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_70', '9_92'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_88', 'origin': '9_70~CUW~9_92#MGNP'} Metrics: ['ELUC: -5.620483896424559', 'NSGA-II_crowding_distance: 0.15172516435257222', 'NSGA-II_rank: 1', 'change: 0.1267724583690216', 'is_elite: False']\n", + "Id: 10_40 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_80', '8_84'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_40', 'origin': '9_80~CUW~8_84#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.40452197149683305', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 10_59 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_70', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_59', 'origin': '9_70~CUW~9_56#MGNP'} Metrics: ['ELUC: -6.082934068157281', 'NSGA-II_crowding_distance: 0.8569258558874948', 'NSGA-II_rank: 3', 'change: 0.14531016990795928', 'is_elite: False']\n", + "Id: 10_53 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_42', '9_42'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_53', 'origin': '9_42~CUW~9_42#MGNP'} Metrics: ['ELUC: -6.110858876464323', 'NSGA-II_crowding_distance: 0.10233617320935343', 'NSGA-II_rank: 1', 'change: 0.12798726385045597', 'is_elite: False']\n", + "Id: 10_44 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_80', '9_26'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_44', 'origin': '9_80~CUW~9_26#MGNP'} Metrics: ['ELUC: -6.249723347815067', 'NSGA-II_crowding_distance: 0.09569591723651005', 'NSGA-II_rank: 7', 'change: 0.2715324495919018', 'is_elite: False']\n", + "Id: 10_47 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '7_67'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_47', 'origin': '1_1~CUW~7_67#MGNP'} Metrics: ['ELUC: -6.264320276898897', 'NSGA-II_crowding_distance: 0.3037636870098853', 'NSGA-II_rank: 4', 'change: 0.17178648694553397', 'is_elite: False']\n", + "Id: 10_38 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_70', '9_26'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_38', 'origin': '9_70~CUW~9_26#MGNP'} Metrics: ['ELUC: -6.504596051255548', 'NSGA-II_crowding_distance: 0.4151202763260546', 'NSGA-II_rank: 3', 'change: 0.15171121971144202', 'is_elite: False']\n", + "Id: 10_68 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_55', '9_70'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_68', 'origin': '8_55~CUW~9_70#MGNP'} Metrics: ['ELUC: -6.522364824225521', 'NSGA-II_crowding_distance: 0.4099139010878505', 'NSGA-II_rank: 2', 'change: 0.14208717274518137', 'is_elite: False']\n", + "Id: 10_24 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_80', '9_52'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_24', 'origin': '9_80~CUW~9_52#MGNP'} Metrics: ['ELUC: -6.639420275822511', 'NSGA-II_crowding_distance: 0.125374328318111', 'NSGA-II_rank: 7', 'change: 0.2717813661765353', 'is_elite: False']\n", + "Id: 10_99 Identity: {'ancestor_count': 5, 'ancestor_ids': ['9_80', '8_60'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_99', 'origin': '9_80~CUW~8_60#MGNP'} Metrics: ['ELUC: -6.862530226006514', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3033437461190532', 'is_elite: False']\n", + "Id: 10_84 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '9_42'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_84', 'origin': '1_1~CUW~9_42#MGNP'} Metrics: ['ELUC: -6.948312332026981', 'NSGA-II_crowding_distance: 0.18925213235446023', 'NSGA-II_rank: 2', 'change: 0.14968959683244404', 'is_elite: False']\n", + "Id: 10_63 Identity: {'ancestor_count': 5, 'ancestor_ids': ['9_80', '2_49'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_63', 'origin': '9_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.960951010148245', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.28705029288353645', 'is_elite: False']\n", + "Id: 10_41 Identity: {'ancestor_count': 9, 'ancestor_ids': ['8_55', '9_42'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_41', 'origin': '8_55~CUW~9_42#MGNP'} Metrics: ['ELUC: -7.058810887973038', 'NSGA-II_crowding_distance: 0.13899348559809216', 'NSGA-II_rank: 1', 'change: 0.1328984395361871', 'is_elite: False']\n", + "Id: 10_27 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '7_100'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_27', 'origin': '7_100~CUW~7_100#MGNP'} Metrics: ['ELUC: -7.10274554310801', 'NSGA-II_crowding_distance: 0.0909559933384092', 'NSGA-II_rank: 1', 'change: 0.15262719999540683', 'is_elite: False']\n", + "Id: 7_100 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_100', 'origin': '1_1~CUW~6_55#MGNP'} Metrics: ['ELUC: -7.224173299592141', 'NSGA-II_crowding_distance: 0.2724876496749776', 'NSGA-II_rank: 1', 'change: 0.1572314298524543', 'is_elite: True']\n", + "Id: 10_35 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_35', 'origin': '9_26~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.253319691834868', 'NSGA-II_crowding_distance: 0.8404279481212423', 'NSGA-II_rank: 6', 'change: 0.19110855029240292', 'is_elite: False']\n", + "Id: 10_22 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_56', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_22', 'origin': '9_56~CUW~9_80#MGNP'} Metrics: ['ELUC: -7.729567571431729', 'NSGA-II_crowding_distance: 0.2922358080528623', 'NSGA-II_rank: 7', 'change: 0.275055229778432', 'is_elite: False']\n", + "Id: 10_91 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '9_52'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_91', 'origin': '1_1~CUW~9_52#MGNP'} Metrics: ['ELUC: -7.982339173663734', 'NSGA-II_crowding_distance: 0.39286925147010704', 'NSGA-II_rank: 2', 'change: 0.16080200232100458', 'is_elite: False']\n", + "Id: 10_12 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '7_100'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_12', 'origin': '9_26~CUW~7_100#MGNP'} Metrics: ['ELUC: -8.251493260066034', 'NSGA-II_crowding_distance: 0.23334364335058363', 'NSGA-II_rank: 4', 'change: 0.17247652912832406', 'is_elite: False']\n", + "Id: 10_52 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_52', 'origin': '7_67~CUW~9_56#MGNP'} Metrics: ['ELUC: -8.273273112657463', 'NSGA-II_crowding_distance: 0.40620696318147975', 'NSGA-II_rank: 5', 'change: 0.18252950256029227', 'is_elite: False']\n", + "Id: 10_86 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_86', 'origin': '7_67~CUW~9_56#MGNP'} Metrics: ['ELUC: -8.41881416760354', 'NSGA-II_crowding_distance: 0.6984581010233166', 'NSGA-II_rank: 6', 'change: 0.21919866687260006', 'is_elite: False']\n", + "Id: 10_96 Identity: {'ancestor_count': 9, 'ancestor_ids': ['7_67', '9_26'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_96', 'origin': '7_67~CUW~9_26#MGNP'} Metrics: ['ELUC: -8.807592645503878', 'NSGA-II_crowding_distance: 0.5704374612295798', 'NSGA-II_rank: 5', 'change: 0.18633216039145306', 'is_elite: False']\n", + "Id: 10_60 Identity: {'ancestor_count': 7, 'ancestor_ids': ['9_80', '8_48'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_60', 'origin': '9_80~CUW~8_48#MGNP'} Metrics: ['ELUC: -9.144020721495721', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29102297755364376', 'is_elite: False']\n", + "Id: 10_55 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_55', 'origin': '9_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.538948220438373', 'NSGA-II_crowding_distance: 0.1873918515402141', 'NSGA-II_rank: 4', 'change: 0.1744774094434215', 'is_elite: False']\n", + "Id: 10_95 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '9_22'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_95', 'origin': '1_1~CUW~9_22#MGNP'} Metrics: ['ELUC: -9.86697051791418', 'NSGA-II_crowding_distance: 0.41513713079870596', 'NSGA-II_rank: 4', 'change: 0.18618155439632333', 'is_elite: False']\n", + "Id: 10_13 Identity: {'ancestor_count': 5, 'ancestor_ids': ['9_80', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_13', 'origin': '9_80~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.92004524285056', 'NSGA-II_crowding_distance: 0.4810569134166217', 'NSGA-II_rank: 6', 'change: 0.28712747919387055', 'is_elite: False']\n", + "Id: 10_81 Identity: {'ancestor_count': 6, 'ancestor_ids': ['8_60', '7_67'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_81', 'origin': '8_60~CUW~7_67#MGNP'} Metrics: ['ELUC: -9.940119157130171', 'NSGA-II_crowding_distance: 0.5460434627715047', 'NSGA-II_rank: 3', 'change: 0.1702434309258705', 'is_elite: False']\n", + "Id: 10_80 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '2_49'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_80', 'origin': '8_48~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.97907874146722', 'NSGA-II_crowding_distance: 0.028440692152305932', 'NSGA-II_rank: 6', 'change: 0.28906699141753756', 'is_elite: False']\n", + "Id: 10_57 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_57', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.021733128070313', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2911305487317096', 'is_elite: False']\n", + "Id: 10_30 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '9_70'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_30', 'origin': '7_67~CUW~9_70#MGNP'} Metrics: ['ELUC: -10.495746698273', 'NSGA-II_crowding_distance: 0.5549051303634261', 'NSGA-II_rank: 5', 'change: 0.24265670735117464', 'is_elite: False']\n", + "Id: 10_36 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '9_30'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_36', 'origin': '9_26~CUW~9_30#MGNP'} Metrics: ['ELUC: -10.892265773865534', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.24569207637780632', 'is_elite: False']\n", + "Id: 10_64 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '9_92'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_64', 'origin': '7_67~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.976544513669367', 'NSGA-II_crowding_distance: 0.3676318904922484', 'NSGA-II_rank: 3', 'change: 0.19567398563519123', 'is_elite: False']\n", + "Id: 10_85 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_56', '8_48'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_85', 'origin': '9_56~CUW~8_48#MGNP'} Metrics: ['ELUC: -10.989777907983823', 'NSGA-II_crowding_distance: 0.36180116812576374', 'NSGA-II_rank: 2', 'change: 0.16960389251652971', 'is_elite: False']\n", + "Id: 10_19 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_100', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_19', 'origin': '7_100~CUW~9_56#MGNP'} Metrics: ['ELUC: -11.098142237252654', 'NSGA-II_crowding_distance: 0.18312794120207554', 'NSGA-II_rank: 2', 'change: 0.19049634559045608', 'is_elite: False']\n", + "Id: 10_98 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_56', '9_42'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_98', 'origin': '9_56~CUW~9_42#MGNP'} Metrics: ['ELUC: -11.602042996088114', 'NSGA-II_crowding_distance: 0.5624192905271063', 'NSGA-II_rank: 4', 'change: 0.22209001791795135', 'is_elite: False']\n", + "Id: 9_92 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '8_60'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_92', 'origin': '8_21~CUW~8_60#MGNP'} Metrics: ['ELUC: -11.619260633154786', 'NSGA-II_crowding_distance: 0.3430439964692804', 'NSGA-II_rank: 1', 'change: 0.15728478917744898', 'is_elite: True']\n", + "Id: 10_28 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_100', '9_92'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_28', 'origin': '7_100~CUW~9_92#MGNP'} Metrics: ['ELUC: -11.749163670302911', 'NSGA-II_crowding_distance: 0.17394275821467814', 'NSGA-II_rank: 1', 'change: 0.1827976324007969', 'is_elite: False']\n", + "Id: 10_73 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_72', '7_67'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_73', 'origin': '7_72~CUW~7_67#MGNP'} Metrics: ['ELUC: -11.992560100152234', 'NSGA-II_crowding_distance: 0.20161421593929374', 'NSGA-II_rank: 3', 'change: 0.21762547486177444', 'is_elite: False']\n", + "Id: 10_54 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_72', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_54', 'origin': '7_72~CUW~9_56#MGNP'} Metrics: ['ELUC: -12.06127186464076', 'NSGA-II_crowding_distance: 0.20009285314478348', 'NSGA-II_rank: 2', 'change: 0.19410631232800632', 'is_elite: False']\n", + "Id: 10_87 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '9_92'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_87', 'origin': '7_67~CUW~9_92#MGNP'} Metrics: ['ELUC: -12.230445932756476', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.25559794470399483', 'is_elite: False']\n", + "Id: 10_14 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '9_52'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_14', 'origin': '7_67~CUW~9_52#MGNP'} Metrics: ['ELUC: -12.245439675403606', 'NSGA-II_crowding_distance: 0.12833517215587364', 'NSGA-II_rank: 3', 'change: 0.21899967609489737', 'is_elite: False']\n", + "Id: 10_48 Identity: {'ancestor_count': 6, 'ancestor_ids': ['9_70', '7_67'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_48', 'origin': '9_70~CUW~7_67#MGNP'} Metrics: ['ELUC: -12.54826222219031', 'NSGA-II_crowding_distance: 0.2878466146173374', 'NSGA-II_rank: 3', 'change: 0.2371492599983383', 'is_elite: False']\n", + "Id: 10_34 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_52', '8_84'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_34', 'origin': '9_52~CUW~8_84#MGNP'} Metrics: ['ELUC: -12.82782048249384', 'NSGA-II_crowding_distance: 0.11431619623909381', 'NSGA-II_rank: 1', 'change: 0.18867579872268114', 'is_elite: False']\n", + "Id: 10_56 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '8_48'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_56', 'origin': '8_48~CUW~8_48#MGNP'} Metrics: ['ELUC: -12.913254469369791', 'NSGA-II_crowding_distance: 0.2647237657364162', 'NSGA-II_rank: 2', 'change: 0.20519637771718835', 'is_elite: False']\n", + "Id: 10_39 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_39', 'origin': '1_1~CUW~9_80#MGNP'} Metrics: ['ELUC: -12.926250268926179', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2732852316186839', 'is_elite: False']\n", + "Id: 9_52 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_100', '8_48'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_52', 'origin': '7_100~CUW~8_48#MGNP'} Metrics: ['ELUC: -13.035800244164475', 'NSGA-II_crowding_distance: 0.09369965478480641', 'NSGA-II_rank: 1', 'change: 0.19507241859196478', 'is_elite: False']\n", + "Id: 10_74 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_48', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_74', 'origin': '8_48~CUW~9_56#MGNP'} Metrics: ['ELUC: -13.673994164176696', 'NSGA-II_crowding_distance: 0.07321682898698556', 'NSGA-II_rank: 1', 'change: 0.20227385941321735', 'is_elite: False']\n", + "Id: 10_26 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_52', '9_92'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_26', 'origin': '9_52~CUW~9_92#MGNP'} Metrics: ['ELUC: -13.855523700594372', 'NSGA-II_crowding_distance: 0.10557034497112218', 'NSGA-II_rank: 1', 'change: 0.20300772901070285', 'is_elite: False']\n", + "Id: 10_11 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_56', '9_70'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_11', 'origin': '9_56~CUW~9_70#MGNP'} Metrics: ['ELUC: -14.056136920184816', 'NSGA-II_crowding_distance: 0.24889037728253668', 'NSGA-II_rank: 2', 'change: 0.22117116879293652', 'is_elite: False']\n", + "Id: 10_20 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_42', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_20', 'origin': '9_42~CUW~9_56#MGNP'} Metrics: ['ELUC: -14.155035898986423', 'NSGA-II_crowding_distance: 0.2960854362772912', 'NSGA-II_rank: 2', 'change: 0.24251639687306578', 'is_elite: False']\n", + "Id: 10_76 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_48', '2_49'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_76', 'origin': '8_48~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.54585025412709', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2840698222162352', 'is_elite: False']\n", + "Id: 9_56 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '8_18'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_56', 'origin': '8_21~CUW~8_18#MGNP'} Metrics: ['ELUC: -14.642231008397209', 'NSGA-II_crowding_distance: 0.18295313876864436', 'NSGA-II_rank: 1', 'change: 0.2173424200253688', 'is_elite: False']\n", + "Id: 10_71 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_67', '8_48'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_71', 'origin': '7_67~CUW~8_48#MGNP'} Metrics: ['ELUC: -15.24456811588234', 'NSGA-II_crowding_distance: 0.32585841689606554', 'NSGA-II_rank: 1', 'change: 0.23402435660756468', 'is_elite: True']\n", + "Id: 7_67 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_67', 'origin': '5_86~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.720979465924962', 'NSGA-II_crowding_distance: 0.3134585112044146', 'NSGA-II_rank: 1', 'change: 0.27929430774028374', 'is_elite: True']\n", + "Id: 10_69 Identity: {'ancestor_count': 8, 'ancestor_ids': ['2_49', '9_56'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_69', 'origin': '2_49~CUW~9_56#MGNP'} Metrics: ['ELUC: -16.828022577072193', 'NSGA-II_crowding_distance: 0.12011406548892772', 'NSGA-II_rank: 1', 'change: 0.3006816805553014', 'is_elite: False']\n", + "Id: 10_45 Identity: {'ancestor_count': 5, 'ancestor_ids': ['9_80', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_45', 'origin': '9_80~CUW~9_80#MGNP'} Metrics: ['ELUC: -17.53681552686248', 'NSGA-II_crowding_distance: 0.05004927994094071', 'NSGA-II_rank: 1', 'change: 0.301288678696347', 'is_elite: False']\n", + "Id: 10_89 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_89', 'origin': '2_49~CUW~9_80#MGNP'} Metrics: ['ELUC: -17.576273633655095', 'NSGA-II_crowding_distance: 0.009249005953060087', 'NSGA-II_rank: 1', 'change: 0.30291721929295984', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 9_80 Identity: {'ancestor_count': 4, 'ancestor_ids': ['8_96', '7_72'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_80', 'origin': '8_96~CUW~7_72#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 10_77 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_77', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 10_94 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '2_49'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_94', 'origin': '9_26~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 10_100 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_100', 'origin': '9_26~CUW~9_80#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 10.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 11...:\n", + "PopulationResponse:\n", + " Generation: 11\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/11/20240219-205941\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 11 and asking ESP for generation 12...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 11 data persisted.\n", + "Evaluated candidates:\n", + "Id: 11_78 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_42', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_78', 'origin': '10_42~CUW~10_71#MGNP'} Metrics: ['ELUC: 7.96194858077036', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15239514025807324', 'is_elite: False']\n", + "Id: 11_99 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '9_56'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_99', 'origin': '1_1~CUW~9_56#MGNP'} Metrics: ['ELUC: 6.180187537333111', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.17769555923567376', 'is_elite: False']\n", + "Id: 11_36 Identity: {'ancestor_count': 10, 'ancestor_ids': ['9_56', '10_41'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_36', 'origin': '9_56~CUW~10_41#MGNP'} Metrics: ['ELUC: 5.254241087966304', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.16797205464988424', 'is_elite: False']\n", + "Id: 11_33 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '10_53'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_33', 'origin': '1_1~CUW~10_53#MGNP'} Metrics: ['ELUC: 4.26916798235384', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11603556372784674', 'is_elite: False']\n", + "Id: 11_67 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_67', 'origin': '10_16~CUW~10_71#MGNP'} Metrics: ['ELUC: 3.93075019513847', 'NSGA-II_crowding_distance: 0.8260879487424995', 'NSGA-II_rank: 7', 'change: 0.166076753691836', 'is_elite: False']\n", + "Id: 11_95 Identity: {'ancestor_count': 9, 'ancestor_ids': ['8_60', '10_28'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_95', 'origin': '8_60~CUW~10_28#MGNP'} Metrics: ['ELUC: 3.6732644559469816', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11937839505444532', 'is_elite: False']\n", + "Id: 11_20 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_100', '10_16'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_20', 'origin': '10_100~CUW~10_16#MGNP'} Metrics: ['ELUC: 3.523987793660636', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.25144931839097234', 'is_elite: False']\n", + "Id: 11_44 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_42', '10_69'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_44', 'origin': '10_42~CUW~10_69#MGNP'} Metrics: ['ELUC: 3.4302908395342846', 'NSGA-II_crowding_distance: 1.651967815563094', 'NSGA-II_rank: 9', 'change: 0.26687231780207105', 'is_elite: False']\n", + "Id: 11_19 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_69', '9_26'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_19', 'origin': '10_69~CUW~9_26#MGNP'} Metrics: ['ELUC: 2.734455002908796', 'NSGA-II_crowding_distance: 0.7344091358337281', 'NSGA-II_rank: 9', 'change: 0.3009468464645263', 'is_elite: False']\n", + "Id: 11_86 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '9_26'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_86', 'origin': '2_49~CUW~9_26#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 11_30 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_41', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_30', 'origin': '10_41~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.06083058610553', 'NSGA-II_crowding_distance: 0.7098730089601748', 'NSGA-II_rank: 6', 'change: 0.12294255446130985', 'is_elite: False']\n", + "Id: 11_93 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_28', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_93', 'origin': '10_28~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.677705305700536', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07024615463851168', 'is_elite: False']\n", + "Id: 11_97 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_97', 'origin': '7_67~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.4849514230353595', 'NSGA-II_crowding_distance: 1.093003702642705', 'NSGA-II_rank: 6', 'change: 0.16416888380982486', 'is_elite: False']\n", + "Id: 11_17 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_28', '8_60'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_17', 'origin': '10_28~CUW~8_60#MGNP'} Metrics: ['ELUC: 1.3259931181815041', 'NSGA-II_crowding_distance: 1.0552670434723368', 'NSGA-II_rank: 5', 'change: 0.11768860462102833', 'is_elite: False']\n", + "Id: 11_25 Identity: {'ancestor_count': 9, 'ancestor_ids': ['8_60', '10_16'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_25', 'origin': '8_60~CUW~10_16#MGNP'} Metrics: ['ELUC: 0.3141559926643893', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04465965281992899', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 11_27 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_27', 'origin': '9_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.26013855187574086', 'NSGA-II_crowding_distance: 0.6084639037448545', 'NSGA-II_rank: 4', 'change: 0.08270529908760892', 'is_elite: False']\n", + "Id: 11_81 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '10_53'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_81', 'origin': '1_1~CUW~10_53#MGNP'} Metrics: ['ELUC: -0.2782269211676359', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05394090964272852', 'is_elite: False']\n", + "Id: 11_62 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_34', '10_16'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_62', 'origin': '10_34~CUW~10_16#MGNP'} Metrics: ['ELUC: -0.39488806901866863', 'NSGA-II_crowding_distance: 0.7798675731526625', 'NSGA-II_rank: 7', 'change: 0.18416279828515067', 'is_elite: False']\n", + "Id: 11_57 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_100', '10_41'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_57', 'origin': '10_100~CUW~10_41#MGNP'} Metrics: ['ELUC: -0.6146452508033523', 'NSGA-II_crowding_distance: 1.0147058307238095', 'NSGA-II_rank: 7', 'change: 0.21713286819933583', 'is_elite: False']\n", + "Id: 11_75 Identity: {'ancestor_count': 5, 'ancestor_ids': ['8_60', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_75', 'origin': '8_60~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6559034925481594', 'NSGA-II_crowding_distance: 0.21288487880160673', 'NSGA-II_rank: 1', 'change: 0.03850922290125663', 'is_elite: True']\n", + "Id: 11_45 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '10_16'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_45', 'origin': '1_1~CUW~10_16#MGNP'} Metrics: ['ELUC: -1.2536896939843996', 'NSGA-II_crowding_distance: 0.6302035672191213', 'NSGA-II_rank: 3', 'change: 0.0834939998186168', 'is_elite: False']\n", + "Id: 11_22 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '10_16'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_22', 'origin': '10_16~CUW~10_16#MGNP'} Metrics: ['ELUC: -1.3999250163403016', 'NSGA-II_crowding_distance: 0.2515856695215691', 'NSGA-II_rank: 2', 'change: 0.04666024098539572', 'is_elite: False']\n", + "Id: 8_60 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '7_72'], 'birth_generation': 8, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '8_60', 'origin': '1_1~CUW~7_72#MGNP'} Metrics: ['ELUC: -1.715672688295017', 'NSGA-II_crowding_distance: 0.15662123643837447', 'NSGA-II_rank: 1', 'change: 0.039302720306517665', 'is_elite: False']\n", + "Id: 11_50 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_71', '9_26'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_50', 'origin': '10_71~CUW~9_26#MGNP'} Metrics: ['ELUC: -2.488179550811349', 'NSGA-II_crowding_distance: 0.7942451998805999', 'NSGA-II_rank: 4', 'change: 0.14394877791574912', 'is_elite: False']\n", + "Id: 11_40 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_42', '10_88'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_40', 'origin': '10_42~CUW~10_88#MGNP'} Metrics: ['ELUC: -2.714582208662379', 'NSGA-II_crowding_distance: 0.3301279157721702', 'NSGA-II_rank: 2', 'change: 0.06565050986523177', 'is_elite: False']\n", + "Id: 10_16 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_70', '9_92'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_16', 'origin': '9_70~CUW~9_92#MGNP'} Metrics: ['ELUC: -2.765006864348396', 'NSGA-II_crowding_distance: 0.2908773462364103', 'NSGA-II_rank: 1', 'change: 0.049449375274699475', 'is_elite: True']\n", + "Id: 11_32 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_42', '8_60'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_32', 'origin': '10_42~CUW~8_60#MGNP'} Metrics: ['ELUC: -3.021092235633168', 'NSGA-II_crowding_distance: 0.3769960822799836', 'NSGA-II_rank: 2', 'change: 0.10818440386292244', 'is_elite: False']\n", + "Id: 9_26 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_100', '8_55'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_26', 'origin': '7_100~CUW~8_55#MGNP'} Metrics: ['ELUC: -3.477165514872989', 'NSGA-II_crowding_distance: 0.24275301271323424', 'NSGA-II_rank: 1', 'change: 0.09620096193689191', 'is_elite: True']\n", + "Id: 11_83 Identity: {'ancestor_count': 10, 'ancestor_ids': ['7_67', '10_41'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_83', 'origin': '7_67~CUW~10_41#MGNP'} Metrics: ['ELUC: -3.588726882677538', 'NSGA-II_crowding_distance: 0.7530412619737398', 'NSGA-II_rank: 6', 'change: 0.1760592555197537', 'is_elite: False']\n", + "Id: 11_48 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_48', 'origin': '1_1~CUW~10_71#MGNP'} Metrics: ['ELUC: -3.8900551299813775', 'NSGA-II_crowding_distance: 0.18811764548860724', 'NSGA-II_rank: 1', 'change: 0.10278904859369649', 'is_elite: False']\n", + "Id: 11_41 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_88', '10_88'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_41', 'origin': '10_88~CUW~10_88#MGNP'} Metrics: ['ELUC: -4.94121073554712', 'NSGA-II_crowding_distance: 0.361583063683323', 'NSGA-II_rank: 2', 'change: 0.13048963489504428', 'is_elite: False']\n", + "Id: 11_87 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_88', '10_88'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_87', 'origin': '10_88~CUW~10_88#MGNP'} Metrics: ['ELUC: -4.98488170088947', 'NSGA-II_crowding_distance: 0.4785615890540376', 'NSGA-II_rank: 1', 'change: 0.12674466672463314', 'is_elite: True']\n", + "Id: 11_38 Identity: {'ancestor_count': 10, 'ancestor_ids': ['7_67', '10_42'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_38', 'origin': '7_67~CUW~10_42#MGNP'} Metrics: ['ELUC: -5.1031042074837885', 'NSGA-II_crowding_distance: 0.5361288288812778', 'NSGA-II_rank: 3', 'change: 0.13584292066535925', 'is_elite: False']\n", + "Id: 11_80 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_71', '9_26'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_80', 'origin': '10_71~CUW~9_26#MGNP'} Metrics: ['ELUC: -5.1132289978006655', 'NSGA-II_crowding_distance: 0.4655293332744369', 'NSGA-II_rank: 6', 'change: 0.1819579687467231', 'is_elite: False']\n", + "Id: 11_16 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_88', '10_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_16', 'origin': '10_88~CUW~10_100#MGNP'} Metrics: ['ELUC: -5.435016453677767', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26052412131263075', 'is_elite: False']\n", + "Id: 11_56 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_16', '10_42'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_56', 'origin': '10_16~CUW~10_42#MGNP'} Metrics: ['ELUC: -5.947992295340382', 'NSGA-II_crowding_distance: 0.2042669981381311', 'NSGA-II_rank: 3', 'change: 0.1442368383601264', 'is_elite: False']\n", + "Id: 11_71 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_100', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_71', 'origin': '10_100~CUW~10_71#MGNP'} Metrics: ['ELUC: -6.92550786862993', 'NSGA-II_crowding_distance: 0.8377157774575072', 'NSGA-II_rank: 7', 'change: 0.24670943916553595', 'is_elite: False']\n", + "Id: 7_100 Identity: {'ancestor_count': 6, 'ancestor_ids': ['1_1', '6_55'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_100', 'origin': '1_1~CUW~6_55#MGNP'} Metrics: ['ELUC: -7.224173299592141', 'NSGA-II_crowding_distance: 0.6003426678328151', 'NSGA-II_rank: 4', 'change: 0.1572314298524543', 'is_elite: False']\n", + "Id: 11_91 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_91', 'origin': '9_26~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.432489113728403', 'NSGA-II_crowding_distance: 0.5370857290660855', 'NSGA-II_rank: 6', 'change: 0.1886913510367272', 'is_elite: False']\n", + "Id: 11_63 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_63', 'origin': '7_67~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.544623789236691', 'NSGA-II_crowding_distance: 0.3502807574095745', 'NSGA-II_rank: 3', 'change: 0.1490940008408137', 'is_elite: False']\n", + "Id: 11_59 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_16', '10_41'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_59', 'origin': '10_16~CUW~10_41#MGNP'} Metrics: ['ELUC: -7.608263311501791', 'NSGA-II_crowding_distance: 0.43080522968464247', 'NSGA-II_rank: 2', 'change: 0.13497056206158872', 'is_elite: False']\n", + "Id: 11_42 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_100', '7_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_42', 'origin': '10_100~CUW~7_100#MGNP'} Metrics: ['ELUC: -7.691504877201848', 'NSGA-II_crowding_distance: 0.9195029095716256', 'NSGA-II_rank: 5', 'change: 0.1757606720505539', 'is_elite: False']\n", + "Id: 11_12 Identity: {'ancestor_count': 10, 'ancestor_ids': ['9_92', '10_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_12', 'origin': '9_92~CUW~10_100#MGNP'} Metrics: ['ELUC: -8.258404697591711', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.25458100875632866', 'is_elite: False']\n", + "Id: 11_52 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_52', 'origin': '1_1~CUW~10_71#MGNP'} Metrics: ['ELUC: -8.487603993521363', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.20390056721208893', 'is_elite: False']\n", + "Id: 11_58 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_58', 'origin': '9_26~CUW~9_92#MGNP'} Metrics: ['ELUC: -8.65580220929681', 'NSGA-II_crowding_distance: 0.22979897993534837', 'NSGA-II_rank: 5', 'change: 0.1757683261863231', 'is_elite: False']\n", + "Id: 11_92 Identity: {'ancestor_count': 8, 'ancestor_ids': ['8_60', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_92', 'origin': '8_60~CUW~10_71#MGNP'} Metrics: ['ELUC: -9.26987330310003', 'NSGA-II_crowding_distance: 0.38609621306015374', 'NSGA-II_rank: 5', 'change: 0.20284754937801933', 'is_elite: False']\n", + "Id: 11_100 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_34', '7_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_100', 'origin': '10_34~CUW~7_100#MGNP'} Metrics: ['ELUC: -9.55467021010489', 'NSGA-II_crowding_distance: 0.3229691767214864', 'NSGA-II_rank: 4', 'change: 0.1746737604478638', 'is_elite: False']\n", + "Id: 11_13 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '10_41'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_13', 'origin': '1_1~CUW~10_41#MGNP'} Metrics: ['ELUC: -9.829811429357427', 'NSGA-II_crowding_distance: 0.2148451815887259', 'NSGA-II_rank: 4', 'change: 0.1907496351392428', 'is_elite: False']\n", + "Id: 11_65 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_28', '7_67'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_65', 'origin': '10_28~CUW~7_67#MGNP'} Metrics: ['ELUC: -9.83178912282512', 'NSGA-II_crowding_distance: 0.2513837116154354', 'NSGA-II_rank: 5', 'change: 0.24152911767170485', 'is_elite: False']\n", + "Id: 11_28 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_42', '10_28'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_28', 'origin': '10_42~CUW~10_28#MGNP'} Metrics: ['ELUC: -9.883662272621605', 'NSGA-II_crowding_distance: 0.23517037772263755', 'NSGA-II_rank: 3', 'change: 0.17076392681644145', 'is_elite: False']\n", + "Id: 11_43 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_28', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_43', 'origin': '10_28~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.904144994467423', 'NSGA-II_crowding_distance: 0.07238530566986348', 'NSGA-II_rank: 3', 'change: 0.17118786837593664', 'is_elite: False']\n", + "Id: 11_61 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '10_28'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_61', 'origin': '10_16~CUW~10_28#MGNP'} Metrics: ['ELUC: -9.946052826088073', 'NSGA-II_crowding_distance: 0.2747184107168812', 'NSGA-II_rank: 2', 'change: 0.1690537467471428', 'is_elite: False']\n", + "Id: 11_94 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_100', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_94', 'origin': '7_100~CUW~10_71#MGNP'} Metrics: ['ELUC: -10.03169232304963', 'NSGA-II_crowding_distance: 0.10521767092959938', 'NSGA-II_rank: 3', 'change: 0.1863242328510754', 'is_elite: False']\n", + "Id: 11_89 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '7_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_89', 'origin': '9_92~CUW~7_100#MGNP'} Metrics: ['ELUC: -10.092182449516114', 'NSGA-II_crowding_distance: 0.3001108434529616', 'NSGA-II_rank: 4', 'change: 0.21395754349182824', 'is_elite: False']\n", + "Id: 11_90 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_28', '8_60'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_90', 'origin': '10_28~CUW~8_60#MGNP'} Metrics: ['ELUC: -10.11788509166382', 'NSGA-II_crowding_distance: 0.05260168322613763', 'NSGA-II_rank: 2', 'change: 0.16940929548122396', 'is_elite: False']\n", + "Id: 11_68 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '7_67'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_68', 'origin': '9_26~CUW~7_67#MGNP'} Metrics: ['ELUC: -10.219834755307291', 'NSGA-II_crowding_distance: 0.49622344890313314', 'NSGA-II_rank: 5', 'change: 0.24313520211623996', 'is_elite: False']\n", + "Id: 11_18 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_18', 'origin': '9_92~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.503893423212768', 'NSGA-II_crowding_distance: 0.4796858831647155', 'NSGA-II_rank: 1', 'change: 0.13334228771385556', 'is_elite: True']\n", + "Id: 11_34 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_34', 'origin': '9_26~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.551866856899439', 'NSGA-II_crowding_distance: 0.29230793264082566', 'NSGA-II_rank: 3', 'change: 0.18725312973009192', 'is_elite: False']\n", + "Id: 11_85 Identity: {'ancestor_count': 9, 'ancestor_ids': ['8_60', '10_28'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_85', 'origin': '8_60~CUW~10_28#MGNP'} Metrics: ['ELUC: -10.606790246566304', 'NSGA-II_crowding_distance: 0.2509806590471289', 'NSGA-II_rank: 2', 'change: 0.17304560016234175', 'is_elite: False']\n", + "Id: 11_14 Identity: {'ancestor_count': 10, 'ancestor_ids': ['2_49', '10_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_14', 'origin': '2_49~CUW~10_100#MGNP'} Metrics: ['ELUC: -11.18996105894475', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.32814969859074683', 'is_elite: False']\n", + "Id: 11_53 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_71', '10_26'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_53', 'origin': '10_71~CUW~10_26#MGNP'} Metrics: ['ELUC: -11.251421026953567', 'NSGA-II_crowding_distance: 0.3313942774193055', 'NSGA-II_rank: 4', 'change: 0.23609540467095053', 'is_elite: False']\n", + "Id: 9_92 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '8_60'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_92', 'origin': '8_21~CUW~8_60#MGNP'} Metrics: ['ELUC: -11.619260633154786', 'NSGA-II_crowding_distance: 0.26164242710912383', 'NSGA-II_rank: 1', 'change: 0.15728478917744898', 'is_elite: True']\n", + "Id: 11_15 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_100', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_15', 'origin': '10_100~CUW~10_71#MGNP'} Metrics: ['ELUC: -12.435569800177568', 'NSGA-II_crowding_distance: 0.39957357716493985', 'NSGA-II_rank: 4', 'change: 0.25304103807326267', 'is_elite: False']\n", + "Id: 11_72 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '7_67'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_72', 'origin': '9_92~CUW~7_67#MGNP'} Metrics: ['ELUC: -12.447999605194571', 'NSGA-II_crowding_distance: 0.42076701087438156', 'NSGA-II_rank: 3', 'change: 0.22161057548402036', 'is_elite: False']\n", + "Id: 11_64 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '7_67'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_64', 'origin': '10_16~CUW~7_67#MGNP'} Metrics: ['ELUC: -12.48105821454338', 'NSGA-II_crowding_distance: 0.25869742972734533', 'NSGA-II_rank: 2', 'change: 0.19985562253351505', 'is_elite: False']\n", + "Id: 11_39 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_39', 'origin': '9_92~CUW~9_92#MGNP'} Metrics: ['ELUC: -12.75204010873119', 'NSGA-II_crowding_distance: 0.21642152383105084', 'NSGA-II_rank: 1', 'change: 0.1732588150378695', 'is_elite: True']\n", + "Id: 11_49 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_71', '10_28'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_49', 'origin': '10_71~CUW~10_28#MGNP'} Metrics: ['ELUC: -12.942455921369035', 'NSGA-II_crowding_distance: 0.07715512957486098', 'NSGA-II_rank: 2', 'change: 0.205874506626463', 'is_elite: False']\n", + "Id: 11_24 Identity: {'ancestor_count': 8, 'ancestor_ids': ['10_71', '7_67'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_24', 'origin': '10_71~CUW~7_67#MGNP'} Metrics: ['ELUC: -13.328048477441573', 'NSGA-II_crowding_distance: 0.23862737488276464', 'NSGA-II_rank: 2', 'change: 0.20747494842121425', 'is_elite: False']\n", + "Id: 11_76 Identity: {'ancestor_count': 9, 'ancestor_ids': ['7_67', '10_34'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_76', 'origin': '7_67~CUW~10_34#MGNP'} Metrics: ['ELUC: -13.379645640494262', 'NSGA-II_crowding_distance: 0.25130891988041865', 'NSGA-II_rank: 3', 'change: 0.24789991528639602', 'is_elite: False']\n", + "Id: 11_46 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_46', 'origin': '10_16~CUW~10_71#MGNP'} Metrics: ['ELUC: -13.559481785987195', 'NSGA-II_crowding_distance: 0.16228812005753557', 'NSGA-II_rank: 1', 'change: 0.18893399792190652', 'is_elite: False']\n", + "Id: 11_84 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_100', '10_41'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_84', 'origin': '10_100~CUW~10_41#MGNP'} Metrics: ['ELUC: -13.57154351617246', 'NSGA-II_crowding_distance: 0.16723960382151706', 'NSGA-II_rank: 3', 'change: 0.26639796844641134', 'is_elite: False']\n", + "Id: 11_37 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_69', '7_67'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_37', 'origin': '10_69~CUW~7_67#MGNP'} Metrics: ['ELUC: -13.695863852954082', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2886328226830111', 'is_elite: False']\n", + "Id: 11_77 Identity: {'ancestor_count': 9, 'ancestor_ids': ['7_67', '9_26'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_77', 'origin': '7_67~CUW~9_26#MGNP'} Metrics: ['ELUC: -13.826257956886984', 'NSGA-II_crowding_distance: 0.11603530314120969', 'NSGA-II_rank: 1', 'change: 0.20345216544789577', 'is_elite: False']\n", + "Id: 11_70 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_70', 'origin': '9_92~CUW~10_71#MGNP'} Metrics: ['ELUC: -14.129461633512014', 'NSGA-II_crowding_distance: 0.09862724960575084', 'NSGA-II_rank: 1', 'change: 0.2138836127977794', 'is_elite: False']\n", + "Id: 11_51 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_51', 'origin': '7_67~CUW~9_92#MGNP'} Metrics: ['ELUC: -14.246142171205527', 'NSGA-II_crowding_distance: 0.12737696110238375', 'NSGA-II_rank: 1', 'change: 0.22575477424833684', 'is_elite: False']\n", + "Id: 11_69 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '2_49'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_69', 'origin': '9_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.290656222210195', 'NSGA-II_crowding_distance: 0.1509685274726857', 'NSGA-II_rank: 3', 'change: 0.2752305532617339', 'is_elite: False']\n", + "Id: 11_96 Identity: {'ancestor_count': 10, 'ancestor_ids': ['2_49', '10_42'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_96', 'origin': '2_49~CUW~10_42#MGNP'} Metrics: ['ELUC: -14.672138617240371', 'NSGA-II_crowding_distance: 0.2371347712946122', 'NSGA-II_rank: 3', 'change: 0.2868547090899461', 'is_elite: False']\n", + "Id: 10_71 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_67', '8_48'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_71', 'origin': '7_67~CUW~8_48#MGNP'} Metrics: ['ELUC: -15.24456811588234', 'NSGA-II_crowding_distance: 0.5341420473057011', 'NSGA-II_rank: 2', 'change: 0.23402435660756468', 'is_elite: False']\n", + "Id: 11_29 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_67', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_29', 'origin': '7_67~CUW~10_71#MGNP'} Metrics: ['ELUC: -15.246736472941514', 'NSGA-II_crowding_distance: 0.18527438931621082', 'NSGA-II_rank: 1', 'change: 0.23292956098196788', 'is_elite: False']\n", + "Id: 11_82 Identity: {'ancestor_count': 7, 'ancestor_ids': ['7_67', '7_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_82', 'origin': '7_67~CUW~7_100#MGNP'} Metrics: ['ELUC: -15.555678423899705', 'NSGA-II_crowding_distance: 0.19676888359740993', 'NSGA-II_rank: 1', 'change: 0.2588132892991434', 'is_elite: False']\n", + "Id: 11_74 Identity: {'ancestor_count': 10, 'ancestor_ids': ['7_100', '10_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_74', 'origin': '7_100~CUW~10_100#MGNP'} Metrics: ['ELUC: -16.159208429717523', 'NSGA-II_crowding_distance: 0.1277552063845971', 'NSGA-II_rank: 1', 'change: 0.2761560804284469', 'is_elite: False']\n", + "Id: 11_73 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_88', '10_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_73', 'origin': '10_88~CUW~10_100#MGNP'} Metrics: ['ELUC: -16.512924255207945', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2998868588609391', 'is_elite: False']\n", + "Id: 11_54 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '2_49'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_54', 'origin': '7_67~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.602948132618064', 'NSGA-II_crowding_distance: 0.3906865306775573', 'NSGA-II_rank: 2', 'change: 0.29760668951780883', 'is_elite: False']\n", + "Id: 11_60 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_100', '10_71'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_60', 'origin': '7_100~CUW~10_71#MGNP'} Metrics: ['ELUC: -16.628590131713125', 'NSGA-II_crowding_distance: 0.042468503194618076', 'NSGA-II_rank: 1', 'change: 0.27872495346092624', 'is_elite: False']\n", + "Id: 7_67 Identity: {'ancestor_count': 5, 'ancestor_ids': ['5_86', '1_1'], 'birth_generation': 7, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '7_67', 'origin': '5_86~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.720979465924962', 'NSGA-II_crowding_distance: 0.0350197170634841', 'NSGA-II_rank: 1', 'change: 0.27929430774028374', 'is_elite: False']\n", + "Id: 11_31 Identity: {'ancestor_count': 6, 'ancestor_ids': ['7_67', '7_67'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_31', 'origin': '7_67~CUW~7_67#MGNP'} Metrics: ['ELUC: -16.921986355846627', 'NSGA-II_crowding_distance: 0.12045803215646629', 'NSGA-II_rank: 1', 'change: 0.2841950322574842', 'is_elite: False']\n", + "Id: 11_35 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_42', '2_49'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_35', 'origin': '10_42~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.502213567581897', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3019378338350691', 'is_elite: False']\n", + "Id: 11_11 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_71', '10_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_11', 'origin': '10_71~CUW~10_100#MGNP'} Metrics: ['ELUC: -17.53897485493258', 'NSGA-II_crowding_distance: 0.10150618742334597', 'NSGA-II_rank: 1', 'change: 0.30135466622164253', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 10_100 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '9_80'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_100', 'origin': '9_26~CUW~9_80#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_21 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_21', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_23 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_23', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_26 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_26', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_47 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '8_60'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_47', 'origin': '2_49~CUW~8_60#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_55 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_55', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_66 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_66', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_79 Identity: {'ancestor_count': 10, 'ancestor_ids': ['2_49', '10_100'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_79', 'origin': '2_49~CUW~10_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_88 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_28', '2_49'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_88', 'origin': '10_28~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 11_98 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_98', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 11.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 12...:\n", + "PopulationResponse:\n", + " Generation: 12\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/12/20240219-210701\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 12 and asking ESP for generation 13...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 12 data persisted.\n", + "Evaluated candidates:\n", + "Id: 12_58 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_58', 'origin': '2_49~CUW~10_16#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 12_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_54', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 6.988287488687617', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24385470530689302', 'is_elite: False']\n", + "Id: 12_94 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '11_98'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_94', 'origin': '2_49~CUW~11_98#MGNP'} Metrics: ['ELUC: 2.9777168477984306', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.26208608172689246', 'is_elite: False']\n", + "Id: 12_46 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '1_1'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_46', 'origin': '11_39~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.0362557698519925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.10555131723413258', 'is_elite: False']\n", + "Id: 12_43 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '9_26'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_43', 'origin': '10_16~CUW~9_26#MGNP'} Metrics: ['ELUC: 1.9233059476411483', 'NSGA-II_crowding_distance: 1.0740407314894629', 'NSGA-II_rank: 7', 'change: 0.11896205888551602', 'is_elite: False']\n", + "Id: 12_68 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '1_1'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_68', 'origin': '9_26~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.2744343018248536', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08240445460120221', 'is_elite: False']\n", + "Id: 12_45 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_98', '11_75'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_45', 'origin': '11_98~CUW~11_75#MGNP'} Metrics: ['ELUC: 1.1410006224971336', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.24041761557328828', 'is_elite: False']\n", + "Id: 12_75 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_98', '11_48'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_75', 'origin': '11_98~CUW~11_48#MGNP'} Metrics: ['ELUC: 0.8281648151571256', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27431544221112614', 'is_elite: False']\n", + "Id: 12_24 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_92', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_24', 'origin': '9_92~CUW~10_16#MGNP'} Metrics: ['ELUC: 0.2811628465391135', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06758191643810098', 'is_elite: False']\n", + "Id: 12_18 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '8_60'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_18', 'origin': '1_1~CUW~8_60#MGNP'} Metrics: ['ELUC: 0.18249742123695253', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.048757422732428814', 'is_elite: False']\n", + "Id: 12_27 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '11_75'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_27', 'origin': '11_75~CUW~11_75#MGNP'} Metrics: ['ELUC: 0.015174621610778486', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.044172631449512334', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 12_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_82', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.019039538076993042', 'NSGA-II_crowding_distance: 0.6839005321810534', 'NSGA-II_rank: 9', 'change: 0.24967821010073035', 'is_elite: False']\n", + "Id: 12_41 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '9_26'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_41', 'origin': '11_39~CUW~9_26#MGNP'} Metrics: ['ELUC: -0.028285992806234193', 'NSGA-II_crowding_distance: 0.959999200296563', 'NSGA-II_rank: 5', 'change: 0.13355757937132287', 'is_elite: False']\n", + "Id: 12_70 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '11_82'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_70', 'origin': '10_16~CUW~11_82#MGNP'} Metrics: ['ELUC: -0.20563467540554034', 'NSGA-II_crowding_distance: 0.9174950924273169', 'NSGA-II_rank: 4', 'change: 0.1213985417217111', 'is_elite: False']\n", + "Id: 12_50 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '11_75'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_50', 'origin': '11_75~CUW~11_75#MGNP'} Metrics: ['ELUC: -0.2986711928799929', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03521296477391404', 'is_elite: False']\n", + "Id: 11_75 Identity: {'ancestor_count': 5, 'ancestor_ids': ['8_60', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_75', 'origin': '8_60~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6559034925481594', 'NSGA-II_crowding_distance: 0.18369499995323674', 'NSGA-II_rank: 2', 'change: 0.03850922290125663', 'is_elite: False']\n", + "Id: 12_14 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '8_60'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_14', 'origin': '11_39~CUW~8_60#MGNP'} Metrics: ['ELUC: -1.0692238013457218', 'NSGA-II_crowding_distance: 0.3230523857567397', 'NSGA-II_rank: 3', 'change: 0.06287599473883493', 'is_elite: False']\n", + "Id: 12_23 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '1_1'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_23', 'origin': '11_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2534769974134168', 'NSGA-II_crowding_distance: 0.25368249914420893', 'NSGA-II_rank: 1', 'change: 0.03000838202835237', 'is_elite: True']\n", + "Id: 12_22 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_22', 'origin': '9_26~CUW~10_16#MGNP'} Metrics: ['ELUC: -1.7018575609246833', 'NSGA-II_crowding_distance: 0.37769957941570753', 'NSGA-II_rank: 3', 'change: 0.0968330023843474', 'is_elite: False']\n", + "Id: 12_73 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '11_98'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_73', 'origin': '11_75~CUW~11_98#MGNP'} Metrics: ['ELUC: -1.7956633559000816', 'NSGA-II_crowding_distance: 1.0266152720779493', 'NSGA-II_rank: 9', 'change: 0.2532232845604283', 'is_elite: False']\n", + "Id: 12_80 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '11_75'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_80', 'origin': '11_18~CUW~11_75#MGNP'} Metrics: ['ELUC: -2.038013866173018', 'NSGA-II_crowding_distance: 0.15112429220095863', 'NSGA-II_rank: 1', 'change: 0.0460055918924179', 'is_elite: False']\n", + "Id: 12_99 Identity: {'ancestor_count': 6, 'ancestor_ids': ['8_60', '11_75'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_99', 'origin': '8_60~CUW~11_75#MGNP'} Metrics: ['ELUC: -2.3472588561083456', 'NSGA-II_crowding_distance: 0.39834424655826306', 'NSGA-II_rank: 2', 'change: 0.04945595479052211', 'is_elite: False']\n", + "Id: 12_81 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_81', 'origin': '2_49~CUW~10_16#MGNP'} Metrics: ['ELUC: -2.390550358081646', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.29220654894405873', 'is_elite: False']\n", + "Id: 10_16 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_70', '9_92'], 'birth_generation': 10, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '10_16', 'origin': '9_70~CUW~9_92#MGNP'} Metrics: ['ELUC: -2.765006864348396', 'NSGA-II_crowding_distance: 0.102067447505124', 'NSGA-II_rank: 1', 'change: 0.049449375274699475', 'is_elite: False']\n", + "Id: 12_56 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_56', 'origin': '10_16~CUW~10_16#MGNP'} Metrics: ['ELUC: -3.095654633905682', 'NSGA-II_crowding_distance: 0.09479537332853326', 'NSGA-II_rank: 1', 'change: 0.058511753831567516', 'is_elite: False']\n", + "Id: 12_100 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_18', '11_87'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_100', 'origin': '11_18~CUW~11_87#MGNP'} Metrics: ['ELUC: -3.174469626985349', 'NSGA-II_crowding_distance: 0.2843370706255806', 'NSGA-II_rank: 3', 'change: 0.12287893779960203', 'is_elite: False']\n", + "Id: 9_26 Identity: {'ancestor_count': 8, 'ancestor_ids': ['7_100', '8_55'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_26', 'origin': '7_100~CUW~8_55#MGNP'} Metrics: ['ELUC: -3.477165514872989', 'NSGA-II_crowding_distance: 0.4093213666857728', 'NSGA-II_rank: 2', 'change: 0.09620096193689191', 'is_elite: False']\n", + "Id: 12_29 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_46', '11_98'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_29', 'origin': '11_46~CUW~11_98#MGNP'} Metrics: ['ELUC: -3.6943542209254407', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27112529987928474', 'is_elite: False']\n", + "Id: 12_59 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_16', '11_87'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_59', 'origin': '10_16~CUW~11_87#MGNP'} Metrics: ['ELUC: -3.8281116367515367', 'NSGA-II_crowding_distance: 0.09140490399280447', 'NSGA-II_rank: 1', 'change: 0.059692986499200115', 'is_elite: False']\n", + "Id: 12_87 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '8_60'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_87', 'origin': '11_75~CUW~8_60#MGNP'} Metrics: ['ELUC: -4.1648722420466315', 'NSGA-II_crowding_distance: 0.24226212987958523', 'NSGA-II_rank: 1', 'change: 0.0676399878587724', 'is_elite: True']\n", + "Id: 12_62 Identity: {'ancestor_count': 10, 'ancestor_ids': ['8_60', '11_77'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_62', 'origin': '8_60~CUW~11_77#MGNP'} Metrics: ['ELUC: -4.2139722838263065', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.16665369634222588', 'is_elite: False']\n", + "Id: 12_84 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '11_87'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_84', 'origin': '1_1~CUW~11_87#MGNP'} Metrics: ['ELUC: -4.247058376777787', 'NSGA-II_crowding_distance: 0.2529268157958765', 'NSGA-II_rank: 3', 'change: 0.12662665709609155', 'is_elite: False']\n", + "Id: 12_69 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '9_26'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_69', 'origin': '9_26~CUW~9_26#MGNP'} Metrics: ['ELUC: -4.700481500901059', 'NSGA-II_crowding_distance: 0.21178253859798668', 'NSGA-II_rank: 2', 'change: 0.11776221025139759', 'is_elite: False']\n", + "Id: 11_87 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_88', '10_88'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_87', 'origin': '10_88~CUW~10_88#MGNP'} Metrics: ['ELUC: -4.98488170088947', 'NSGA-II_crowding_distance: 0.3112314526319007', 'NSGA-II_rank: 2', 'change: 0.12674466672463314', 'is_elite: False']\n", + "Id: 12_13 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_29', '1_1'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_13', 'origin': '11_29~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.0456323416190125', 'NSGA-II_crowding_distance: 1.143170027771818', 'NSGA-II_rank: 7', 'change: 0.15981334548020995', 'is_elite: False']\n", + "Id: 12_71 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_71', 'origin': '9_26~CUW~10_16#MGNP'} Metrics: ['ELUC: -5.246721707814474', 'NSGA-II_crowding_distance: 0.5807318523978142', 'NSGA-II_rank: 1', 'change: 0.10790435701581459', 'is_elite: True']\n", + "Id: 12_85 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '11_82'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_85', 'origin': '9_92~CUW~11_82#MGNP'} Metrics: ['ELUC: -5.423761239517365', 'NSGA-II_crowding_distance: 0.6728275552049938', 'NSGA-II_rank: 7', 'change: 0.17912057318727004', 'is_elite: False']\n", + "Id: 12_19 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '11_31'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_19', 'origin': '10_16~CUW~11_31#MGNP'} Metrics: ['ELUC: -5.511596972987612', 'NSGA-II_crowding_distance: 1.461954338489718', 'NSGA-II_rank: 6', 'change: 0.15488978732689454', 'is_elite: False']\n", + "Id: 12_39 Identity: {'ancestor_count': 8, 'ancestor_ids': ['11_98', '9_92'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_39', 'origin': '11_98~CUW~9_92#MGNP'} Metrics: ['ELUC: -5.994298795186907', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2227744656158308', 'is_elite: False']\n", + "Id: 12_86 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_87', '11_51'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_86', 'origin': '11_87~CUW~11_51#MGNP'} Metrics: ['ELUC: -6.062942277131508', 'NSGA-II_crowding_distance: 1.024637670746638', 'NSGA-II_rank: 5', 'change: 0.15094250761644107', 'is_elite: False']\n", + "Id: 12_21 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_48', '11_29'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_21', 'origin': '11_48~CUW~11_29#MGNP'} Metrics: ['ELUC: -6.09932529374041', 'NSGA-II_crowding_distance: 0.6688058641285499', 'NSGA-II_rank: 4', 'change: 0.15053935879809702', 'is_elite: False']\n", + "Id: 12_60 Identity: {'ancestor_count': 10, 'ancestor_ids': ['10_16', '11_87'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_60', 'origin': '10_16~CUW~11_87#MGNP'} Metrics: ['ELUC: -6.220365851783487', 'NSGA-II_crowding_distance: 0.2087997605224603', 'NSGA-II_rank: 3', 'change: 0.1368619669013857', 'is_elite: False']\n", + "Id: 12_78 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_48', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_78', 'origin': '11_48~CUW~10_16#MGNP'} Metrics: ['ELUC: -6.299003165856269', 'NSGA-II_crowding_distance: 0.18473818561886163', 'NSGA-II_rank: 3', 'change: 0.1455765674950702', 'is_elite: False']\n", + "Id: 12_33 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_77', '11_48'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_33', 'origin': '11_77~CUW~11_48#MGNP'} Metrics: ['ELUC: -7.059868102955317', 'NSGA-II_crowding_distance: 0.25756767604353126', 'NSGA-II_rank: 4', 'change: 0.15609153315915925', 'is_elite: False']\n", + "Id: 12_28 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '11_98'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_28', 'origin': '10_16~CUW~11_98#MGNP'} Metrics: ['ELUC: -7.373455678091558', 'NSGA-II_crowding_distance: 1.3160994678189466', 'NSGA-II_rank: 9', 'change: 0.25702678680062835', 'is_elite: False']\n", + "Id: 12_65 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '11_18'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_65', 'origin': '2_49~CUW~11_18#MGNP'} Metrics: ['ELUC: -7.798749114704099', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27644877268416307', 'is_elite: False']\n", + "Id: 12_16 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '11_82'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_16', 'origin': '10_16~CUW~11_82#MGNP'} Metrics: ['ELUC: -7.848273260093643', 'NSGA-II_crowding_distance: 0.7458464114834467', 'NSGA-II_rank: 7', 'change: 0.2144077057167314', 'is_elite: False']\n", + "Id: 12_49 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_82', '11_18'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_49', 'origin': '11_82~CUW~11_18#MGNP'} Metrics: ['ELUC: -8.314942269006114', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24233802620332745', 'is_elite: False']\n", + "Id: 12_31 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_51', '11_48'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_31', 'origin': '11_51~CUW~11_48#MGNP'} Metrics: ['ELUC: -8.369874350684398', 'NSGA-II_crowding_distance: 0.2959078970174156', 'NSGA-II_rank: 3', 'change: 0.1482796309917395', 'is_elite: False']\n", + "Id: 12_83 Identity: {'ancestor_count': 8, 'ancestor_ids': ['11_82', '8_60'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_83', 'origin': '11_82~CUW~8_60#MGNP'} Metrics: ['ELUC: -8.56382714784554', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23922029883034301', 'is_elite: False']\n", + "Id: 12_66 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '11_48'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_66', 'origin': '9_26~CUW~11_48#MGNP'} Metrics: ['ELUC: -8.641171061832598', 'NSGA-II_crowding_distance: 0.4879303917599601', 'NSGA-II_rank: 2', 'change: 0.13412557824962892', 'is_elite: False']\n", + "Id: 12_47 Identity: {'ancestor_count': 8, 'ancestor_ids': ['11_82', '9_92'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_47', 'origin': '11_82~CUW~9_92#MGNP'} Metrics: ['ELUC: -8.65720563674034', 'NSGA-II_crowding_distance: 0.2428945662908259', 'NSGA-II_rank: 4', 'change: 0.16532027218307943', 'is_elite: False']\n", + "Id: 12_12 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '11_82'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_12', 'origin': '11_18~CUW~11_82#MGNP'} Metrics: ['ELUC: -9.25946872485681', 'NSGA-II_crowding_distance: 0.9693742651925321', 'NSGA-II_rank: 6', 'change: 0.17136439868706824', 'is_elite: False']\n", + "Id: 12_90 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '11_29'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_90', 'origin': '11_39~CUW~11_29#MGNP'} Metrics: ['ELUC: -9.495747737564399', 'NSGA-II_crowding_distance: 0.45252842834077905', 'NSGA-II_rank: 5', 'change: 0.17120304115098894', 'is_elite: False']\n", + "Id: 12_32 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '11_51'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_32', 'origin': '11_18~CUW~11_51#MGNP'} Metrics: ['ELUC: -9.56282582845779', 'NSGA-II_crowding_distance: 0.28610426186300403', 'NSGA-II_rank: 5', 'change: 0.18054035522145048', 'is_elite: False']\n", + "Id: 12_96 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '11_51'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_96', 'origin': '11_18~CUW~11_51#MGNP'} Metrics: ['ELUC: -9.614465476817053', 'NSGA-II_crowding_distance: 0.12843177816991314', 'NSGA-II_rank: 4', 'change: 0.16755745188803967', 'is_elite: False']\n", + "Id: 12_48 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '11_46'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_48', 'origin': '1_1~CUW~11_46#MGNP'} Metrics: ['ELUC: -9.637069005829725', 'NSGA-II_crowding_distance: 0.3033655228883694', 'NSGA-II_rank: 4', 'change: 0.17782241849083597', 'is_elite: False']\n", + "Id: 12_52 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_75', '11_39'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_52', 'origin': '11_75~CUW~11_39#MGNP'} Metrics: ['ELUC: -9.665921029371576', 'NSGA-II_crowding_distance: 0.20153697040216906', 'NSGA-II_rank: 3', 'change: 0.16508353471515747', 'is_elite: False']\n", + "Id: 12_95 Identity: {'ancestor_count': 11, 'ancestor_ids': ['9_26', '11_74'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_95', 'origin': '9_26~CUW~11_74#MGNP'} Metrics: ['ELUC: -9.9162632825113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.25326918202204024', 'is_elite: False']\n", + "Id: 12_63 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_92', '11_29'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_63', 'origin': '9_92~CUW~11_29#MGNP'} Metrics: ['ELUC: -10.144682327468555', 'NSGA-II_crowding_distance: 0.1209623906684081', 'NSGA-II_rank: 3', 'change: 0.1698651345476328', 'is_elite: False']\n", + "Id: 12_64 Identity: {'ancestor_count': 8, 'ancestor_ids': ['11_75', '11_82'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_64', 'origin': '11_75~CUW~11_82#MGNP'} Metrics: ['ELUC: -10.195318464527414', 'NSGA-II_crowding_distance: 0.5874723713626578', 'NSGA-II_rank: 5', 'change: 0.21872245231549844', 'is_elite: False']\n", + "Id: 11_18 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_18', 'origin': '9_92~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.503893423212768', 'NSGA-II_crowding_distance: 0.4625328188063272', 'NSGA-II_rank: 1', 'change: 0.13334228771385556', 'is_elite: True']\n", + "Id: 12_57 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_92', '11_48'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_57', 'origin': '9_92~CUW~11_48#MGNP'} Metrics: ['ELUC: -10.658280058574835', 'NSGA-II_crowding_distance: 0.08906690366948777', 'NSGA-II_rank: 3', 'change: 0.17920611715764323', 'is_elite: False']\n", + "Id: 12_34 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_92', '9_26'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_34', 'origin': '9_92~CUW~9_26#MGNP'} Metrics: ['ELUC: -10.816039917834996', 'NSGA-II_crowding_distance: 0.12872263642205667', 'NSGA-II_rank: 3', 'change: 0.18121395278971594', 'is_elite: False']\n", + "Id: 12_92 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_92', '11_18'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_92', 'origin': '9_92~CUW~11_18#MGNP'} Metrics: ['ELUC: -10.877972856143217', 'NSGA-II_crowding_distance: 0.09960924284154807', 'NSGA-II_rank: 1', 'change: 0.15034977495601035', 'is_elite: False']\n", + "Id: 12_44 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '11_39'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_44', 'origin': '2_49~CUW~11_39#MGNP'} Metrics: ['ELUC: -10.888574350489632', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2802220781426098', 'is_elite: False']\n", + "Id: 12_61 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_18', '11_87'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_61', 'origin': '11_18~CUW~11_87#MGNP'} Metrics: ['ELUC: -10.902281984790353', 'NSGA-II_crowding_distance: 0.2921880079691904', 'NSGA-II_rank: 2', 'change: 0.15670698585556525', 'is_elite: False']\n", + "Id: 12_51 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '11_39'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_51', 'origin': '1_1~CUW~11_39#MGNP'} Metrics: ['ELUC: -11.034061178960684', 'NSGA-II_crowding_distance: 0.17248586523425508', 'NSGA-II_rank: 2', 'change: 0.17109404603313824', 'is_elite: False']\n", + "Id: 12_88 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_92', '11_18'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_88', 'origin': '9_92~CUW~11_18#MGNP'} Metrics: ['ELUC: -11.20172721058043', 'NSGA-II_crowding_distance: 0.06540333040421425', 'NSGA-II_rank: 1', 'change: 0.15122101150176054', 'is_elite: False']\n", + "Id: 12_15 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_77', '11_87'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_15', 'origin': '11_77~CUW~11_87#MGNP'} Metrics: ['ELUC: -11.390676944080349', 'NSGA-II_crowding_distance: 0.4967962920911658', 'NSGA-II_rank: 4', 'change: 0.20643446221371003', 'is_elite: False']\n", + "Id: 12_38 Identity: {'ancestor_count': 3, 'ancestor_ids': ['11_98', '1_1'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_38', 'origin': '11_98~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.43583051652628', 'NSGA-II_crowding_distance: 0.37155786635866833', 'NSGA-II_rank: 4', 'change: 0.26075979632350377', 'is_elite: False']\n", + "Id: 12_40 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_29', '11_75'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_40', 'origin': '11_29~CUW~11_75#MGNP'} Metrics: ['ELUC: -11.603505684721107', 'NSGA-II_crowding_distance: 0.5251149297873814', 'NSGA-II_rank: 3', 'change: 0.1960088436660054', 'is_elite: False']\n", + "Id: 9_92 Identity: {'ancestor_count': 7, 'ancestor_ids': ['8_21', '8_60'], 'birth_generation': 9, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '9_92', 'origin': '8_21~CUW~8_60#MGNP'} Metrics: ['ELUC: -11.619260633154786', 'NSGA-II_crowding_distance: 0.16203318426757574', 'NSGA-II_rank: 1', 'change: 0.15728478917744898', 'is_elite: False']\n", + "Id: 12_97 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '11_51'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_97', 'origin': '1_1~CUW~11_51#MGNP'} Metrics: ['ELUC: -11.667227360113193', 'NSGA-II_crowding_distance: 0.24936950679698422', 'NSGA-II_rank: 2', 'change: 0.18923927352809272', 'is_elite: False']\n", + "Id: 12_11 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_11', 'origin': '10_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.545483548598765', 'NSGA-II_crowding_distance: 0.19970916126807292', 'NSGA-II_rank: 4', 'change: 0.27177148080661656', 'is_elite: False']\n", + "Id: 12_67 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_77', '9_92'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_67', 'origin': '11_77~CUW~9_92#MGNP'} Metrics: ['ELUC: -12.703072524058527', 'NSGA-II_crowding_distance: 0.39388237092965905', 'NSGA-II_rank: 2', 'change: 0.208816204675419', 'is_elite: False']\n", + "Id: 11_39 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_39', 'origin': '9_92~CUW~9_92#MGNP'} Metrics: ['ELUC: -12.75204010873119', 'NSGA-II_crowding_distance: 0.24577620408332784', 'NSGA-II_rank: 1', 'change: 0.1732588150378695', 'is_elite: True']\n", + "Id: 12_35 Identity: {'ancestor_count': 8, 'ancestor_ids': ['11_82', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_35', 'origin': '11_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.053687504384968', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.278565138289348', 'is_elite: False']\n", + "Id: 12_76 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_46', '11_39'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_76', 'origin': '11_46~CUW~11_39#MGNP'} Metrics: ['ELUC: -13.767949486283081', 'NSGA-II_crowding_distance: 0.179605593051195', 'NSGA-II_rank: 1', 'change: 0.19415501920466285', 'is_elite: False']\n", + "Id: 12_53 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_29', '11_87'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_53', 'origin': '11_29~CUW~11_87#MGNP'} Metrics: ['ELUC: -13.91023325067641', 'NSGA-II_crowding_distance: 0.15989867554199988', 'NSGA-II_rank: 1', 'change: 0.20719422684436486', 'is_elite: False']\n", + "Id: 12_79 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '11_82'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_79', 'origin': '1_1~CUW~11_82#MGNP'} Metrics: ['ELUC: -14.68492272545167', 'NSGA-II_crowding_distance: 0.3232990227245267', 'NSGA-II_rank: 2', 'change: 0.24251418537206815', 'is_elite: False']\n", + "Id: 12_37 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_48', '11_29'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_37', 'origin': '11_48~CUW~11_29#MGNP'} Metrics: ['ELUC: -14.727678527788418', 'NSGA-II_crowding_distance: 0.22437605945148148', 'NSGA-II_rank: 1', 'change: 0.22557832295214938', 'is_elite: True']\n", + "Id: 12_72 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '11_82'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_72', 'origin': '11_18~CUW~11_82#MGNP'} Metrics: ['ELUC: -14.784060368610914', 'NSGA-II_crowding_distance: 0.5785341521464855', 'NSGA-II_rank: 3', 'change: 0.24796548914772482', 'is_elite: False']\n", + "Id: 12_74 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_29', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_74', 'origin': '11_29~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.166487718551387', 'NSGA-II_crowding_distance: 0.2235520172348966', 'NSGA-II_rank: 3', 'change: 0.28250006275453604', 'is_elite: False']\n", + "Id: 12_17 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '9_26'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_17', 'origin': '2_49~CUW~9_26#MGNP'} Metrics: ['ELUC: -15.480075772925534', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29228719429246675', 'is_elite: False']\n", + "Id: 12_77 Identity: {'ancestor_count': 8, 'ancestor_ids': ['11_82', '9_92'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_77', 'origin': '11_82~CUW~9_92#MGNP'} Metrics: ['ELUC: -15.622371110871622', 'NSGA-II_crowding_distance: 0.2781805968844438', 'NSGA-II_rank: 2', 'change: 0.24522955778011743', 'is_elite: False']\n", + "Id: 12_36 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_92', '11_29'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_36', 'origin': '9_92~CUW~11_29#MGNP'} Metrics: ['ELUC: -15.727471294654041', 'NSGA-II_crowding_distance: 0.20798490734389058', 'NSGA-II_rank: 1', 'change: 0.24330395300284782', 'is_elite: False']\n", + "Id: 12_91 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_91', 'origin': '2_49~CUW~10_16#MGNP'} Metrics: ['ELUC: -15.816909673433353', 'NSGA-II_crowding_distance: 0.23089564323838846', 'NSGA-II_rank: 2', 'change: 0.296662972978841', 'is_elite: False']\n", + "Id: 12_20 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_20', 'origin': '10_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.13990907497811', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.29715264037856', 'is_elite: False']\n", + "Id: 12_89 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_82', '11_18'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_89', 'origin': '11_82~CUW~11_18#MGNP'} Metrics: ['ELUC: -16.243779737569206', 'NSGA-II_crowding_distance: 0.28357843886046175', 'NSGA-II_rank: 1', 'change: 0.26190767948584065', 'is_elite: True']\n", + "Id: 12_55 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_55', 'origin': '2_49~CUW~10_16#MGNP'} Metrics: ['ELUC: -17.450090365630256', 'NSGA-II_crowding_distance: 0.21021004108002628', 'NSGA-II_rank: 1', 'change: 0.29868406294517097', 'is_elite: False']\n", + "Id: 12_25 Identity: {'ancestor_count': 3, 'ancestor_ids': ['11_98', '11_98'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_25', 'origin': '11_98~CUW~11_98#MGNP'} Metrics: ['ELUC: -17.537911695021084', 'NSGA-II_crowding_distance: 0.020704661630307646', 'NSGA-II_rank: 1', 'change: 0.30266785295370024', 'is_elite: False']\n", + "Id: 12_30 Identity: {'ancestor_count': 3, 'ancestor_ids': ['11_98', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_30', 'origin': '11_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.56832897086345', 'NSGA-II_crowding_distance: 0.004564418259415549', 'NSGA-II_rank: 1', 'change: 0.3028553269911412', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 11_98 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_98', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 12_26 Identity: {'ancestor_count': 3, 'ancestor_ids': ['11_98', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_26', 'origin': '11_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 12_42 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_42', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 12_93 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '11_98'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_93', 'origin': '9_92~CUW~11_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 12_98 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_98', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 12.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 13...:\n", + "PopulationResponse:\n", + " Generation: 13\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/13/20240219-211412\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 13 and asking ESP for generation 14...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 13 data persisted.\n", + "Evaluated candidates:\n", + "Id: 13_94 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_94', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 10.34321356319538', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2759638251605149', 'is_elite: False']\n", + "Id: 13_12 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_12', 'origin': '11_39~CUW~12_98#MGNP'} Metrics: ['ELUC: 8.841330043764525', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2559501788844413', 'is_elite: False']\n", + "Id: 13_72 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_36', '12_55'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_72', 'origin': '12_36~CUW~12_55#MGNP'} Metrics: ['ELUC: 6.191385187437341', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24470508332014082', 'is_elite: False']\n", + "Id: 13_64 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_64', 'origin': '2_49~CUW~11_18#MGNP'} Metrics: ['ELUC: 5.795126774771113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2678075724258717', 'is_elite: False']\n", + "Id: 13_52 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_52', 'origin': '1_1~CUW~11_18#MGNP'} Metrics: ['ELUC: 5.73511514935127', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.122323481040387', 'is_elite: False']\n", + "Id: 13_35 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_56', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_35', 'origin': '12_56~CUW~11_18#MGNP'} Metrics: ['ELUC: 2.9389667285151617', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1364987628971588', 'is_elite: False']\n", + "Id: 13_25 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '12_87'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_25', 'origin': '12_71~CUW~12_87#MGNP'} Metrics: ['ELUC: 1.6884008420224141', 'NSGA-II_crowding_distance: 1.1987889936275267', 'NSGA-II_rank: 7', 'change: 0.1410253525345886', 'is_elite: False']\n", + "Id: 13_67 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_67', 'origin': '12_23~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.2693413633887005', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03118830514273151', 'is_elite: False']\n", + "Id: 13_61 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_61', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.20783309485964677', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04325689410143276', 'is_elite: False']\n", + "Id: 13_79 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_79', 'origin': '12_23~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.15337576724281118', 'NSGA-II_crowding_distance: 0.23797123381284926', 'NSGA-II_rank: 3', 'change: 0.045721924572001346', 'is_elite: False']\n", + "Id: 13_59 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '2_49'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_59', 'origin': '12_71~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.09427403474651484', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3146761408339794', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 13_29 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_29', 'origin': '11_18~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.24696795352033757', 'NSGA-II_crowding_distance: 1.198774776154001', 'NSGA-II_rank: 6', 'change: 0.12779104446335715', 'is_elite: False']\n", + "Id: 13_85 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_92', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_85', 'origin': '12_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.4332086567527898', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08631110876046832', 'is_elite: False']\n", + "Id: 13_19 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_19', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.46148740605512645', 'NSGA-II_crowding_distance: 0.1485319392526702', 'NSGA-II_rank: 2', 'change: 0.03965564324371746', 'is_elite: False']\n", + "Id: 13_24 Identity: {'ancestor_count': 3, 'ancestor_ids': ['12_98', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_24', 'origin': '12_98~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 1.82496666402582', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 13_43 Identity: {'ancestor_count': 9, 'ancestor_ids': ['12_87', '11_39'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_43', 'origin': '12_87~CUW~11_39#MGNP'} Metrics: ['ELUC: -1.149929569651703', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11461441536985911', 'is_elite: False']\n", + "Id: 13_96 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_89', '12_80'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_96', 'origin': '12_89~CUW~12_80#MGNP'} Metrics: ['ELUC: -1.2523657705600701', 'NSGA-II_crowding_distance: 0.3446160363273557', 'NSGA-II_rank: 4', 'change: 0.10705034909508584', 'is_elite: False']\n", + "Id: 12_23 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '1_1'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_23', 'origin': '11_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2534769974134168', 'NSGA-II_crowding_distance: 0.22018216396675105', 'NSGA-II_rank: 1', 'change: 0.03000838202835237', 'is_elite: True']\n", + "Id: 13_30 Identity: {'ancestor_count': 9, 'ancestor_ids': ['12_23', '10_16'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_30', 'origin': '12_23~CUW~10_16#MGNP'} Metrics: ['ELUC: -1.3182375959622408', 'NSGA-II_crowding_distance: 0.0992042769284019', 'NSGA-II_rank: 2', 'change: 0.04473605391995902', 'is_elite: False']\n", + "Id: 13_18 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_18', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6840378685396324', 'NSGA-II_crowding_distance: 0.18742052241188573', 'NSGA-II_rank: 2', 'change: 0.04598586543830206', 'is_elite: False']\n", + "Id: 13_76 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '12_87'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_76', 'origin': '12_23~CUW~12_87#MGNP'} Metrics: ['ELUC: -1.6851549287199454', 'NSGA-II_crowding_distance: 0.10980838426418046', 'NSGA-II_rank: 1', 'change: 0.041997963359800806', 'is_elite: False']\n", + "Id: 13_83 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '12_87'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_83', 'origin': '12_71~CUW~12_87#MGNP'} Metrics: ['ELUC: -1.7152359160291757', 'NSGA-II_crowding_distance: 0.22280612289182', 'NSGA-II_rank: 4', 'change: 0.12750506767992664', 'is_elite: False']\n", + "Id: 13_11 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_89', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_11', 'origin': '12_89~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.738921862580735', 'NSGA-II_crowding_distance: 1.4049939784366905', 'NSGA-II_rank: 5', 'change: 0.21574441574571812', 'is_elite: False']\n", + "Id: 13_48 Identity: {'ancestor_count': 10, 'ancestor_ids': ['9_92', '12_80'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_48', 'origin': '9_92~CUW~12_80#MGNP'} Metrics: ['ELUC: -2.185667478633145', 'NSGA-II_crowding_distance: 0.37751488552568746', 'NSGA-II_rank: 3', 'change: 0.06541405912566452', 'is_elite: False']\n", + "Id: 13_56 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '12_87'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_56', 'origin': '1_1~CUW~12_87#MGNP'} Metrics: ['ELUC: -2.2197157091994923', 'NSGA-II_crowding_distance: 0.09477084493089555', 'NSGA-II_rank: 1', 'change: 0.04637538804136115', 'is_elite: False']\n", + "Id: 13_16 Identity: {'ancestor_count': 11, 'ancestor_ids': ['1_1', '12_53'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_16', 'origin': '1_1~CUW~12_53#MGNP'} Metrics: ['ELUC: -2.442514887144116', 'NSGA-II_crowding_distance: 0.4644977614478527', 'NSGA-II_rank: 4', 'change: 0.12767262969396131', 'is_elite: False']\n", + "Id: 13_62 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_23', '12_80'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_62', 'origin': '12_23~CUW~12_80#MGNP'} Metrics: ['ELUC: -2.950779476177818', 'NSGA-II_crowding_distance: 0.11501682353145418', 'NSGA-II_rank: 1', 'change: 0.048797432864316856', 'is_elite: False']\n", + "Id: 13_38 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_56', '11_39'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_38', 'origin': '12_56~CUW~11_39#MGNP'} Metrics: ['ELUC: -3.282554319884755', 'NSGA-II_crowding_distance: 0.7640356619467594', 'NSGA-II_rank: 3', 'change: 0.08701426618827995', 'is_elite: False']\n", + "Id: 13_58 Identity: {'ancestor_count': 10, 'ancestor_ids': ['9_92', '12_71'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_58', 'origin': '9_92~CUW~12_71#MGNP'} Metrics: ['ELUC: -3.2894087433428205', 'NSGA-II_crowding_distance: 0.4089172108180743', 'NSGA-II_rank: 2', 'change: 0.06236825359552909', 'is_elite: False']\n", + "Id: 13_68 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '12_87'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_68', 'origin': '1_1~CUW~12_87#MGNP'} Metrics: ['ELUC: -3.3333974754965636', 'NSGA-II_crowding_distance: 0.1322018417444908', 'NSGA-II_rank: 1', 'change: 0.06179432218612942', 'is_elite: False']\n", + "Id: 13_57 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '12_23'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_57', 'origin': '2_49~CUW~12_23#MGNP'} Metrics: ['ELUC: -3.5341856684874027', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2653563002842475', 'is_elite: False']\n", + "Id: 13_88 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_88', 'origin': '11_18~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.8673051266746126', 'NSGA-II_crowding_distance: 0.7056228826854696', 'NSGA-II_rank: 2', 'change: 0.11994069811682997', 'is_elite: False']\n", + "Id: 13_97 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '12_55'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_97', 'origin': '12_71~CUW~12_55#MGNP'} Metrics: ['ELUC: -3.878534297047486', 'NSGA-II_crowding_distance: 1.028908202223906', 'NSGA-II_rank: 6', 'change: 0.22234721010181963', 'is_elite: False']\n", + "Id: 13_42 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '12_89'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_42', 'origin': '12_71~CUW~12_89#MGNP'} Metrics: ['ELUC: -3.974882159769743', 'NSGA-II_crowding_distance: 0.6329260151191214', 'NSGA-II_rank: 4', 'change: 0.17418354895969593', 'is_elite: False']\n", + "Id: 12_87 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '8_60'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_87', 'origin': '11_75~CUW~8_60#MGNP'} Metrics: ['ELUC: -4.1648722420466315', 'NSGA-II_crowding_distance: 0.16399961825074644', 'NSGA-II_rank: 1', 'change: 0.0676399878587724', 'is_elite: True']\n", + "Id: 13_71 Identity: {'ancestor_count': 9, 'ancestor_ids': ['12_87', '11_39'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_71', 'origin': '12_87~CUW~11_39#MGNP'} Metrics: ['ELUC: -4.448990917015797', 'NSGA-II_crowding_distance: 0.13970556344725607', 'NSGA-II_rank: 1', 'change: 0.09179618894519434', 'is_elite: False']\n", + "Id: 13_28 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_37', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_28', 'origin': '12_37~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.748879256308505', 'NSGA-II_crowding_distance: 0.08841266805494741', 'NSGA-II_rank: 1', 'change: 0.09941423556112268', 'is_elite: False']\n", + "Id: 13_32 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_18', '12_71'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_32', 'origin': '11_18~CUW~12_71#MGNP'} Metrics: ['ELUC: -5.241220406326345', 'NSGA-II_crowding_distance: 0.05676919039140489', 'NSGA-II_rank: 1', 'change: 0.10473218018777924', 'is_elite: False']\n", + "Id: 12_71 Identity: {'ancestor_count': 9, 'ancestor_ids': ['9_26', '10_16'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_71', 'origin': '9_26~CUW~10_16#MGNP'} Metrics: ['ELUC: -5.246721707814474', 'NSGA-II_crowding_distance: 0.08338563756380703', 'NSGA-II_rank: 1', 'change: 0.10790435701581459', 'is_elite: False']\n", + "Id: 13_53 Identity: {'ancestor_count': 8, 'ancestor_ids': ['12_98', '9_92'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_53', 'origin': '12_98~CUW~9_92#MGNP'} Metrics: ['ELUC: -5.704396670317941', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27141288544831405', 'is_elite: False']\n", + "Id: 13_36 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_36', 'origin': '12_71~CUW~11_18#MGNP'} Metrics: ['ELUC: -5.971034032582094', 'NSGA-II_crowding_distance: 0.3842570985591533', 'NSGA-II_rank: 1', 'change: 0.11722743399293699', 'is_elite: True']\n", + "Id: 13_66 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_87', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_66', 'origin': '12_87~CUW~12_98#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 13_87 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_87', '12_55'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_87', 'origin': '12_87~CUW~12_55#MGNP'} Metrics: ['ELUC: -6.044441921134705', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 13_89 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_55', '11_39'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_89', 'origin': '12_55~CUW~11_39#MGNP'} Metrics: ['ELUC: -6.189154652412246', 'NSGA-II_crowding_distance: 0.6006525138498677', 'NSGA-II_rank: 6', 'change: 0.23686497053204425', 'is_elite: False']\n", + "Id: 13_27 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_36', '12_80'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_27', 'origin': '12_36~CUW~12_80#MGNP'} Metrics: ['ELUC: -6.5359410576959025', 'NSGA-II_crowding_distance: 0.5451535350744757', 'NSGA-II_rank: 4', 'change: 0.17439843836369787', 'is_elite: False']\n", + "Id: 13_60 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_55', '12_71'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_60', 'origin': '12_55~CUW~12_71#MGNP'} Metrics: ['ELUC: -8.002659634107333', 'NSGA-II_crowding_distance: 1.2712383011015425', 'NSGA-II_rank: 5', 'change: 0.21980484673186382', 'is_elite: False']\n", + "Id: 13_91 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '12_87'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_91', 'origin': '12_71~CUW~12_87#MGNP'} Metrics: ['ELUC: -8.397990855911507', 'NSGA-II_crowding_distance: 0.42711735531425554', 'NSGA-II_rank: 4', 'change: 0.19949910718381905', 'is_elite: False']\n", + "Id: 13_40 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_37', '12_71'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_40', 'origin': '12_37~CUW~12_71#MGNP'} Metrics: ['ELUC: -8.567140053910109', 'NSGA-II_crowding_distance: 0.7144889342409069', 'NSGA-II_rank: 3', 'change: 0.15871999777142812', 'is_elite: False']\n", + "Id: 13_73 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_87', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_73', 'origin': '12_87~CUW~12_98#MGNP'} Metrics: ['ELUC: -8.707366983762057', 'NSGA-II_crowding_distance: 0.45799711916555264', 'NSGA-II_rank: 6', 'change: 0.27234533696976454', 'is_elite: False']\n", + "Id: 13_37 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_76', '12_71'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_37', 'origin': '12_76~CUW~12_71#MGNP'} Metrics: ['ELUC: -9.484476394142357', 'NSGA-II_crowding_distance: 0.22174142343551687', 'NSGA-II_rank: 4', 'change: 0.2028328478225292', 'is_elite: False']\n", + "Id: 13_84 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_18', '12_89'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_84', 'origin': '11_18~CUW~12_89#MGNP'} Metrics: ['ELUC: -9.648120024641004', 'NSGA-II_crowding_distance: 0.21966151926686517', 'NSGA-II_rank: 3', 'change: 0.16750044387640892', 'is_elite: False']\n", + "Id: 13_47 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_89', '12_87'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_47', 'origin': '12_89~CUW~12_87#MGNP'} Metrics: ['ELUC: -9.67649692330854', 'NSGA-II_crowding_distance: 0.289888199763839', 'NSGA-II_rank: 4', 'change: 0.21845809669086033', 'is_elite: False']\n", + "Id: 13_100 Identity: {'ancestor_count': 9, 'ancestor_ids': ['12_98', '10_16'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_100', 'origin': '12_98~CUW~10_16#MGNP'} Metrics: ['ELUC: -9.806386141621346', 'NSGA-II_crowding_distance: 0.1469179592506315', 'NSGA-II_rank: 6', 'change: 0.27563969481890344', 'is_elite: False']\n", + "Id: 13_74 Identity: {'ancestor_count': 8, 'ancestor_ids': ['12_98', '9_92'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_74', 'origin': '12_98~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.235688844262363', 'NSGA-II_crowding_distance: 0.11313848705034453', 'NSGA-II_rank: 6', 'change: 0.28108294328389555', 'is_elite: False']\n", + "Id: 13_80 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_18', '12_71'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_80', 'origin': '11_18~CUW~12_71#MGNP'} Metrics: ['ELUC: -10.387237228439925', 'NSGA-II_crowding_distance: 0.19418606367862282', 'NSGA-II_rank: 3', 'change: 0.1857937422451062', 'is_elite: False']\n", + "Id: 13_41 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '9_92'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_41', 'origin': '11_18~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.418079397902053', 'NSGA-II_crowding_distance: 0.6764468045369005', 'NSGA-II_rank: 2', 'change: 0.13365589358920038', 'is_elite: False']\n", + "Id: 11_18 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_18', 'origin': '9_92~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.503893423212768', 'NSGA-II_crowding_distance: 0.39480377377725945', 'NSGA-II_rank: 1', 'change: 0.13334228771385556', 'is_elite: True']\n", + "Id: 13_15 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_89', '2_49'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_15', 'origin': '12_89~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.581030376914018', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.286414102977134', 'is_elite: False']\n", + "Id: 13_54 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '9_92'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_54', 'origin': '1_1~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.665439534601642', 'NSGA-II_crowding_distance: 0.13048021154140158', 'NSGA-II_rank: 1', 'change: 0.15536257360427363', 'is_elite: False']\n", + "Id: 13_14 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_98', '12_89'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_14', 'origin': '12_98~CUW~12_89#MGNP'} Metrics: ['ELUC: -10.79499743764045', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2660757829482983', 'is_elite: False']\n", + "Id: 13_98 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_55', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_98', 'origin': '12_55~CUW~11_18#MGNP'} Metrics: ['ELUC: -10.927173240137861', 'NSGA-II_crowding_distance: 0.42399124371479896', 'NSGA-II_rank: 4', 'change: 0.2314240640564941', 'is_elite: False']\n", + "Id: 13_95 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_37', '11_39'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_95', 'origin': '12_37~CUW~11_39#MGNP'} Metrics: ['ELUC: -11.272805598740945', 'NSGA-II_crowding_distance: 0.11423527832022734', 'NSGA-II_rank: 3', 'change: 0.19116762512306876', 'is_elite: False']\n", + "Id: 13_17 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '12_23'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_17', 'origin': '2_49~CUW~12_23#MGNP'} Metrics: ['ELUC: -11.33769975539517', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.26774448964988484', 'is_elite: False']\n", + "Id: 13_70 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '9_92'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_70', 'origin': '10_16~CUW~9_92#MGNP'} Metrics: ['ELUC: -11.436785754149897', 'NSGA-II_crowding_distance: 0.06690595837735895', 'NSGA-II_rank: 1', 'change: 0.15644320466103923', 'is_elite: False']\n", + "Id: 13_20 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_53', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_20', 'origin': '12_53~CUW~11_18#MGNP'} Metrics: ['ELUC: -11.541421820683333', 'NSGA-II_crowding_distance: 0.3071051956043285', 'NSGA-II_rank: 2', 'change: 0.17420059158267745', 'is_elite: False']\n", + "Id: 13_45 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '11_39'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_45', 'origin': '11_39~CUW~11_39#MGNP'} Metrics: ['ELUC: -11.708789822324851', 'NSGA-II_crowding_distance: 0.13116221556772226', 'NSGA-II_rank: 1', 'change: 0.1576198446331641', 'is_elite: False']\n", + "Id: 13_99 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '1_1'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_99', 'origin': '11_39~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.741084393840335', 'NSGA-II_crowding_distance: 0.25378810069154684', 'NSGA-II_rank: 3', 'change: 0.19294493342782035', 'is_elite: False']\n", + "Id: 13_81 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_18', '12_37'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_81', 'origin': '11_18~CUW~12_37#MGNP'} Metrics: ['ELUC: -12.602345517754639', 'NSGA-II_crowding_distance: 0.15062961318731646', 'NSGA-II_rank: 2', 'change: 0.18007126023566944', 'is_elite: False']\n", + "Id: 13_86 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_18', '12_37'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_86', 'origin': '11_18~CUW~12_37#MGNP'} Metrics: ['ELUC: -12.729915854614463', 'NSGA-II_crowding_distance: 0.2152600759319111', 'NSGA-II_rank: 2', 'change: 0.19500328606049389', 'is_elite: False']\n", + "Id: 11_39 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_39', 'origin': '9_92~CUW~9_92#MGNP'} Metrics: ['ELUC: -12.75204010873119', 'NSGA-II_crowding_distance: 0.30283970693384055', 'NSGA-II_rank: 1', 'change: 0.1732588150378695', 'is_elite: True']\n", + "Id: 13_13 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_37', '12_89'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_13', 'origin': '12_37~CUW~12_89#MGNP'} Metrics: ['ELUC: -13.96283419269095', 'NSGA-II_crowding_distance: 0.5422068782358898', 'NSGA-II_rank: 3', 'change: 0.21245946385733028', 'is_elite: False']\n", + "Id: 13_93 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '12_36'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_93', 'origin': '12_71~CUW~12_36#MGNP'} Metrics: ['ELUC: -14.220285087820098', 'NSGA-II_crowding_distance: 0.46039890371434006', 'NSGA-II_rank: 2', 'change: 0.211148766285226', 'is_elite: False']\n", + "Id: 13_69 Identity: {'ancestor_count': 11, 'ancestor_ids': ['9_92', '12_76'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_69', 'origin': '9_92~CUW~12_76#MGNP'} Metrics: ['ELUC: -14.270093310450855', 'NSGA-II_crowding_distance: 0.287711503167592', 'NSGA-II_rank: 1', 'change: 0.20451435470454712', 'is_elite: True']\n", + "Id: 13_46 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_46', 'origin': '12_71~CUW~12_98#MGNP'} Metrics: ['ELUC: -14.401563307117868', 'NSGA-II_crowding_distance: 0.4471856582703667', 'NSGA-II_rank: 3', 'change: 0.29094028152507345', 'is_elite: False']\n", + "Id: 12_37 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_48', '11_29'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_37', 'origin': '11_48~CUW~11_29#MGNP'} Metrics: ['ELUC: -14.727678527788418', 'NSGA-II_crowding_distance: 0.10768320587388473', 'NSGA-II_rank: 1', 'change: 0.22557832295214938', 'is_elite: False']\n", + "Id: 13_33 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_89', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_33', 'origin': '12_89~CUW~11_18#MGNP'} Metrics: ['ELUC: -14.817431316740949', 'NSGA-II_crowding_distance: 0.1512915670654231', 'NSGA-II_rank: 1', 'change: 0.227356128910817', 'is_elite: False']\n", + "Id: 13_51 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_55', '12_76'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_51', 'origin': '12_55~CUW~12_76#MGNP'} Metrics: ['ELUC: -15.002740143932632', 'NSGA-II_crowding_distance: 0.3359359075918181', 'NSGA-II_rank: 2', 'change: 0.2813743056993784', 'is_elite: False']\n", + "Id: 13_31 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_55', '12_36'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_31', 'origin': '12_55~CUW~12_36#MGNP'} Metrics: ['ELUC: -15.135844613392111', 'NSGA-II_crowding_distance: 0.07099504332798855', 'NSGA-II_rank: 2', 'change: 0.2866189512746254', 'is_elite: False']\n", + "Id: 13_90 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_98', '12_76'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_90', 'origin': '12_98~CUW~12_76#MGNP'} Metrics: ['ELUC: -15.323609444706666', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3074589915456699', 'is_elite: False']\n", + "Id: 13_23 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '12_87'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_23', 'origin': '2_49~CUW~12_87#MGNP'} Metrics: ['ELUC: -15.72575998019886', 'NSGA-II_crowding_distance: 0.1001234765219171', 'NSGA-II_rank: 2', 'change: 0.28844991527625213', 'is_elite: False']\n", + "Id: 13_75 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_89', '12_53'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_75', 'origin': '12_89~CUW~12_53#MGNP'} Metrics: ['ELUC: -15.806849518357986', 'NSGA-II_crowding_distance: 0.19692195496135773', 'NSGA-II_rank: 1', 'change: 0.25240649066124904', 'is_elite: True']\n", + "Id: 13_78 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_98', '12_36'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_78', 'origin': '12_98~CUW~12_36#MGNP'} Metrics: ['ELUC: -15.861946061817312', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30151717549090673', 'is_elite: False']\n", + "Id: 12_89 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_82', '11_18'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_89', 'origin': '11_82~CUW~11_18#MGNP'} Metrics: ['ELUC: -16.243779737569206', 'NSGA-II_crowding_distance: 0.07461933246196803', 'NSGA-II_rank: 1', 'change: 0.26190767948584065', 'is_elite: False']\n", + "Id: 13_55 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_89', '9_92'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_55', 'origin': '12_89~CUW~9_92#MGNP'} Metrics: ['ELUC: -16.352448645247595', 'NSGA-II_crowding_distance: 0.03644530976982493', 'NSGA-II_rank: 1', 'change: 0.2654122512098532', 'is_elite: False']\n", + "Id: 13_39 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_89', '11_39'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_39', 'origin': '12_89~CUW~11_39#MGNP'} Metrics: ['ELUC: -16.46327877873397', 'NSGA-II_crowding_distance: 0.0843649555713749', 'NSGA-II_rank: 1', 'change: 0.2690571813434578', 'is_elite: False']\n", + "Id: 13_34 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_55', '12_36'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_34', 'origin': '12_55~CUW~12_36#MGNP'} Metrics: ['ELUC: -16.806139667680405', 'NSGA-II_crowding_distance: 0.12726978102204542', 'NSGA-II_rank: 1', 'change: 0.2828855973627345', 'is_elite: False']\n", + "Id: 13_65 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_98', '12_53'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_65', 'origin': '12_98~CUW~12_53#MGNP'} Metrics: ['ELUC: -16.887282765411758', 'NSGA-II_crowding_distance: 0.10904825275504432', 'NSGA-II_rank: 1', 'change: 0.29983616939522567', 'is_elite: False']\n", + "Id: 13_49 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_89', '2_49'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_49', 'origin': '12_89~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.574875123783883', 'NSGA-II_crowding_distance: 0.05104389190765968', 'NSGA-II_rank: 1', 'change: 0.30237748818650967', 'is_elite: False']\n", + "Id: 13_21 Identity: {'ancestor_count': 9, 'ancestor_ids': ['10_16', '2_49'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_21', 'origin': '10_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597132604481576', 'NSGA-II_crowding_distance: 0.00343525882952205', 'NSGA-II_rank: 1', 'change: 0.30302015867341875', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 12_98 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_98', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 13_22 Identity: {'ancestor_count': 3, 'ancestor_ids': ['12_98', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_22', 'origin': '12_98~CUW~12_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 13_26 Identity: {'ancestor_count': 3, 'ancestor_ids': ['12_98', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_26', 'origin': '12_98~CUW~12_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 13_44 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_44', 'origin': '2_49~CUW~12_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 13_50 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_50', 'origin': '2_49~CUW~12_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 13_63 Identity: {'ancestor_count': 3, 'ancestor_ids': ['12_98', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_63', 'origin': '12_98~CUW~12_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 13_77 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '12_55'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_77', 'origin': '1_1~CUW~12_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 13_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_82', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 13_92 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_92', 'origin': '2_49~CUW~12_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 13.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 14...:\n", + "PopulationResponse:\n", + " Generation: 14\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/14/20240219-212124\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 14 and asking ESP for generation 15...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 14 data persisted.\n", + "Evaluated candidates:\n", + "Id: 14_26 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_26', 'origin': '2_49~CUW~12_23#MGNP'} Metrics: ['ELUC: 17.86476976957827', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27572361128217', 'is_elite: False']\n", + "Id: 14_98 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '2_49'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_98', 'origin': '12_23~CUW~2_49#MGNP'} Metrics: ['ELUC: 12.800236401847837', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.29103606462127424', 'is_elite: False']\n", + "Id: 14_76 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '2_49'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_76', 'origin': '13_69~CUW~2_49#MGNP'} Metrics: ['ELUC: 9.805622063185078', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2501165182145023', 'is_elite: False']\n", + "Id: 14_39 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_87', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_39', 'origin': '12_87~CUW~13_92#MGNP'} Metrics: ['ELUC: 4.323750945593125', 'NSGA-II_crowding_distance: 1.6162936750490091', 'NSGA-II_rank: 10', 'change: 0.25274830264274945', 'is_elite: False']\n", + "Id: 14_46 Identity: {'ancestor_count': 9, 'ancestor_ids': ['12_87', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_46', 'origin': '12_87~CUW~11_18#MGNP'} Metrics: ['ELUC: 3.159206328575617', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.15862358196963214', 'is_elite: False']\n", + "Id: 14_72 Identity: {'ancestor_count': 11, 'ancestor_ids': ['1_1', '13_33'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_72', 'origin': '1_1~CUW~13_33#MGNP'} Metrics: ['ELUC: 2.9912772315815954', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08225693026473686', 'is_elite: False']\n", + "Id: 14_45 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_68', '13_75'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_45', 'origin': '13_68~CUW~13_75#MGNP'} Metrics: ['ELUC: 1.7193649413927288', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.10862304328346964', 'is_elite: False']\n", + "Id: 14_31 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '12_87'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_31', 'origin': '13_69~CUW~12_87#MGNP'} Metrics: ['ELUC: 1.2619867455296525', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.13500968551390025', 'is_elite: False']\n", + "Id: 14_84 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_84', 'origin': '11_18~CUW~12_23#MGNP'} Metrics: ['ELUC: 1.2221763022076428', 'NSGA-II_crowding_distance: 0.5308436707667072', 'NSGA-II_rank: 4', 'change: 0.10349955290310886', 'is_elite: False']\n", + "Id: 14_71 Identity: {'ancestor_count': 8, 'ancestor_ids': ['12_23', '13_68'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_71', 'origin': '12_23~CUW~13_68#MGNP'} Metrics: ['ELUC: 1.1202853380459759', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04723195051255178', 'is_elite: False']\n", + "Id: 14_33 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_71', '13_45'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_33', 'origin': '13_71~CUW~13_45#MGNP'} Metrics: ['ELUC: 0.788239555653066', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.12849727653442813', 'is_elite: False']\n", + "Id: 14_13 Identity: {'ancestor_count': 9, 'ancestor_ids': ['13_68', '11_39'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_13', 'origin': '13_68~CUW~11_39#MGNP'} Metrics: ['ELUC: 0.6790294896001565', 'NSGA-II_crowding_distance: 0.3592084654458866', 'NSGA-II_rank: 5', 'change: 0.11963217652741633', 'is_elite: False']\n", + "Id: 14_90 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_68', '13_45'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_90', 'origin': '13_68~CUW~13_45#MGNP'} Metrics: ['ELUC: 0.4101019597011018', 'NSGA-II_crowding_distance: 0.24067482707277782', 'NSGA-II_rank: 3', 'change: 0.0863980090347943', 'is_elite: False']\n", + "Id: 14_94 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_94', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.1946610232745918', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.028280630069407592', 'is_elite: False']\n", + "Id: 14_74 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_74', 'origin': '2_49~CUW~12_23#MGNP'} Metrics: ['ELUC: -0.001220037181166947', 'NSGA-II_crowding_distance: 1.424178807514417', 'NSGA-II_rank: 10', 'change: 0.263047982170913', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 14_57 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '1_1'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_57', 'origin': '13_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.05311807146461452', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.15697782375506072', 'is_elite: False']\n", + "Id: 14_29 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_18', '13_71'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_29', 'origin': '11_18~CUW~13_71#MGNP'} Metrics: ['ELUC: -0.33989888149470526', 'NSGA-II_crowding_distance: 0.1651371076502426', 'NSGA-II_rank: 3', 'change: 0.08883965734648107', 'is_elite: False']\n", + "Id: 14_48 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_48', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.944539740319652', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 14_22 Identity: {'ancestor_count': 10, 'ancestor_ids': ['11_39', '13_71'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_22', 'origin': '11_39~CUW~13_71#MGNP'} Metrics: ['ELUC: -0.9812491424071907', 'NSGA-II_crowding_distance: 0.4116068443879875', 'NSGA-II_rank: 6', 'change: 0.12972583860842207', 'is_elite: False']\n", + "Id: 14_83 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '12_87'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_83', 'origin': '11_39~CUW~12_87#MGNP'} Metrics: ['ELUC: -1.035783584400861', 'NSGA-II_crowding_distance: 0.4385224707675049', 'NSGA-II_rank: 7', 'change: 0.14541692557824823', 'is_elite: False']\n", + "Id: 12_23 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '1_1'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_23', 'origin': '11_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2534769974134168', 'NSGA-II_crowding_distance: 0.36099855037298023', 'NSGA-II_rank: 1', 'change: 0.03000838202835237', 'is_elite: True']\n", + "Id: 14_37 Identity: {'ancestor_count': 12, 'ancestor_ids': ['1_1', '13_75'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_37', 'origin': '1_1~CUW~13_75#MGNP'} Metrics: ['ELUC: -1.3366552165719194', 'NSGA-II_crowding_distance: 0.27267958546016535', 'NSGA-II_rank: 5', 'change: 0.12688249481969258', 'is_elite: False']\n", + "Id: 14_93 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_87', '2_49'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_93', 'origin': '12_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.3856086794012707', 'NSGA-II_crowding_distance: 0.40137060286524656', 'NSGA-II_rank: 8', 'change: 0.2445119805843767', 'is_elite: False']\n", + "Id: 14_32 Identity: {'ancestor_count': 9, 'ancestor_ids': ['13_68', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_32', 'origin': '13_68~CUW~11_18#MGNP'} Metrics: ['ELUC: -2.0085715154548316', 'NSGA-II_crowding_distance: 0.14225686000439186', 'NSGA-II_rank: 5', 'change: 0.128307010157433', 'is_elite: False']\n", + "Id: 14_36 Identity: {'ancestor_count': 9, 'ancestor_ids': ['13_68', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_36', 'origin': '13_68~CUW~11_18#MGNP'} Metrics: ['ELUC: -2.0761078326858966', 'NSGA-II_crowding_distance: 1.2180988805334918', 'NSGA-II_rank: 7', 'change: 0.1478578372807211', 'is_elite: False']\n", + "Id: 14_41 Identity: {'ancestor_count': 8, 'ancestor_ids': ['13_68', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_41', 'origin': '13_68~CUW~12_23#MGNP'} Metrics: ['ELUC: -2.4281346769124075', 'NSGA-II_crowding_distance: 0.13566735829625598', 'NSGA-II_rank: 3', 'change: 0.08908973654473078', 'is_elite: False']\n", + "Id: 14_11 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_71', '13_68'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_11', 'origin': '13_71~CUW~13_68#MGNP'} Metrics: ['ELUC: -2.644761774377441', 'NSGA-II_crowding_distance: 0.4370491136103364', 'NSGA-II_rank: 2', 'change: 0.07670026711683922', 'is_elite: False']\n", + "Id: 14_25 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '1_1'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_25', 'origin': '11_18~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.704248140830125', 'NSGA-II_crowding_distance: 0.8560970642029746', 'NSGA-II_rank: 6', 'change: 0.14327807049193556', 'is_elite: False']\n", + "Id: 14_50 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_71', '13_33'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_50', 'origin': '13_71~CUW~13_33#MGNP'} Metrics: ['ELUC: -2.72535115743546', 'NSGA-II_crowding_distance: 0.3852800087638716', 'NSGA-II_rank: 5', 'change: 0.13159747915079162', 'is_elite: False']\n", + "Id: 14_63 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_45', '13_71'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_63', 'origin': '13_45~CUW~13_71#MGNP'} Metrics: ['ELUC: -2.7656170444851003', 'NSGA-II_crowding_distance: 0.08749692627078597', 'NSGA-II_rank: 3', 'change: 0.08972768466744951', 'is_elite: False']\n", + "Id: 14_96 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '12_87'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_96', 'origin': '1_1~CUW~12_87#MGNP'} Metrics: ['ELUC: -2.930706679732033', 'NSGA-II_crowding_distance: 0.23202298714253689', 'NSGA-II_rank: 1', 'change: 0.06287703782825925', 'is_elite: True']\n", + "Id: 14_67 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_92', '13_62'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_67', 'origin': '13_92~CUW~13_62#MGNP'} Metrics: ['ELUC: -3.044966120831529', 'NSGA-II_crowding_distance: 0.7465624912299906', 'NSGA-II_rank: 8', 'change: 0.24805711067092157', 'is_elite: False']\n", + "Id: 14_19 Identity: {'ancestor_count': 8, 'ancestor_ids': ['12_87', '13_68'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_19', 'origin': '12_87~CUW~13_68#MGNP'} Metrics: ['ELUC: -3.3395846683667867', 'NSGA-II_crowding_distance: 0.0861563002691572', 'NSGA-II_rank: 1', 'change: 0.06383698056651618', 'is_elite: False']\n", + "Id: 14_86 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_71', '11_39'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_86', 'origin': '13_71~CUW~11_39#MGNP'} Metrics: ['ELUC: -3.3509453709097765', 'NSGA-II_crowding_distance: 0.6405646375236224', 'NSGA-II_rank: 4', 'change: 0.10657880245792424', 'is_elite: False']\n", + "Id: 14_20 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '13_68'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_20', 'origin': '13_36~CUW~13_68#MGNP'} Metrics: ['ELUC: -3.5889104041993334', 'NSGA-II_crowding_distance: 0.10617822217471666', 'NSGA-II_rank: 3', 'change: 0.09534629221917179', 'is_elite: False']\n", + "Id: 14_59 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_59', 'origin': '11_39~CUW~12_23#MGNP'} Metrics: ['ELUC: -4.089367845696363', 'NSGA-II_crowding_distance: 0.3212453055287835', 'NSGA-II_rank: 3', 'change: 0.09851495482436336', 'is_elite: False']\n", + "Id: 12_87 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '8_60'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_87', 'origin': '11_75~CUW~8_60#MGNP'} Metrics: ['ELUC: -4.1648722420466315', 'NSGA-II_crowding_distance: 0.09592565468748748', 'NSGA-II_rank: 1', 'change: 0.0676399878587724', 'is_elite: False']\n", + "Id: 14_79 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_71', '13_68'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_79', 'origin': '13_71~CUW~13_68#MGNP'} Metrics: ['ELUC: -4.266232630914458', 'NSGA-II_crowding_distance: 0.24611942668232784', 'NSGA-II_rank: 2', 'change: 0.07942319544908254', 'is_elite: False']\n", + "Id: 14_14 Identity: {'ancestor_count': 10, 'ancestor_ids': ['2_49', '13_71'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_14', 'origin': '2_49~CUW~13_71#MGNP'} Metrics: ['ELUC: -4.314811743697343', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26414532295115506', 'is_elite: False']\n", + "Id: 14_53 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '1_1'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_53', 'origin': '11_39~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.34424950304927', 'NSGA-II_crowding_distance: 0.08886162369390986', 'NSGA-II_rank: 1', 'change: 0.07540958631192861', 'is_elite: False']\n", + "Id: 14_54 Identity: {'ancestor_count': 9, 'ancestor_ids': ['13_54', '1_1'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_54', 'origin': '13_54~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.465530332537837', 'NSGA-II_crowding_distance: 0.20477074740144552', 'NSGA-II_rank: 2', 'change: 0.11617947719158608', 'is_elite: False']\n", + "Id: 14_70 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_71', '1_1'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_70', 'origin': '13_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.839694869687631', 'NSGA-II_crowding_distance: 0.06860366840665737', 'NSGA-II_rank: 1', 'change: 0.08270236808231678', 'is_elite: False']\n", + "Id: 14_55 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '12_87'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_55', 'origin': '12_23~CUW~12_87#MGNP'} Metrics: ['ELUC: -5.114731272853626', 'NSGA-II_crowding_distance: 0.18005446640080947', 'NSGA-II_rank: 1', 'change: 0.08280407901741332', 'is_elite: False']\n", + "Id: 14_27 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '12_87'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_27', 'origin': '13_69~CUW~12_87#MGNP'} Metrics: ['ELUC: -5.210510856925955', 'NSGA-II_crowding_distance: 0.8099594033117572', 'NSGA-II_rank: 5', 'change: 0.14896198173897457', 'is_elite: False']\n", + "Id: 14_75 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_76', '13_36'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_75', 'origin': '13_76~CUW~13_36#MGNP'} Metrics: ['ELUC: -5.272022776003435', 'NSGA-II_crowding_distance: 0.4020517261275024', 'NSGA-II_rank: 2', 'change: 0.12013347224388626', 'is_elite: False']\n", + "Id: 14_44 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_44', 'origin': '11_18~CUW~12_23#MGNP'} Metrics: ['ELUC: -5.508170420112069', 'NSGA-II_crowding_distance: 0.5930610177430814', 'NSGA-II_rank: 4', 'change: 0.14397214229436567', 'is_elite: False']\n", + "Id: 13_36 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_36', 'origin': '12_71~CUW~11_18#MGNP'} Metrics: ['ELUC: -5.971034032582094', 'NSGA-II_crowding_distance: 0.2089120848005429', 'NSGA-II_rank: 1', 'change: 0.11722743399293699', 'is_elite: True']\n", + "Id: 14_85 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_85', 'origin': '11_18~CUW~13_92#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 14_99 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '13_75'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_99', 'origin': '2_49~CUW~13_75#MGNP'} Metrics: ['ELUC: -6.044420008282666', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26285265012303893', 'is_elite: False']\n", + "Id: 14_58 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '13_34'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_58', 'origin': '13_36~CUW~13_34#MGNP'} Metrics: ['ELUC: -6.085041420737441', 'NSGA-II_crowding_distance: 0.8109879055453146', 'NSGA-II_rank: 8', 'change: 0.26068635847540556', 'is_elite: False']\n", + "Id: 14_21 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_45', '13_36'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_21', 'origin': '13_45~CUW~13_36#MGNP'} Metrics: ['ELUC: -6.285646209366383', 'NSGA-II_crowding_distance: 0.5434849676534379', 'NSGA-II_rank: 3', 'change: 0.14035441914272065', 'is_elite: False']\n", + "Id: 14_18 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '13_36'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_18', 'origin': '13_36~CUW~13_36#MGNP'} Metrics: ['ELUC: -6.411884118709213', 'NSGA-II_crowding_distance: 0.3291984816582537', 'NSGA-II_rank: 1', 'change: 0.12312570585009329', 'is_elite: True']\n", + "Id: 14_61 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_34', '13_33'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_61', 'origin': '13_34~CUW~13_33#MGNP'} Metrics: ['ELUC: -6.462861159937399', 'NSGA-II_crowding_distance: 1.5614775292324952', 'NSGA-II_rank: 7', 'change: 0.2330921388096443', 'is_elite: False']\n", + "Id: 14_92 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_92', 'origin': '13_36~CUW~12_23#MGNP'} Metrics: ['ELUC: -6.928249482407904', 'NSGA-II_crowding_distance: 0.858978293077495', 'NSGA-II_rank: 6', 'change: 0.17845423258108536', 'is_elite: False']\n", + "Id: 14_15 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_15', 'origin': '1_1~CUW~13_92#MGNP'} Metrics: ['ELUC: -7.83802286356562', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2701622462250483', 'is_elite: False']\n", + "Id: 14_60 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_34', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_60', 'origin': '13_34~CUW~11_18#MGNP'} Metrics: ['ELUC: -7.926079240583958', 'NSGA-II_crowding_distance: 0.40637551399409355', 'NSGA-II_rank: 6', 'change: 0.2023473402065487', 'is_elite: False']\n", + "Id: 14_24 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_24', 'origin': '13_36~CUW~13_92#MGNP'} Metrics: ['ELUC: -8.517281153528389', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2672216227968179', 'is_elite: False']\n", + "Id: 14_17 Identity: {'ancestor_count': 11, 'ancestor_ids': ['11_39', '13_36'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_17', 'origin': '11_39~CUW~13_36#MGNP'} Metrics: ['ELUC: -8.711673875642278', 'NSGA-II_crowding_distance: 0.3711927047751813', 'NSGA-II_rank: 4', 'change: 0.15454362189627585', 'is_elite: False']\n", + "Id: 14_81 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_23', '13_34'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_81', 'origin': '12_23~CUW~13_34#MGNP'} Metrics: ['ELUC: -9.15902057383507', 'NSGA-II_crowding_distance: 0.7294148625345176', 'NSGA-II_rank: 6', 'change: 0.2096720629555483', 'is_elite: False']\n", + "Id: 14_87 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '13_45'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_87', 'origin': '13_36~CUW~13_45#MGNP'} Metrics: ['ELUC: -9.350636003396435', 'NSGA-II_crowding_distance: 0.7870792413144712', 'NSGA-II_rank: 5', 'change: 0.17651494896742334', 'is_elite: False']\n", + "Id: 14_43 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_43', 'origin': '11_39~CUW~11_18#MGNP'} Metrics: ['ELUC: -9.795463929684626', 'NSGA-II_crowding_distance: 0.21654326790900466', 'NSGA-II_rank: 4', 'change: 0.1627573966706243', 'is_elite: False']\n", + "Id: 14_91 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_33', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_91', 'origin': '13_33~CUW~11_18#MGNP'} Metrics: ['ELUC: -9.946550875831468', 'NSGA-II_crowding_distance: 0.1800523297074933', 'NSGA-II_rank: 4', 'change: 0.18076614740530011', 'is_elite: False']\n", + "Id: 14_12 Identity: {'ancestor_count': 11, 'ancestor_ids': ['11_18', '13_36'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_12', 'origin': '11_18~CUW~13_36#MGNP'} Metrics: ['ELUC: -10.076392799992426', 'NSGA-II_crowding_distance: 0.6885752712379644', 'NSGA-II_rank: 5', 'change: 0.21478370954890444', 'is_elite: False']\n", + "Id: 14_95 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_33', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_95', 'origin': '13_33~CUW~11_18#MGNP'} Metrics: ['ELUC: -10.100688715220086', 'NSGA-II_crowding_distance: 0.6595520435812067', 'NSGA-II_rank: 4', 'change: 0.19325914764674298', 'is_elite: False']\n", + "Id: 14_38 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_45', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_38', 'origin': '13_45~CUW~12_23#MGNP'} Metrics: ['ELUC: -10.244552213374657', 'NSGA-II_crowding_distance: 0.6266879852559', 'NSGA-II_rank: 3', 'change: 0.15223180058063732', 'is_elite: False']\n", + "Id: 14_52 Identity: {'ancestor_count': 7, 'ancestor_ids': ['2_49', '12_23'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_52', 'origin': '2_49~CUW~12_23#MGNP'} Metrics: ['ELUC: -10.32621474963244', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2802858729944098', 'is_elite: False']\n", + "Id: 14_97 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '11_39'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_97', 'origin': '2_49~CUW~11_39#MGNP'} Metrics: ['ELUC: -10.392708275165829', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27943723904063483', 'is_elite: False']\n", + "Id: 11_18 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_18', 'origin': '9_92~CUW~9_92#MGNP'} Metrics: ['ELUC: -10.503893423212768', 'NSGA-II_crowding_distance: 0.37479421994502016', 'NSGA-II_rank: 2', 'change: 0.13334228771385556', 'is_elite: False']\n", + "Id: 14_78 Identity: {'ancestor_count': 9, 'ancestor_ids': ['12_23', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_78', 'origin': '12_23~CUW~11_18#MGNP'} Metrics: ['ELUC: -10.802363557674488', 'NSGA-II_crowding_distance: 0.4372950655516683', 'NSGA-II_rank: 2', 'change: 0.1376564561748301', 'is_elite: False']\n", + "Id: 14_68 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_68', 'origin': '11_18~CUW~11_18#MGNP'} Metrics: ['ELUC: -10.870847660171393', 'NSGA-II_crowding_distance: 0.4019964487581802', 'NSGA-II_rank: 1', 'change: 0.13230157729994926', 'is_elite: True']\n", + "Id: 14_40 Identity: {'ancestor_count': 11, 'ancestor_ids': ['1_1', '13_34'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_40', 'origin': '1_1~CUW~13_34#MGNP'} Metrics: ['ELUC: -11.517133890278743', 'NSGA-II_crowding_distance: 0.6179738703125318', 'NSGA-II_rank: 3', 'change: 0.22856958535926153', 'is_elite: False']\n", + "Id: 14_64 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_64', 'origin': '11_39~CUW~11_18#MGNP'} Metrics: ['ELUC: -11.930104070715586', 'NSGA-II_crowding_distance: 0.2442597077539651', 'NSGA-II_rank: 1', 'change: 0.14942659429306818', 'is_elite: True']\n", + "Id: 11_39 Identity: {'ancestor_count': 8, 'ancestor_ids': ['9_92', '9_92'], 'birth_generation': 11, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '11_39', 'origin': '9_92~CUW~9_92#MGNP'} Metrics: ['ELUC: -12.75204010873119', 'NSGA-II_crowding_distance: 0.16841403383197714', 'NSGA-II_rank: 1', 'change: 0.1732588150378695', 'is_elite: False']\n", + "Id: 14_65 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_65', 'origin': '13_69~CUW~13_92#MGNP'} Metrics: ['ELUC: -12.756956998646741', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2720969631958208', 'is_elite: False']\n", + "Id: 14_23 Identity: {'ancestor_count': 12, 'ancestor_ids': ['11_18', '13_69'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_23', 'origin': '11_18~CUW~13_69#MGNP'} Metrics: ['ELUC: -13.247258122281051', 'NSGA-II_crowding_distance: 0.19109124967624014', 'NSGA-II_rank: 1', 'change: 0.17732507861657013', 'is_elite: False']\n", + "Id: 14_80 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_33', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_80', 'origin': '13_33~CUW~11_18#MGNP'} Metrics: ['ELUC: -13.31931044756313', 'NSGA-II_crowding_distance: 0.5390446596825504', 'NSGA-II_rank: 2', 'change: 0.20996957394909416', 'is_elite: False']\n", + "Id: 14_77 Identity: {'ancestor_count': 10, 'ancestor_ids': ['2_49', '13_45'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_77', 'origin': '2_49~CUW~13_45#MGNP'} Metrics: ['ELUC: -13.568128249437331', 'NSGA-II_crowding_distance: 0.5650293309227801', 'NSGA-II_rank: 3', 'change: 0.2650608515401622', 'is_elite: False']\n", + "Id: 14_69 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_54', '13_33'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_69', 'origin': '13_54~CUW~13_33#MGNP'} Metrics: ['ELUC: -14.100394998312597', 'NSGA-II_crowding_distance: 0.18944129160429046', 'NSGA-II_rank: 2', 'change: 0.23477751391054533', 'is_elite: False']\n", + "Id: 13_69 Identity: {'ancestor_count': 11, 'ancestor_ids': ['9_92', '12_76'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_69', 'origin': '9_92~CUW~12_76#MGNP'} Metrics: ['ELUC: -14.270093310450855', 'NSGA-II_crowding_distance: 0.23400410990878648', 'NSGA-II_rank: 1', 'change: 0.20451435470454712', 'is_elite: True']\n", + "Id: 14_89 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_33', '13_33'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_89', 'origin': '13_33~CUW~13_33#MGNP'} Metrics: ['ELUC: -14.616730849004279', 'NSGA-II_crowding_distance: 0.1363512749733688', 'NSGA-II_rank: 1', 'change: 0.22390631588504697', 'is_elite: False']\n", + "Id: 14_56 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '13_69'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_56', 'origin': '13_75~CUW~13_69#MGNP'} Metrics: ['ELUC: -14.82839492562599', 'NSGA-II_crowding_distance: 0.24276554326842426', 'NSGA-II_rank: 2', 'change: 0.2386949276623212', 'is_elite: False']\n", + "Id: 14_30 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_33', '13_33'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_30', 'origin': '13_33~CUW~13_33#MGNP'} Metrics: ['ELUC: -15.062553047188725', 'NSGA-II_crowding_distance: 0.07660164889710948', 'NSGA-II_rank: 1', 'change: 0.23175025053986928', 'is_elite: False']\n", + "Id: 14_82 Identity: {'ancestor_count': 11, 'ancestor_ids': ['2_49', '13_33'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_82', 'origin': '2_49~CUW~13_33#MGNP'} Metrics: ['ELUC: -15.211225144516813', 'NSGA-II_crowding_distance: 0.3301798627238714', 'NSGA-II_rank: 2', 'change: 0.28430167630637504', 'is_elite: False']\n", + "Id: 14_47 Identity: {'ancestor_count': 12, 'ancestor_ids': ['11_18', '13_75'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_47', 'origin': '11_18~CUW~13_75#MGNP'} Metrics: ['ELUC: -15.314896154485298', 'NSGA-II_crowding_distance: 0.07217877780161079', 'NSGA-II_rank: 1', 'change: 0.23491446041404643', 'is_elite: False']\n", + "Id: 14_49 Identity: {'ancestor_count': 12, 'ancestor_ids': ['11_39', '13_75'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_49', 'origin': '11_39~CUW~13_75#MGNP'} Metrics: ['ELUC: -15.67425221449165', 'NSGA-II_crowding_distance: 0.08660375487709146', 'NSGA-II_rank: 1', 'change: 0.2429060659113936', 'is_elite: False']\n", + "Id: 13_75 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_89', '12_53'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_75', 'origin': '12_89~CUW~12_53#MGNP'} Metrics: ['ELUC: -15.806849518357986', 'NSGA-II_crowding_distance: 0.1915520302978721', 'NSGA-II_rank: 1', 'change: 0.25240649066124904', 'is_elite: False']\n", + "Id: 14_34 Identity: {'ancestor_count': 10, 'ancestor_ids': ['13_45', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_34', 'origin': '13_45~CUW~13_92#MGNP'} Metrics: ['ELUC: -16.620557906464906', 'NSGA-II_crowding_distance: 0.2077707992488928', 'NSGA-II_rank: 1', 'change: 0.2840018236813721', 'is_elite: False']\n", + "Id: 14_16 Identity: {'ancestor_count': 8, 'ancestor_ids': ['13_76', '2_49'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_16', 'origin': '13_76~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.971768057324507', 'NSGA-II_crowding_distance: 0.35602075449028003', 'NSGA-II_rank: 3', 'change: 0.29771577336559185', 'is_elite: False']\n", + "Id: 14_35 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_35', 'origin': '12_23~CUW~13_92#MGNP'} Metrics: ['ELUC: -17.034319117126863', 'NSGA-II_crowding_distance: 0.20157571609222324', 'NSGA-II_rank: 2', 'change: 0.29531446890422697', 'is_elite: False']\n", + "Id: 14_42 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_34', '13_34'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_42', 'origin': '13_34~CUW~13_34#MGNP'} Metrics: ['ELUC: -17.167885088648802', 'NSGA-II_crowding_distance: 0.1086744993864027', 'NSGA-II_rank: 1', 'change: 0.291303473799314', 'is_elite: False']\n", + "Id: 14_66 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_66', 'origin': '11_18~CUW~13_92#MGNP'} Metrics: ['ELUC: -17.224473492080207', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.305539736361473', 'is_elite: False']\n", + "Id: 14_62 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '13_69'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_62', 'origin': '2_49~CUW~13_69#MGNP'} Metrics: ['ELUC: -17.4967940523127', 'NSGA-II_crowding_distance: 0.0632614876383978', 'NSGA-II_rank: 1', 'change: 0.3015578749960566', 'is_elite: False']\n", + "Id: 14_100 Identity: {'ancestor_count': 8, 'ancestor_ids': ['13_68', '2_49'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_100', 'origin': '13_68~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.587784345872436', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3029605014665315', 'is_elite: False']\n", + "Id: 14_51 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_92', '13_36'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_51', 'origin': '13_92~CUW~13_36#MGNP'} Metrics: ['ELUC: -17.594371710152576', 'NSGA-II_crowding_distance: 0.010623037715429875', 'NSGA-II_rank: 1', 'change: 0.3029416824923015', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 13_92 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '12_98'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_92', 'origin': '2_49~CUW~12_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 14_28 Identity: {'ancestor_count': 4, 'ancestor_ids': ['13_92', '13_92'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_28', 'origin': '13_92~CUW~13_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 14_73 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_92', '13_33'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_73', 'origin': '13_92~CUW~13_33#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 14_88 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_33', '2_49'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_88', 'origin': '13_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 14.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 15...:\n", + "PopulationResponse:\n", + " Generation: 15\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/15/20240219-212835\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 15 and asking ESP for generation 16...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 15 data persisted.\n", + "Evaluated candidates:\n", + "Id: 15_70 Identity: {'ancestor_count': 11, 'ancestor_ids': ['1_1', '14_34'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_70', 'origin': '1_1~CUW~14_34#MGNP'} Metrics: ['ELUC: 23.818592403137103', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3038022245543597', 'is_elite: False']\n", + "Id: 15_34 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_34', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 23.710722243358646', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.30352800449833667', 'is_elite: False']\n", + "Id: 15_96 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_34', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_96', 'origin': '14_34~CUW~14_18#MGNP'} Metrics: ['ELUC: 23.25485968625113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3053735503946561', 'is_elite: False']\n", + "Id: 15_99 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '14_88'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_99', 'origin': '14_18~CUW~14_88#MGNP'} Metrics: ['ELUC: 17.608821828143483', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3001432385920676', 'is_elite: False']\n", + "Id: 15_22 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_22', 'origin': '2_49~CUW~14_18#MGNP'} Metrics: ['ELUC: 13.993529997779852', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27748167771970794', 'is_elite: False']\n", + "Id: 15_73 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_68', '14_34'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_73', 'origin': '14_68~CUW~14_34#MGNP'} Metrics: ['ELUC: 13.537820982752734', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2641635704998322', 'is_elite: False']\n", + "Id: 15_63 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_34', '14_96'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_63', 'origin': '14_34~CUW~14_96#MGNP'} Metrics: ['ELUC: 11.379484403157962', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25527595372286793', 'is_elite: False']\n", + "Id: 15_14 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_34', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_14', 'origin': '14_34~CUW~14_64#MGNP'} Metrics: ['ELUC: 10.38946423580157', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2576404655317613', 'is_elite: False']\n", + "Id: 15_13 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_13', 'origin': '13_69~CUW~1_1#MGNP'} Metrics: ['ELUC: 7.373975477637744', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.15662692794149755', 'is_elite: False']\n", + "Id: 15_86 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_86', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 5.391439684077844', 'NSGA-II_crowding_distance: 1.2019692370910044', 'NSGA-II_rank: 8', 'change: 0.22588798710476832', 'is_elite: False']\n", + "Id: 15_98 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_98', 'origin': '14_68~CUW~1_1#MGNP'} Metrics: ['ELUC: 4.129513085216185', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.14403524841136298', 'is_elite: False']\n", + "Id: 15_85 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '2_49'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_85', 'origin': '12_23~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.976812630371209', 'NSGA-II_crowding_distance: 1.9140975805148686', 'NSGA-II_rank: 11', 'change: 0.2908502463217893', 'is_elite: False']\n", + "Id: 15_50 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '12_87'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_50', 'origin': '14_18~CUW~12_87#MGNP'} Metrics: ['ELUC: 2.583872856557732', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.1035401917951029', 'is_elite: False']\n", + "Id: 15_41 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_23', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_41', 'origin': '12_23~CUW~14_68#MGNP'} Metrics: ['ELUC: 2.529079284471704', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09729036733312908', 'is_elite: False']\n", + "Id: 15_45 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_34', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_45', 'origin': '14_34~CUW~14_18#MGNP'} Metrics: ['ELUC: 1.0774326833791257', 'NSGA-II_crowding_distance: 0.8269267144966788', 'NSGA-II_rank: 11', 'change: 0.3151296131986506', 'is_elite: False']\n", + "Id: 15_75 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '14_34'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_75', 'origin': '13_75~CUW~14_34#MGNP'} Metrics: ['ELUC: 0.9606160226433569', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3182676542546243', 'is_elite: False']\n", + "Id: 15_80 Identity: {'ancestor_count': 13, 'ancestor_ids': ['12_23', '14_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_80', 'origin': '12_23~CUW~14_23#MGNP'} Metrics: ['ELUC: 0.7897809311933419', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.052751723511025986', 'is_elite: False']\n", + "Id: 15_25 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '11_39'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_25', 'origin': '13_36~CUW~11_39#MGNP'} Metrics: ['ELUC: 0.7127585606876281', 'NSGA-II_crowding_distance: 0.3715144030120082', 'NSGA-II_rank: 5', 'change: 0.10253643711429179', 'is_elite: False']\n", + "Id: 15_46 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_55', '13_36'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_46', 'origin': '14_55~CUW~13_36#MGNP'} Metrics: ['ELUC: 0.1368838947287407', 'NSGA-II_crowding_distance: 0.268013145176593', 'NSGA-II_rank: 3', 'change: 0.06384888391506256', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 15_19 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_19', 'origin': '11_39~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.2690019041925553', 'NSGA-II_crowding_distance: 0.4676111921066867', 'NSGA-II_rank: 5', 'change: 0.1304872221016153', 'is_elite: False']\n", + "Id: 15_77 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_53', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_77', 'origin': '14_53~CUW~14_18#MGNP'} Metrics: ['ELUC: -1.1578849610396649', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08585971601970153', 'is_elite: False']\n", + "Id: 15_95 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_23', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_95', 'origin': '12_23~CUW~14_68#MGNP'} Metrics: ['ELUC: -1.2074414785435015', 'NSGA-II_crowding_distance: 0.22830337531018752', 'NSGA-II_rank: 3', 'change: 0.08027893128864888', 'is_elite: False']\n", + "Id: 12_23 Identity: {'ancestor_count': 6, 'ancestor_ids': ['11_75', '1_1'], 'birth_generation': 12, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '12_23', 'origin': '11_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2534769974134168', 'NSGA-II_crowding_distance: 0.1734626042353304', 'NSGA-II_rank: 1', 'change: 0.03000838202835237', 'is_elite: False']\n", + "Id: 15_43 Identity: {'ancestor_count': 12, 'ancestor_ids': ['1_1', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_43', 'origin': '1_1~CUW~14_18#MGNP'} Metrics: ['ELUC: -1.2824145909418516', 'NSGA-II_crowding_distance: 0.2388167463108286', 'NSGA-II_rank: 3', 'change: 0.09177694587005769', 'is_elite: False']\n", + "Id: 15_78 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_78', 'origin': '12_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2979516506139455', 'NSGA-II_crowding_distance: 0.09129799914777739', 'NSGA-II_rank: 1', 'change: 0.03462884686369317', 'is_elite: False']\n", + "Id: 15_17 Identity: {'ancestor_count': 8, 'ancestor_ids': ['12_23', '14_96'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_17', 'origin': '12_23~CUW~14_96#MGNP'} Metrics: ['ELUC: -2.1972802029999374', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.042176123079217115', 'is_elite: False']\n", + "Id: 15_91 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_87', '12_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_91', 'origin': '12_87~CUW~12_23#MGNP'} Metrics: ['ELUC: -2.2434192601738303', 'NSGA-II_crowding_distance: 0.12282450972712852', 'NSGA-II_rank: 1', 'change: 0.04045004507346226', 'is_elite: False']\n", + "Id: 15_24 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '14_55'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_24', 'origin': '14_18~CUW~14_55#MGNP'} Metrics: ['ELUC: -2.336149703493393', 'NSGA-II_crowding_distance: 0.5020197511472627', 'NSGA-II_rank: 3', 'change: 0.11514692355185506', 'is_elite: False']\n", + "Id: 15_71 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_71', 'origin': '2_49~CUW~14_18#MGNP'} Metrics: ['ELUC: -2.361932513091952', 'NSGA-II_crowding_distance: 1.0485562742811712', 'NSGA-II_rank: 8', 'change: 0.23960323796486022', 'is_elite: False']\n", + "Id: 15_39 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_39', 'origin': '12_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.481672851262548', 'NSGA-II_crowding_distance: 0.08691317525868329', 'NSGA-II_rank: 1', 'change: 0.051188829785220054', 'is_elite: False']\n", + "Id: 15_57 Identity: {'ancestor_count': 10, 'ancestor_ids': ['2_49', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_57', 'origin': '2_49~CUW~14_64#MGNP'} Metrics: ['ELUC: -2.813128578922146', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.26690067386273963', 'is_elite: False']\n", + "Id: 15_37 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '14_96'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_37', 'origin': '1_1~CUW~14_96#MGNP'} Metrics: ['ELUC: -2.8273372221253013', 'NSGA-II_crowding_distance: 0.0647114364105213', 'NSGA-II_rank: 1', 'change: 0.05647373189697619', 'is_elite: False']\n", + "Id: 15_51 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_53', '14_55'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_51', 'origin': '14_53~CUW~14_55#MGNP'} Metrics: ['ELUC: -2.9208374689125898', 'NSGA-II_crowding_distance: 0.5801941609082457', 'NSGA-II_rank: 2', 'change: 0.07956968451874499', 'is_elite: False']\n", + "Id: 14_96 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '12_87'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_96', 'origin': '1_1~CUW~12_87#MGNP'} Metrics: ['ELUC: -2.930706679732033', 'NSGA-II_crowding_distance: 0.1571165413683811', 'NSGA-II_rank: 1', 'change: 0.06287703782825925', 'is_elite: False']\n", + "Id: 15_15 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_15', 'origin': '1_1~CUW~14_64#MGNP'} Metrics: ['ELUC: -3.1019823424956785', 'NSGA-II_crowding_distance: 0.36867187060908807', 'NSGA-II_rank: 5', 'change: 0.1404139188949489', 'is_elite: False']\n", + "Id: 15_35 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '12_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_35', 'origin': '13_75~CUW~12_23#MGNP'} Metrics: ['ELUC: -3.7426641189012773', 'NSGA-II_crowding_distance: 0.5398922401029175', 'NSGA-II_rank: 5', 'change: 0.15413498875181786', 'is_elite: False']\n", + "Id: 15_18 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '12_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_18', 'origin': '14_68~CUW~12_23#MGNP'} Metrics: ['ELUC: -3.845409800768202', 'NSGA-II_crowding_distance: 0.6060762350040358', 'NSGA-II_rank: 4', 'change: 0.13032629262357653', 'is_elite: False']\n", + "Id: 15_21 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_23', '13_36'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_21', 'origin': '12_23~CUW~13_36#MGNP'} Metrics: ['ELUC: -4.034900818019752', 'NSGA-II_crowding_distance: 0.37849233980048036', 'NSGA-II_rank: 1', 'change: 0.08286108004603764', 'is_elite: True']\n", + "Id: 15_90 Identity: {'ancestor_count': 12, 'ancestor_ids': ['1_1', '13_75'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_90', 'origin': '1_1~CUW~13_75#MGNP'} Metrics: ['ELUC: -4.0654031961106565', 'NSGA-II_crowding_distance: 1.1214936255675299', 'NSGA-II_rank: 6', 'change: 0.16653504577833864', 'is_elite: False']\n", + "Id: 15_11 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_36', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_11', 'origin': '13_36~CUW~14_18#MGNP'} Metrics: ['ELUC: -5.641044403123452', 'NSGA-II_crowding_distance: 0.3659841700010064', 'NSGA-II_rank: 4', 'change: 0.13162706429373086', 'is_elite: False']\n", + "Id: 15_76 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_76', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.776044321561461', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30927650289949626', 'is_elite: False']\n", + "Id: 13_36 Identity: {'ancestor_count': 10, 'ancestor_ids': ['12_71', '11_18'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_36', 'origin': '12_71~CUW~11_18#MGNP'} Metrics: ['ELUC: -5.971034032582094', 'NSGA-II_crowding_distance: 0.4342454811357095', 'NSGA-II_rank: 2', 'change: 0.11722743399293699', 'is_elite: False']\n", + "Id: 15_12 Identity: {'ancestor_count': 8, 'ancestor_ids': ['2_49', '14_96'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_12', 'origin': '2_49~CUW~14_96#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 15_64 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_64', 'origin': '14_18~CUW~14_18#MGNP'} Metrics: ['ELUC: -6.151926178043534', 'NSGA-II_crowding_distance: 0.5419361436471523', 'NSGA-II_rank: 3', 'change: 0.12541395419785784', 'is_elite: False']\n", + "Id: 14_18 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '13_36'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_18', 'origin': '13_36~CUW~13_36#MGNP'} Metrics: ['ELUC: -6.411884118709213', 'NSGA-II_crowding_distance: 0.3079588103962878', 'NSGA-II_rank: 2', 'change: 0.12312570585009329', 'is_elite: False']\n", + "Id: 15_47 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '14_55'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_47', 'origin': '14_18~CUW~14_55#MGNP'} Metrics: ['ELUC: -6.691556990010648', 'NSGA-II_crowding_distance: 0.5347888592093166', 'NSGA-II_rank: 1', 'change: 0.11198792834699166', 'is_elite: True']\n", + "Id: 15_55 Identity: {'ancestor_count': 12, 'ancestor_ids': ['12_23', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_55', 'origin': '12_23~CUW~14_18#MGNP'} Metrics: ['ELUC: -6.8101546769506935', 'NSGA-II_crowding_distance: 0.5619290746463433', 'NSGA-II_rank: 6', 'change: 0.17750821447400528', 'is_elite: False']\n", + "Id: 15_38 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_34', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_38', 'origin': '14_34~CUW~14_68#MGNP'} Metrics: ['ELUC: -7.148988825165189', 'NSGA-II_crowding_distance: 0.5615624171527265', 'NSGA-II_rank: 8', 'change: 0.2618014308643782', 'is_elite: False']\n", + "Id: 15_40 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_64', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_40', 'origin': '14_64~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.278283885235039', 'NSGA-II_crowding_distance: 0.248465386804832', 'NSGA-II_rank: 4', 'change: 0.14586251612703585', 'is_elite: False']\n", + "Id: 15_54 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_36', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_54', 'origin': '13_36~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.5699171324689285', 'NSGA-II_crowding_distance: 0.16186268771686332', 'NSGA-II_rank: 4', 'change: 0.14887281532022237', 'is_elite: False']\n", + "Id: 15_49 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_49', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.185638162736979', 'NSGA-II_crowding_distance: 0.33799627814485983', 'NSGA-II_rank: 8', 'change: 0.2668792539177539', 'is_elite: False']\n", + "Id: 15_16 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '14_53'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_16', 'origin': '14_18~CUW~14_53#MGNP'} Metrics: ['ELUC: -8.277417646155298', 'NSGA-II_crowding_distance: 0.5144567754486638', 'NSGA-II_rank: 3', 'change: 0.14058479207203234', 'is_elite: False']\n", + "Id: 15_74 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_88', '14_34'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_74', 'origin': '14_88~CUW~14_34#MGNP'} Metrics: ['ELUC: -8.386346605532895', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2986558540781234', 'is_elite: False']\n", + "Id: 15_92 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_88', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_92', 'origin': '14_88~CUW~14_18#MGNP'} Metrics: ['ELUC: -8.626622835328764', 'NSGA-II_crowding_distance: 1.7611121555657459', 'NSGA-II_rank: 7', 'change: 0.20557911299930237', 'is_elite: False']\n", + "Id: 15_69 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_42', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_69', 'origin': '14_42~CUW~14_68#MGNP'} Metrics: ['ELUC: -8.821396651794531', 'NSGA-II_crowding_distance: 0.87850637443247', 'NSGA-II_rank: 6', 'change: 0.2029748097177496', 'is_elite: False']\n", + "Id: 15_83 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_96', '13_36'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_83', 'origin': '14_96~CUW~13_36#MGNP'} Metrics: ['ELUC: -8.928622895754204', 'NSGA-II_crowding_distance: 0.2642991982319981', 'NSGA-II_rank: 4', 'change: 0.15053102578626465', 'is_elite: False']\n", + "Id: 15_59 Identity: {'ancestor_count': 13, 'ancestor_ids': ['13_36', '14_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_59', 'origin': '13_36~CUW~14_23#MGNP'} Metrics: ['ELUC: -8.980524570113644', 'NSGA-II_crowding_distance: 0.6132546652468126', 'NSGA-II_rank: 5', 'change: 0.1644871414580655', 'is_elite: False']\n", + "Id: 15_68 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_34', '13_36'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_68', 'origin': '14_34~CUW~13_36#MGNP'} Metrics: ['ELUC: -9.283582124338377', 'NSGA-II_crowding_distance: 0.7416946556211904', 'NSGA-II_rank: 7', 'change: 0.287870740377181', 'is_elite: False']\n", + "Id: 15_97 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_64', '14_96'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_97', 'origin': '14_64~CUW~14_96#MGNP'} Metrics: ['ELUC: -9.407564897466106', 'NSGA-II_crowding_distance: 0.31537266139664333', 'NSGA-II_rank: 5', 'change: 0.19498129287998142', 'is_elite: False']\n", + "Id: 15_52 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_96', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_52', 'origin': '14_96~CUW~14_64#MGNP'} Metrics: ['ELUC: -9.420763036705361', 'NSGA-II_crowding_distance: 0.4223183736177385', 'NSGA-II_rank: 2', 'change: 0.12968337864251592', 'is_elite: False']\n", + "Id: 15_58 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_34', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_58', 'origin': '14_34~CUW~14_18#MGNP'} Metrics: ['ELUC: -9.771936150106', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.32467821168013183', 'is_elite: False']\n", + "Id: 15_29 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '12_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_29', 'origin': '14_68~CUW~12_23#MGNP'} Metrics: ['ELUC: -10.143889180449424', 'NSGA-II_crowding_distance: 0.19985162123763192', 'NSGA-II_rank: 4', 'change: 0.15851021090166859', 'is_elite: False']\n", + "Id: 15_87 Identity: {'ancestor_count': 13, 'ancestor_ids': ['14_89', '14_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_87', 'origin': '14_89~CUW~14_23#MGNP'} Metrics: ['ELUC: -10.306772460001032', 'NSGA-II_crowding_distance: 0.5572091570562903', 'NSGA-II_rank: 5', 'change: 0.20665692554412793', 'is_elite: False']\n", + "Id: 15_94 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_94', 'origin': '14_68~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.478432766723543', 'NSGA-II_crowding_distance: 0.557816573492529', 'NSGA-II_rank: 4', 'change: 0.1644303407174386', 'is_elite: False']\n", + "Id: 15_30 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_30', 'origin': '14_68~CUW~14_68#MGNP'} Metrics: ['ELUC: -10.730205278761504', 'NSGA-II_crowding_distance: 0.3057785322216499', 'NSGA-II_rank: 1', 'change: 0.12880877755264608', 'is_elite: True']\n", + "Id: 14_68 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_18', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_68', 'origin': '11_18~CUW~11_18#MGNP'} Metrics: ['ELUC: -10.870847660171393', 'NSGA-II_crowding_distance: 0.1238169504731231', 'NSGA-II_rank: 1', 'change: 0.13230157729994926', 'is_elite: False']\n", + "Id: 15_66 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_66', 'origin': '14_68~CUW~14_64#MGNP'} Metrics: ['ELUC: -10.980945027129827', 'NSGA-II_crowding_distance: 0.20611967722861366', 'NSGA-II_rank: 2', 'change: 0.14326778706327356', 'is_elite: False']\n", + "Id: 15_42 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_34', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_42', 'origin': '14_34~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.994545610672793', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2756955928976447', 'is_elite: False']\n", + "Id: 15_79 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '13_69'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_79', 'origin': '2_49~CUW~13_69#MGNP'} Metrics: ['ELUC: -11.290392251000204', 'NSGA-II_crowding_distance: 0.5148251886934923', 'NSGA-II_rank: 5', 'change: 0.27562827731500755', 'is_elite: False']\n", + "Id: 15_20 Identity: {'ancestor_count': 12, 'ancestor_ids': ['12_23', '14_88'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_20', 'origin': '12_23~CUW~14_88#MGNP'} Metrics: ['ELUC: -11.378191943456931', 'NSGA-II_crowding_distance: 0.6759553433132992', 'NSGA-II_rank: 4', 'change: 0.24885550716547922', 'is_elite: False']\n", + "Id: 15_33 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_33', 'origin': '14_68~CUW~14_64#MGNP'} Metrics: ['ELUC: -11.448925501969967', 'NSGA-II_crowding_distance: 0.06277791988523507', 'NSGA-II_rank: 2', 'change: 0.1433342589665521', 'is_elite: False']\n", + "Id: 15_93 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_34', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_93', 'origin': '14_34~CUW~14_64#MGNP'} Metrics: ['ELUC: -11.601627851826693', 'NSGA-II_crowding_distance: 0.32334260646660506', 'NSGA-II_rank: 4', 'change: 0.28012143032132797', 'is_elite: False']\n", + "Id: 15_48 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '14_88'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_48', 'origin': '13_69~CUW~14_88#MGNP'} Metrics: ['ELUC: -11.653397538121121', 'NSGA-II_crowding_distance: 0.08934990407580062', 'NSGA-II_rank: 5', 'change: 0.28641039405290364', 'is_elite: False']\n", + "Id: 15_53 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_88', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_53', 'origin': '14_88~CUW~14_68#MGNP'} Metrics: ['ELUC: -11.702771194217869', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2870870884410349', 'is_elite: False']\n", + "Id: 15_88 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_64', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_88', 'origin': '14_64~CUW~14_64#MGNP'} Metrics: ['ELUC: -11.741230721479212', 'NSGA-II_crowding_distance: 0.6496444059941247', 'NSGA-II_rank: 3', 'change: 0.15036737877760495', 'is_elite: False']\n", + "Id: 15_28 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_28', 'origin': '14_68~CUW~14_64#MGNP'} Metrics: ['ELUC: -11.7726066402315', 'NSGA-II_crowding_distance: 0.06020519440214889', 'NSGA-II_rank: 2', 'change: 0.14413332444176882', 'is_elite: False']\n", + "Id: 14_64 Identity: {'ancestor_count': 9, 'ancestor_ids': ['11_39', '11_18'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_64', 'origin': '11_39~CUW~11_18#MGNP'} Metrics: ['ELUC: -11.930104070715586', 'NSGA-II_crowding_distance: 0.0532557654372789', 'NSGA-II_rank: 2', 'change: 0.14942659429306818', 'is_elite: False']\n", + "Id: 15_23 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_64', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_23', 'origin': '14_64~CUW~14_64#MGNP'} Metrics: ['ELUC: -12.06134195246652', 'NSGA-II_crowding_distance: 0.08382108649688269', 'NSGA-II_rank: 2', 'change: 0.15211346502194506', 'is_elite: False']\n", + "Id: 15_61 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_64', '13_69'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_61', 'origin': '14_64~CUW~13_69#MGNP'} Metrics: ['ELUC: -12.073450675839043', 'NSGA-II_crowding_distance: 0.1987644013563059', 'NSGA-II_rank: 1', 'change: 0.14295770790198734', 'is_elite: False']\n", + "Id: 15_44 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_64', '11_39'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_44', 'origin': '14_64~CUW~11_39#MGNP'} Metrics: ['ELUC: -12.196530691433077', 'NSGA-II_crowding_distance: 0.31472748984202714', 'NSGA-II_rank: 2', 'change: 0.16554541321133523', 'is_elite: False']\n", + "Id: 15_65 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_65', 'origin': '13_75~CUW~14_64#MGNP'} Metrics: ['ELUC: -12.67162585524164', 'NSGA-II_crowding_distance: 0.2758087347193783', 'NSGA-II_rank: 1', 'change: 0.161048684163051', 'is_elite: True']\n", + "Id: 15_84 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_89', '1_1'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_84', 'origin': '14_89~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.996561117031675', 'NSGA-II_crowding_distance: 0.65811388053841', 'NSGA-II_rank: 3', 'change: 0.20924623688975186', 'is_elite: False']\n", + "Id: 15_27 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '2_49'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_27', 'origin': '14_68~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.083478963340323', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28471964019954277', 'is_elite: False']\n", + "Id: 15_62 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_96', '14_34'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_62', 'origin': '14_96~CUW~14_34#MGNP'} Metrics: ['ELUC: -13.128389630977011', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.27382597841183576', 'is_elite: False']\n", + "Id: 15_67 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_68', '13_69'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_67', 'origin': '14_68~CUW~13_69#MGNP'} Metrics: ['ELUC: -13.767077972265898', 'NSGA-II_crowding_distance: 0.6812062534579133', 'NSGA-II_rank: 2', 'change: 0.19928559328333575', 'is_elite: False']\n", + "Id: 15_31 Identity: {'ancestor_count': 13, 'ancestor_ids': ['13_69', '14_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_31', 'origin': '13_69~CUW~14_23#MGNP'} Metrics: ['ELUC: -14.059017513721951', 'NSGA-II_crowding_distance: 0.23658655607389933', 'NSGA-II_rank: 1', 'change: 0.1915572066448896', 'is_elite: True']\n", + "Id: 13_69 Identity: {'ancestor_count': 11, 'ancestor_ids': ['9_92', '12_76'], 'birth_generation': 13, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '13_69', 'origin': '9_92~CUW~12_76#MGNP'} Metrics: ['ELUC: -14.270093310450855', 'NSGA-II_crowding_distance: 0.12075102131299167', 'NSGA-II_rank: 1', 'change: 0.20451435470454712', 'is_elite: False']\n", + "Id: 15_56 Identity: {'ancestor_count': 13, 'ancestor_ids': ['14_49', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_56', 'origin': '14_49~CUW~14_64#MGNP'} Metrics: ['ELUC: -14.567465822408847', 'NSGA-II_crowding_distance: 0.09064639137451949', 'NSGA-II_rank: 1', 'change: 0.21895809590660587', 'is_elite: False']\n", + "Id: 15_100 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_34', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_100', 'origin': '14_34~CUW~14_68#MGNP'} Metrics: ['ELUC: -14.709139146035367', 'NSGA-II_crowding_distance: 0.5103131476119636', 'NSGA-II_rank: 2', 'change: 0.2899668715145529', 'is_elite: False']\n", + "Id: 15_26 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '13_69'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_26', 'origin': '13_75~CUW~13_69#MGNP'} Metrics: ['ELUC: -14.80875698938803', 'NSGA-II_crowding_distance: 0.14675054584825814', 'NSGA-II_rank: 1', 'change: 0.2224199291486311', 'is_elite: False']\n", + "Id: 15_36 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '2_49'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_36', 'origin': '14_68~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.536262228583267', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2946340243075726', 'is_elite: False']\n", + "Id: 15_81 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_81', 'origin': '13_75~CUW~14_68#MGNP'} Metrics: ['ELUC: -15.723820826513172', 'NSGA-II_crowding_distance: 0.42138461016277307', 'NSGA-II_rank: 1', 'change: 0.24312148758869404', 'is_elite: True']\n", + "Id: 15_32 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_32', 'origin': '2_49~CUW~14_18#MGNP'} Metrics: ['ELUC: -17.486781673961662', 'NSGA-II_crowding_distance: 0.3072758320054456', 'NSGA-II_rank: 1', 'change: 0.30270480182257037', 'is_elite: True']\n", + "Id: 15_89 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_88', '13_36'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_89', 'origin': '14_88~CUW~13_36#MGNP'} Metrics: ['ELUC: -17.597183973186343', 'NSGA-II_crowding_distance: 0.00734861863739169', 'NSGA-II_rank: 1', 'change: 0.3030141981151573', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 14_88 Identity: {'ancestor_count': 11, 'ancestor_ids': ['13_33', '2_49'], 'birth_generation': 14, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '14_88', 'origin': '13_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 15_60 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_88', '2_49'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_60', 'origin': '14_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 15_72 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_88', '14_88'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_72', 'origin': '14_88~CUW~14_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 15_82 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '14_34'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_82', 'origin': '14_18~CUW~14_34#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 15.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 16...:\n", + "PopulationResponse:\n", + " Generation: 16\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/16/20240219-213544\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 16 and asking ESP for generation 17...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 16 data persisted.\n", + "Evaluated candidates:\n", + "Id: 16_13 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_32', '15_47'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_13', 'origin': '15_32~CUW~15_47#MGNP'} Metrics: ['ELUC: 23.832421464326053', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3037860327445153', 'is_elite: False']\n", + "Id: 16_57 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_65', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_57', 'origin': '15_65~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.82379713188398', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.30377685144317806', 'is_elite: False']\n", + "Id: 16_40 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_30', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_40', 'origin': '15_30~CUW~2_49#MGNP'} Metrics: ['ELUC: 21.255031647466463', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2900103343439323', 'is_elite: False']\n", + "Id: 16_86 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_32', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_86', 'origin': '15_32~CUW~1_1#MGNP'} Metrics: ['ELUC: 14.291437200601958', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2712358725498669', 'is_elite: False']\n", + "Id: 16_46 Identity: {'ancestor_count': 13, 'ancestor_ids': ['2_49', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_46', 'origin': '2_49~CUW~15_81#MGNP'} Metrics: ['ELUC: 8.810091830522884', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23850455924994374', 'is_elite: False']\n", + "Id: 16_25 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_61', '15_82'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_25', 'origin': '15_61~CUW~15_82#MGNP'} Metrics: ['ELUC: 6.385450268019058', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2286552868656776', 'is_elite: False']\n", + "Id: 16_19 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_32', '15_61'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_19', 'origin': '15_32~CUW~15_61#MGNP'} Metrics: ['ELUC: 4.934916593181972', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.3343809747211195', 'is_elite: False']\n", + "Id: 16_74 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_91', '15_30'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_74', 'origin': '15_91~CUW~15_30#MGNP'} Metrics: ['ELUC: 4.010035020686865', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1544066027714326', 'is_elite: False']\n", + "Id: 16_43 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_43', 'origin': '15_31~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.21947481318206', 'NSGA-II_crowding_distance: 1.5372085013530783', 'NSGA-II_rank: 9', 'change: 0.25359729842879924', 'is_elite: False']\n", + "Id: 16_66 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '14_96'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_66', 'origin': '13_69~CUW~14_96#MGNP'} Metrics: ['ELUC: 2.895192017612156', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.12196127353775621', 'is_elite: False']\n", + "Id: 16_64 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_91', '15_65'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_64', 'origin': '15_91~CUW~15_65#MGNP'} Metrics: ['ELUC: 2.5579099820989386', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.09603530723665506', 'is_elite: False']\n", + "Id: 16_60 Identity: {'ancestor_count': 13, 'ancestor_ids': ['12_23', '15_32'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_60', 'origin': '12_23~CUW~15_32#MGNP'} Metrics: ['ELUC: 2.52591248677403', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3516776242363735', 'is_elite: False']\n", + "Id: 16_71 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_82', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_71', 'origin': '15_82~CUW~15_81#MGNP'} Metrics: ['ELUC: 1.990433369220199', 'NSGA-II_crowding_distance: 0.9203682811757987', 'NSGA-II_rank: 7', 'change: 0.17092643507249294', 'is_elite: False']\n", + "Id: 16_89 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_32', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_89', 'origin': '15_32~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.8890340470182387', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26219009196504894', 'is_elite: False']\n", + "Id: 16_99 Identity: {'ancestor_count': 12, 'ancestor_ids': ['15_21', '14_68'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_99', 'origin': '15_21~CUW~14_68#MGNP'} Metrics: ['ELUC: 1.4096504388447815', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11583139834027913', 'is_elite: False']\n", + "Id: 16_62 Identity: {'ancestor_count': 8, 'ancestor_ids': ['14_96', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_62', 'origin': '14_96~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.208702162514545', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.05193410394047628', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 16_56 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_56', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.26384075790866507', 'NSGA-II_crowding_distance: 0.14393689703935733', 'NSGA-II_rank: 1', 'change: 0.026487389101048964', 'is_elite: False']\n", + "Id: 16_41 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_21', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_41', 'origin': '15_21~CUW~15_81#MGNP'} Metrics: ['ELUC: -0.3525992107504708', 'NSGA-II_crowding_distance: 0.3766730953535709', 'NSGA-II_rank: 5', 'change: 0.12823510403332647', 'is_elite: False']\n", + "Id: 16_72 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_69', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_72', 'origin': '13_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.9991512155881943', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 16_85 Identity: {'ancestor_count': 8, 'ancestor_ids': ['1_1', '15_39'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_85', 'origin': '1_1~CUW~15_39#MGNP'} Metrics: ['ELUC: -0.5691152621923276', 'NSGA-II_crowding_distance: 0.14746660345127197', 'NSGA-II_rank: 1', 'change: 0.038187611950768384', 'is_elite: False']\n", + "Id: 16_29 Identity: {'ancestor_count': 7, 'ancestor_ids': ['12_23', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_29', 'origin': '12_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6583332199701809', 'NSGA-II_crowding_distance: 0.0983919526170495', 'NSGA-II_rank: 2', 'change: 0.05455390958690029', 'is_elite: False']\n", + "Id: 16_38 Identity: {'ancestor_count': 12, 'ancestor_ids': ['15_21', '12_23'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_38', 'origin': '15_21~CUW~12_23#MGNP'} Metrics: ['ELUC: -0.793080948933317', 'NSGA-II_crowding_distance: 0.05386099658939593', 'NSGA-II_rank: 2', 'change: 0.061723271511578165', 'is_elite: False']\n", + "Id: 16_22 Identity: {'ancestor_count': 12, 'ancestor_ids': ['15_21', '14_96'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_22', 'origin': '15_21~CUW~14_96#MGNP'} Metrics: ['ELUC: -1.0310907420912176', 'NSGA-II_crowding_distance: 0.067128841007572', 'NSGA-II_rank: 2', 'change: 0.06248952354664967', 'is_elite: False']\n", + "Id: 16_17 Identity: {'ancestor_count': 12, 'ancestor_ids': ['1_1', '15_21'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_17', 'origin': '1_1~CUW~15_21#MGNP'} Metrics: ['ELUC: -1.4280128207859901', 'NSGA-II_crowding_distance: 0.1580744213429131', 'NSGA-II_rank: 2', 'change: 0.06911427417574798', 'is_elite: False']\n", + "Id: 16_45 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_61', '15_91'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_45', 'origin': '15_61~CUW~15_91#MGNP'} Metrics: ['ELUC: -1.5189745046144425', 'NSGA-II_crowding_distance: 0.12919149737800936', 'NSGA-II_rank: 1', 'change: 0.04918813071170537', 'is_elite: False']\n", + "Id: 16_24 Identity: {'ancestor_count': 8, 'ancestor_ids': ['14_96', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_24', 'origin': '14_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8499730369784853', 'NSGA-II_crowding_distance: 0.2001907919082868', 'NSGA-II_rank: 1', 'change: 0.054998924497522375', 'is_elite: True']\n", + "Id: 16_83 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_21', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_83', 'origin': '15_21~CUW~15_81#MGNP'} Metrics: ['ELUC: -2.0046737000915447', 'NSGA-II_crowding_distance: 0.6186047949630222', 'NSGA-II_rank: 5', 'change: 0.13106399597361817', 'is_elite: False']\n", + "Id: 16_32 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_65', '15_21'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_32', 'origin': '15_65~CUW~15_21#MGNP'} Metrics: ['ELUC: -2.230799483218654', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.10693792288148775', 'is_elite: False']\n", + "Id: 16_68 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_61', '14_96'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_68', 'origin': '15_61~CUW~14_96#MGNP'} Metrics: ['ELUC: -2.2943189696321444', 'NSGA-II_crowding_distance: 1.0617116295589852', 'NSGA-II_rank: 4', 'change: 0.13401732915369372', 'is_elite: False']\n", + "Id: 16_69 Identity: {'ancestor_count': 13, 'ancestor_ids': ['2_49', '15_47'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_69', 'origin': '2_49~CUW~15_47#MGNP'} Metrics: ['ELUC: -2.3064493428715127', 'NSGA-II_crowding_distance: 1.0032301077271453', 'NSGA-II_rank: 9', 'change: 0.2576977439948293', 'is_elite: False']\n", + "Id: 16_58 Identity: {'ancestor_count': 12, 'ancestor_ids': ['15_21', '15_78'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_58', 'origin': '15_21~CUW~15_78#MGNP'} Metrics: ['ELUC: -2.84911985175339', 'NSGA-II_crowding_distance: 0.13702451026834206', 'NSGA-II_rank: 2', 'change: 0.07515617721479413', 'is_elite: False']\n", + "Id: 16_27 Identity: {'ancestor_count': 12, 'ancestor_ids': ['15_21', '15_78'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_27', 'origin': '15_21~CUW~15_78#MGNP'} Metrics: ['ELUC: -3.044210923567008', 'NSGA-II_crowding_distance: 0.10086462529399406', 'NSGA-II_rank: 2', 'change: 0.07950338608811437', 'is_elite: False']\n", + "Id: 16_48 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_82', '15_30'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_48', 'origin': '15_82~CUW~15_30#MGNP'} Metrics: ['ELUC: -3.280687885557365', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.25247466230564697', 'is_elite: False']\n", + "Id: 16_95 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_61', '15_47'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_95', 'origin': '15_61~CUW~15_47#MGNP'} Metrics: ['ELUC: -3.630478993628068', 'NSGA-II_crowding_distance: 0.6210456594708778', 'NSGA-II_rank: 3', 'change: 0.10403524722202584', 'is_elite: False']\n", + "Id: 16_65 Identity: {'ancestor_count': 11, 'ancestor_ids': ['1_1', '15_30'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_65', 'origin': '1_1~CUW~15_30#MGNP'} Metrics: ['ELUC: -3.8372203725102874', 'NSGA-II_crowding_distance: 0.34928124881366696', 'NSGA-II_rank: 3', 'change: 0.12051410481700249', 'is_elite: False']\n", + "Id: 15_21 Identity: {'ancestor_count': 11, 'ancestor_ids': ['12_23', '13_36'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_21', 'origin': '12_23~CUW~13_36#MGNP'} Metrics: ['ELUC: -4.034900818019752', 'NSGA-II_crowding_distance: 0.24609706032559409', 'NSGA-II_rank: 2', 'change: 0.08286108004603764', 'is_elite: False']\n", + "Id: 16_20 Identity: {'ancestor_count': 13, 'ancestor_ids': ['12_23', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_20', 'origin': '12_23~CUW~15_81#MGNP'} Metrics: ['ELUC: -4.1911075970152485', 'NSGA-II_crowding_distance: 1.0798692481894419', 'NSGA-II_rank: 6', 'change: 0.15891568577751145', 'is_elite: False']\n", + "Id: 16_93 Identity: {'ancestor_count': 8, 'ancestor_ids': ['15_91', '12_23'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_93', 'origin': '15_91~CUW~12_23#MGNP'} Metrics: ['ELUC: -4.38278791073638', 'NSGA-II_crowding_distance: 0.3538293772002241', 'NSGA-II_rank: 1', 'change: 0.06032080560269918', 'is_elite: True']\n", + "Id: 16_91 Identity: {'ancestor_count': 13, 'ancestor_ids': ['2_49', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_91', 'origin': '2_49~CUW~15_81#MGNP'} Metrics: ['ELUC: -4.621567788995781', 'NSGA-II_crowding_distance: 0.561776628540801', 'NSGA-II_rank: 7', 'change: 0.24380074897227882', 'is_elite: False']\n", + "Id: 16_75 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_75', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.675939903206251', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27237579290132496', 'is_elite: False']\n", + "Id: 16_78 Identity: {'ancestor_count': 13, 'ancestor_ids': ['12_23', '15_47'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_78', 'origin': '12_23~CUW~15_47#MGNP'} Metrics: ['ELUC: -5.136279752740241', 'NSGA-II_crowding_distance: 0.5793317644856716', 'NSGA-II_rank: 2', 'change: 0.11005613086485912', 'is_elite: False']\n", + "Id: 16_49 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '15_91'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_49', 'origin': '14_68~CUW~15_91#MGNP'} Metrics: ['ELUC: -5.491115453607585', 'NSGA-II_crowding_distance: 0.5752527173934112', 'NSGA-II_rank: 3', 'change: 0.135537929241746', 'is_elite: False']\n", + "Id: 16_90 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_47', '12_23'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_90', 'origin': '15_47~CUW~12_23#MGNP'} Metrics: ['ELUC: -5.6393197088583715', 'NSGA-II_crowding_distance: 0.2949182494877404', 'NSGA-II_rank: 1', 'change: 0.0962673445678932', 'is_elite: True']\n", + "Id: 16_97 Identity: {'ancestor_count': 8, 'ancestor_ids': ['14_96', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_97', 'origin': '14_96~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.051030359517113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26282497008231354', 'is_elite: False']\n", + "Id: 16_96 Identity: {'ancestor_count': 13, 'ancestor_ids': ['12_23', '15_32'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_96', 'origin': '12_23~CUW~15_32#MGNP'} Metrics: ['ELUC: -6.0565681494769', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2628107277083641', 'is_elite: False']\n", + "Id: 16_53 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_21', '15_65'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_53', 'origin': '15_21~CUW~15_65#MGNP'} Metrics: ['ELUC: -6.397022599880506', 'NSGA-II_crowding_distance: 0.505125332426273', 'NSGA-II_rank: 5', 'change: 0.14743490707763443', 'is_elite: False']\n", + "Id: 16_54 Identity: {'ancestor_count': 13, 'ancestor_ids': ['12_23', '15_82'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_54', 'origin': '12_23~CUW~15_82#MGNP'} Metrics: ['ELUC: -6.484311348962424', 'NSGA-II_crowding_distance: 0.7344807247052141', 'NSGA-II_rank: 7', 'change: 0.2547417992600744', 'is_elite: False']\n", + "Id: 16_15 Identity: {'ancestor_count': 13, 'ancestor_ids': ['14_96', '15_47'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_15', 'origin': '14_96~CUW~15_47#MGNP'} Metrics: ['ELUC: -6.584084069380759', 'NSGA-II_crowding_distance: 0.11253311855586975', 'NSGA-II_rank: 1', 'change: 0.11096116463079751', 'is_elite: False']\n", + "Id: 16_67 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_47', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_67', 'origin': '15_47~CUW~15_81#MGNP'} Metrics: ['ELUC: -6.633882904246192', 'NSGA-II_crowding_distance: 0.6309366572352376', 'NSGA-II_rank: 6', 'change: 0.17417948438822442', 'is_elite: False']\n", + "Id: 16_98 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_81', '15_21'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_98', 'origin': '15_81~CUW~15_21#MGNP'} Metrics: ['ELUC: -6.643037180799974', 'NSGA-II_crowding_distance: 0.1745821900043666', 'NSGA-II_rank: 5', 'change: 0.15069688646494298', 'is_elite: False']\n", + "Id: 15_47 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '14_55'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_47', 'origin': '14_18~CUW~14_55#MGNP'} Metrics: ['ELUC: -6.691556990010648', 'NSGA-II_crowding_distance: 0.026990225486341713', 'NSGA-II_rank: 1', 'change: 0.11198792834699166', 'is_elite: False']\n", + "Id: 16_81 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_65', '15_21'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_81', 'origin': '15_65~CUW~15_21#MGNP'} Metrics: ['ELUC: -6.942686754188164', 'NSGA-II_crowding_distance: 0.03829778582530123', 'NSGA-II_rank: 1', 'change: 0.11292884835082205', 'is_elite: False']\n", + "Id: 16_23 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_47', '15_47'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_23', 'origin': '15_47~CUW~15_47#MGNP'} Metrics: ['ELUC: -7.228773498269304', 'NSGA-II_crowding_distance: 0.26856505506743317', 'NSGA-II_rank: 1', 'change: 0.11429840444908353', 'is_elite: True']\n", + "Id: 16_26 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_81', '12_23'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_26', 'origin': '15_81~CUW~12_23#MGNP'} Metrics: ['ELUC: -7.233626802170488', 'NSGA-II_crowding_distance: 0.3027258474936233', 'NSGA-II_rank: 5', 'change: 0.1644197743434815', 'is_elite: False']\n", + "Id: 16_34 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_47', '15_31'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_34', 'origin': '15_47~CUW~15_31#MGNP'} Metrics: ['ELUC: -7.659618327793074', 'NSGA-II_crowding_distance: 0.9768747128992314', 'NSGA-II_rank: 4', 'change: 0.14484296959349677', 'is_elite: False']\n", + "Id: 16_94 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_81', '14_96'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_94', 'origin': '15_81~CUW~14_96#MGNP'} Metrics: ['ELUC: -8.838929471896959', 'NSGA-II_crowding_distance: 0.8969844035339102', 'NSGA-II_rank: 6', 'change: 0.20071274442285467', 'is_elite: False']\n", + "Id: 16_47 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_61', '14_96'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_47', 'origin': '15_61~CUW~14_96#MGNP'} Metrics: ['ELUC: -8.843168020427138', 'NSGA-II_crowding_distance: 0.984199290213819', 'NSGA-II_rank: 5', 'change: 0.17017631647975032', 'is_elite: False']\n", + "Id: 16_42 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_30', '15_32'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_42', 'origin': '15_30~CUW~15_32#MGNP'} Metrics: ['ELUC: -9.050333830357307', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.30225865920552625', 'is_elite: False']\n", + "Id: 16_52 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_30', '14_96'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_52', 'origin': '15_30~CUW~14_96#MGNP'} Metrics: ['ELUC: -9.085466936390134', 'NSGA-II_crowding_distance: 0.9382883704410145', 'NSGA-II_rank: 4', 'change: 0.15014826363297587', 'is_elite: False']\n", + "Id: 16_55 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_55', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.622243666171359', 'NSGA-II_crowding_distance: 0.5780045896920919', 'NSGA-II_rank: 6', 'change: 0.2780187892843645', 'is_elite: False']\n", + "Id: 16_28 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_61', '15_82'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_28', 'origin': '15_61~CUW~15_82#MGNP'} Metrics: ['ELUC: -9.86932362263448', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2786124290994367', 'is_elite: False']\n", + "Id: 16_63 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_30', '15_65'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_63', 'origin': '15_30~CUW~15_65#MGNP'} Metrics: ['ELUC: -10.308686972297574', 'NSGA-II_crowding_distance: 0.4960017456233431', 'NSGA-II_rank: 3', 'change: 0.13759070888845634', 'is_elite: False']\n", + "Id: 16_61 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '12_23'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_61', 'origin': '14_68~CUW~12_23#MGNP'} Metrics: ['ELUC: -10.422179972497243', 'NSGA-II_crowding_distance: 0.4626364313175548', 'NSGA-II_rank: 3', 'change: 0.15689063711370582', 'is_elite: False']\n", + "Id: 16_37 Identity: {'ancestor_count': 13, 'ancestor_ids': ['2_49', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_37', 'origin': '2_49~CUW~15_81#MGNP'} Metrics: ['ELUC: -10.69396597462253', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27688340204717754', 'is_elite: False']\n", + "Id: 15_30 Identity: {'ancestor_count': 10, 'ancestor_ids': ['14_68', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_30', 'origin': '14_68~CUW~14_68#MGNP'} Metrics: ['ELUC: -10.730205278761504', 'NSGA-II_crowding_distance: 0.5462586759242091', 'NSGA-II_rank: 2', 'change: 0.12880877755264608', 'is_elite: False']\n", + "Id: 16_76 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_47', '15_26'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_76', 'origin': '15_47~CUW~15_26#MGNP'} Metrics: ['ELUC: -10.764925173330697', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.19600451119264614', 'is_elite: False']\n", + "Id: 16_39 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_30', '14_68'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_39', 'origin': '15_30~CUW~14_68#MGNP'} Metrics: ['ELUC: -10.836219152912104', 'NSGA-II_crowding_distance: 0.2515117478491278', 'NSGA-II_rank: 1', 'change: 0.12698823097443232', 'is_elite: True']\n", + "Id: 16_80 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_30', '15_30'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_80', 'origin': '15_30~CUW~15_30#MGNP'} Metrics: ['ELUC: -10.902313564923116', 'NSGA-II_crowding_distance: 0.03494769881628989', 'NSGA-II_rank: 1', 'change: 0.12700279791219063', 'is_elite: False']\n", + "Id: 16_100 Identity: {'ancestor_count': 11, 'ancestor_ids': ['14_68', '15_30'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_100', 'origin': '14_68~CUW~15_30#MGNP'} Metrics: ['ELUC: -10.932245347279506', 'NSGA-II_crowding_distance: 0.09350839817202164', 'NSGA-II_rank: 1', 'change: 0.13578625135922562', 'is_elite: False']\n", + "Id: 16_30 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_61', '15_21'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_30', 'origin': '15_61~CUW~15_21#MGNP'} Metrics: ['ELUC: -11.292858135419257', 'NSGA-II_crowding_distance: 0.662226447667947', 'NSGA-II_rank: 3', 'change: 0.1944403044746176', 'is_elite: False']\n", + "Id: 16_35 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '15_30'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_35', 'origin': '15_31~CUW~15_30#MGNP'} Metrics: ['ELUC: -11.390845203439863', 'NSGA-II_crowding_distance: 0.2437569659170313', 'NSGA-II_rank: 2', 'change: 0.15423929860034705', 'is_elite: False']\n", + "Id: 16_73 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_82', '15_26'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_73', 'origin': '15_82~CUW~15_26#MGNP'} Metrics: ['ELUC: -11.597606026804968', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.24064999434455908', 'is_elite: False']\n", + "Id: 16_87 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '15_61'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_87', 'origin': '15_31~CUW~15_61#MGNP'} Metrics: ['ELUC: -11.950868435389385', 'NSGA-II_crowding_distance: 0.10954766654858811', 'NSGA-II_rank: 1', 'change: 0.13710932075071733', 'is_elite: False']\n", + "Id: 16_14 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_61', '15_30'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_14', 'origin': '15_61~CUW~15_30#MGNP'} Metrics: ['ELUC: -12.054724855418332', 'NSGA-II_crowding_distance: 0.12122500173150515', 'NSGA-II_rank: 1', 'change: 0.14942401055366472', 'is_elite: False']\n", + "Id: 16_84 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_65', '15_31'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_84', 'origin': '15_65~CUW~15_31#MGNP'} Metrics: ['ELUC: -12.227976057811066', 'NSGA-II_crowding_distance: 0.10997930225901961', 'NSGA-II_rank: 2', 'change: 0.1674987988384036', 'is_elite: False']\n", + "Id: 16_50 Identity: {'ancestor_count': 13, 'ancestor_ids': ['1_1', '15_61'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_50', 'origin': '1_1~CUW~15_61#MGNP'} Metrics: ['ELUC: -12.234771866321775', 'NSGA-II_crowding_distance: 0.17558603597006636', 'NSGA-II_rank: 2', 'change: 0.16922840295766728', 'is_elite: False']\n", + "Id: 15_65 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '14_64'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_65', 'origin': '13_75~CUW~14_64#MGNP'} Metrics: ['ELUC: -12.67162585524164', 'NSGA-II_crowding_distance: 0.09644160853943526', 'NSGA-II_rank: 1', 'change: 0.161048684163051', 'is_elite: False']\n", + "Id: 16_21 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_65', '15_31'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_21', 'origin': '15_65~CUW~15_31#MGNP'} Metrics: ['ELUC: -12.921712162858528', 'NSGA-II_crowding_distance: 0.051451530826862005', 'NSGA-II_rank: 1', 'change: 0.16348699549523082', 'is_elite: False']\n", + "Id: 16_77 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '15_65'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_77', 'origin': '15_31~CUW~15_65#MGNP'} Metrics: ['ELUC: -13.167691657407211', 'NSGA-II_crowding_distance: 0.15876062840122282', 'NSGA-II_rank: 1', 'change: 0.16798228479787478', 'is_elite: False']\n", + "Id: 16_31 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_26', '15_21'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_31', 'origin': '15_26~CUW~15_21#MGNP'} Metrics: ['ELUC: -13.485074664226719', 'NSGA-II_crowding_distance: 0.23505229937768124', 'NSGA-II_rank: 2', 'change: 0.19275379859650654', 'is_elite: False']\n", + "Id: 16_11 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_30', '15_26'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_11', 'origin': '15_30~CUW~15_26#MGNP'} Metrics: ['ELUC: -13.945964934977326', 'NSGA-II_crowding_distance: 0.14665131329146963', 'NSGA-II_rank: 2', 'change: 0.20262064828828052', 'is_elite: False']\n", + "Id: 15_31 Identity: {'ancestor_count': 13, 'ancestor_ids': ['13_69', '14_23'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_31', 'origin': '13_69~CUW~14_23#MGNP'} Metrics: ['ELUC: -14.059017513721951', 'NSGA-II_crowding_distance: 0.16457030312353318', 'NSGA-II_rank: 1', 'change: 0.1915572066448896', 'is_elite: False']\n", + "Id: 16_33 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_56', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_33', 'origin': '15_56~CUW~1_1#MGNP'} Metrics: ['ELUC: -14.085747788220411', 'NSGA-II_crowding_distance: 0.5600673582205324', 'NSGA-II_rank: 2', 'change: 0.2204388151914724', 'is_elite: False']\n", + "Id: 16_82 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_91', '15_65'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_82', 'origin': '15_91~CUW~15_65#MGNP'} Metrics: ['ELUC: -14.243625780560333', 'NSGA-II_crowding_distance: 0.11800293805804292', 'NSGA-II_rank: 1', 'change: 0.19882746205930826', 'is_elite: False']\n", + "Id: 16_44 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_44', 'origin': '15_31~CUW~15_81#MGNP'} Metrics: ['ELUC: -14.69668262283583', 'NSGA-II_crowding_distance: 0.09736289730931998', 'NSGA-II_rank: 1', 'change: 0.2159452801823801', 'is_elite: False']\n", + "Id: 16_79 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_65', '15_26'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_79', 'origin': '15_65~CUW~15_26#MGNP'} Metrics: ['ELUC: -14.825884975078761', 'NSGA-II_crowding_distance: 0.12496584441508063', 'NSGA-II_rank: 1', 'change: 0.21799726285863952', 'is_elite: False']\n", + "Id: 16_51 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_81', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_51', 'origin': '15_81~CUW~15_81#MGNP'} Metrics: ['ELUC: -15.53089388037496', 'NSGA-II_crowding_distance: 0.1352730813984992', 'NSGA-II_rank: 1', 'change: 0.23907548109609691', 'is_elite: False']\n", + "Id: 15_81 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_81', 'origin': '13_75~CUW~14_68#MGNP'} Metrics: ['ELUC: -15.723820826513172', 'NSGA-II_crowding_distance: 0.22168652203832012', 'NSGA-II_rank: 1', 'change: 0.24312148758869404', 'is_elite: True']\n", + "Id: 16_92 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_82', '15_31'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_92', 'origin': '15_82~CUW~15_31#MGNP'} Metrics: ['ELUC: -16.753798798526933', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3008117025649594', 'is_elite: False']\n", + "Id: 16_12 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_82', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_12', 'origin': '15_82~CUW~15_81#MGNP'} Metrics: ['ELUC: -16.88418382461264', 'NSGA-II_crowding_distance: 0.24247135124159985', 'NSGA-II_rank: 1', 'change: 0.28225605145499094', 'is_elite: True']\n", + "Id: 16_16 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_82', '15_31'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_16', 'origin': '15_82~CUW~15_31#MGNP'} Metrics: ['ELUC: -16.9595518850534', 'NSGA-II_crowding_distance: 0.09647823096555969', 'NSGA-II_rank: 1', 'change: 0.29449879829704484', 'is_elite: False']\n", + "Id: 16_36 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_82', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_36', 'origin': '15_82~CUW~15_81#MGNP'} Metrics: ['ELUC: -17.43600833540373', 'NSGA-II_crowding_distance: 0.05748839371137763', 'NSGA-II_rank: 1', 'change: 0.30167837349453214', 'is_elite: False']\n", + "Id: 15_32 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '14_18'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_32', 'origin': '2_49~CUW~14_18#MGNP'} Metrics: ['ELUC: -17.486781673961662', 'NSGA-II_crowding_distance: 0.013676395274615588', 'NSGA-II_rank: 1', 'change: 0.30270480182257037', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 15_82 Identity: {'ancestor_count': 12, 'ancestor_ids': ['14_18', '14_34'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_82', 'origin': '14_18~CUW~14_34#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 16_18 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_18', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 16_59 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_82', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_59', 'origin': '15_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 16_70 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_70', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 16_88 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_88', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 16.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 17...:\n", + "PopulationResponse:\n", + " Generation: 17\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/17/20240219-214255\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 17 and asking ESP for generation 18...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 17 data persisted.\n", + "Evaluated candidates:\n", + "Id: 17_37 Identity: {'ancestor_count': 14, 'ancestor_ids': ['2_49', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_37', 'origin': '2_49~CUW~16_90#MGNP'} Metrics: ['ELUC: 12.470812210963757', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.27234547494011746', 'is_elite: False']\n", + "Id: 17_19 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_12', '16_56'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_19', 'origin': '16_12~CUW~16_56#MGNP'} Metrics: ['ELUC: 12.064397437880046', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24438760012071392', 'is_elite: False']\n", + "Id: 17_54 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_88', '16_51'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_54', 'origin': '16_88~CUW~16_51#MGNP'} Metrics: ['ELUC: 8.905684258374194', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2693547274137277', 'is_elite: False']\n", + "Id: 17_61 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_61', 'origin': '15_31~CUW~2_49#MGNP'} Metrics: ['ELUC: 8.041200514758682', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2737469742330062', 'is_elite: False']\n", + "Id: 17_27 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '16_39'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_27', 'origin': '2_49~CUW~16_39#MGNP'} Metrics: ['ELUC: 5.806527398370644', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2686943156290342', 'is_elite: False']\n", + "Id: 17_86 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_56'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_86', 'origin': '16_39~CUW~16_56#MGNP'} Metrics: ['ELUC: 4.718796395376255', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.132007532117991', 'is_elite: False']\n", + "Id: 17_95 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '16_88'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_95', 'origin': '15_31~CUW~16_88#MGNP'} Metrics: ['ELUC: 4.399887764552998', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.23275615633314764', 'is_elite: False']\n", + "Id: 17_71 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_90', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_71', 'origin': '16_90~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.144281171129901', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3454724034192049', 'is_elite: False']\n", + "Id: 17_75 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_85', '16_39'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_75', 'origin': '16_85~CUW~16_39#MGNP'} Metrics: ['ELUC: 3.116958571068919', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.06989014551396147', 'is_elite: False']\n", + "Id: 17_73 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_90', '16_88'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_73', 'origin': '16_90~CUW~16_88#MGNP'} Metrics: ['ELUC: 2.7924438350820138', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2603019847353503', 'is_elite: False']\n", + "Id: 17_17 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_17', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.910235461000815', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.055257222862567984', 'is_elite: False']\n", + "Id: 17_51 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_24', '16_88'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_51', 'origin': '16_24~CUW~16_88#MGNP'} Metrics: ['ELUC: 1.8221240369972664', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.25145400895320036', 'is_elite: False']\n", + "Id: 17_97 Identity: {'ancestor_count': 14, 'ancestor_ids': ['2_49', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_97', 'origin': '2_49~CUW~16_90#MGNP'} Metrics: ['ELUC: 1.6841993325162823', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.35092512495295936', 'is_elite: False']\n", + "Id: 17_90 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_90', 'origin': '15_31~CUW~16_90#MGNP'} Metrics: ['ELUC: 1.5767313437720083', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.12131248102787266', 'is_elite: False']\n", + "Id: 17_16 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_16', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.994837699267899', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.04652673309778606', 'is_elite: False']\n", + "Id: 17_29 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_29', 'origin': '1_1~CUW~16_85#MGNP'} Metrics: ['ELUC: 0.9418888129592541', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.04433373358991878', 'is_elite: False']\n", + "Id: 17_11 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_11', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.7109777339470621', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03936654091026327', 'is_elite: False']\n", + "Id: 17_98 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_98', 'origin': '1_1~CUW~16_85#MGNP'} Metrics: ['ELUC: 0.02913539280774491', 'NSGA-II_crowding_distance: 0.2344162513631765', 'NSGA-II_rank: 3', 'change: 0.04287833480282331', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 17_26 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_77', '16_24'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_26', 'origin': '16_77~CUW~16_24#MGNP'} Metrics: ['ELUC: -0.1827614106285793', 'NSGA-II_crowding_distance: 0.6868836198764645', 'NSGA-II_rank: 7', 'change: 0.10552764728341152', 'is_elite: False']\n", + "Id: 17_33 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '16_15'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_33', 'origin': '15_31~CUW~16_15#MGNP'} Metrics: ['ELUC: -0.2619301436269851', 'NSGA-II_crowding_distance: 0.660210422883869', 'NSGA-II_rank: 7', 'change: 0.1404574270167397', 'is_elite: False']\n", + "Id: 17_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['16_56', '1_1'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_100', 'origin': '16_56~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.4433021742615898', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03619426605419219', 'is_elite: False']\n", + "Id: 17_23 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_88', '16_23'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_23', 'origin': '16_88~CUW~16_23#MGNP'} Metrics: ['ELUC: -0.5458575954007179', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23883720281942966', 'is_elite: False']\n", + "Id: 17_48 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_88', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_48', 'origin': '16_88~CUW~16_93#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 17_93 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_93', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_93', 'origin': '16_93~CUW~16_85#MGNP'} Metrics: ['ELUC: -0.8501377994037809', 'NSGA-II_crowding_distance: 0.3348349965341174', 'NSGA-II_rank: 1', 'change: 0.03312994436869362', 'is_elite: True']\n", + "Id: 17_18 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '16_24'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_18', 'origin': '1_1~CUW~16_24#MGNP'} Metrics: ['ELUC: -1.2490003793047793', 'NSGA-II_crowding_distance: 0.3358485994423287', 'NSGA-II_rank: 4', 'change: 0.0575651130642298', 'is_elite: False']\n", + "Id: 17_60 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_79', '16_56'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_60', 'origin': '16_79~CUW~16_56#MGNP'} Metrics: ['ELUC: -1.4188333655452887', 'NSGA-II_crowding_distance: 0.7432635890518957', 'NSGA-II_rank: 6', 'change: 0.07882812194582683', 'is_elite: False']\n", + "Id: 16_24 Identity: {'ancestor_count': 8, 'ancestor_ids': ['14_96', '1_1'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_24', 'origin': '14_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8499730369784853', 'NSGA-II_crowding_distance: 0.29417550427836703', 'NSGA-II_rank: 3', 'change: 0.054998924497522375', 'is_elite: False']\n", + "Id: 17_22 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_85', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_22', 'origin': '16_85~CUW~16_93#MGNP'} Metrics: ['ELUC: -2.032381040897222', 'NSGA-II_crowding_distance: 0.3154877366626101', 'NSGA-II_rank: 2', 'change: 0.05468954904038258', 'is_elite: False']\n", + "Id: 17_59 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_93', '15_31'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_59', 'origin': '16_93~CUW~15_31#MGNP'} Metrics: ['ELUC: -2.0901622551910624', 'NSGA-II_crowding_distance: 0.3981979683007301', 'NSGA-II_rank: 5', 'change: 0.07687791583638237', 'is_elite: False']\n", + "Id: 17_46 Identity: {'ancestor_count': 14, 'ancestor_ids': ['1_1', '16_23'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_46', 'origin': '1_1~CUW~16_23#MGNP'} Metrics: ['ELUC: -2.1309669953338144', 'NSGA-II_crowding_distance: 0.15335335928404006', 'NSGA-II_rank: 5', 'change: 0.0893475856921544', 'is_elite: False']\n", + "Id: 17_87 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_87', 'origin': '16_39~CUW~16_85#MGNP'} Metrics: ['ELUC: -2.138595834495019', 'NSGA-II_crowding_distance: 0.40036787819599295', 'NSGA-II_rank: 6', 'change: 0.10348334198599501', 'is_elite: False']\n", + "Id: 17_77 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_90', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_77', 'origin': '16_90~CUW~16_85#MGNP'} Metrics: ['ELUC: -2.1763532249958857', 'NSGA-II_crowding_distance: 0.28630869900088984', 'NSGA-II_rank: 4', 'change: 0.0749752099306569', 'is_elite: False']\n", + "Id: 17_88 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '16_24'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_88', 'origin': '1_1~CUW~16_24#MGNP'} Metrics: ['ELUC: -2.376652485599023', 'NSGA-II_crowding_distance: 0.18078110396224928', 'NSGA-II_rank: 3', 'change: 0.07387392206822846', 'is_elite: False']\n", + "Id: 17_50 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '1_1'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_50', 'origin': '15_31~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.9345269795362863', 'NSGA-II_crowding_distance: 0.32475259578691457', 'NSGA-II_rank: 6', 'change: 0.11481899944617943', 'is_elite: False']\n", + "Id: 17_74 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_93', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_74', 'origin': '16_93~CUW~16_85#MGNP'} Metrics: ['ELUC: -2.9910728758205263', 'NSGA-II_crowding_distance: 0.2920493658705353', 'NSGA-II_rank: 1', 'change: 0.05404598348340827', 'is_elite: True']\n", + "Id: 17_13 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_81', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_13', 'origin': '15_81~CUW~16_93#MGNP'} Metrics: ['ELUC: -3.042447246263053', 'NSGA-II_crowding_distance: 0.6754021044693586', 'NSGA-II_rank: 7', 'change: 0.18110164476685384', 'is_elite: False']\n", + "Id: 17_34 Identity: {'ancestor_count': 14, 'ancestor_ids': ['1_1', '15_31'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_34', 'origin': '1_1~CUW~15_31#MGNP'} Metrics: ['ELUC: -3.0457768004638353', 'NSGA-II_crowding_distance: 0.6697531441931548', 'NSGA-II_rank: 6', 'change: 0.13752727516320293', 'is_elite: False']\n", + "Id: 17_30 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_45'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_30', 'origin': '16_23~CUW~16_45#MGNP'} Metrics: ['ELUC: -3.140158734394227', 'NSGA-II_crowding_distance: 0.12453992765028662', 'NSGA-II_rank: 3', 'change: 0.07669768703960679', 'is_elite: False']\n", + "Id: 17_47 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_47', 'origin': '16_39~CUW~16_85#MGNP'} Metrics: ['ELUC: -3.154716475923526', 'NSGA-II_crowding_distance: 0.31663806150230706', 'NSGA-II_rank: 5', 'change: 0.0959322680651512', 'is_elite: False']\n", + "Id: 17_82 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_45', '16_51'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_82', 'origin': '16_45~CUW~16_51#MGNP'} Metrics: ['ELUC: -3.665640697602201', 'NSGA-II_crowding_distance: 0.6327909496572233', 'NSGA-II_rank: 5', 'change: 0.14090136769571263', 'is_elite: False']\n", + "Id: 17_91 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_90', '16_77'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_91', 'origin': '16_90~CUW~16_77#MGNP'} Metrics: ['ELUC: -3.8221375285973247', 'NSGA-II_crowding_distance: 0.3444567239108548', 'NSGA-II_rank: 4', 'change: 0.08490292797832497', 'is_elite: False']\n", + "Id: 17_72 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_90', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_72', 'origin': '16_90~CUW~16_93#MGNP'} Metrics: ['ELUC: -3.968714364017734', 'NSGA-II_crowding_distance: 0.24682319245259157', 'NSGA-II_rank: 3', 'change: 0.07891936786527332', 'is_elite: False']\n", + "Id: 17_36 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_85', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_36', 'origin': '16_85~CUW~16_93#MGNP'} Metrics: ['ELUC: -4.112834344152311', 'NSGA-II_crowding_distance: 0.3035148575505088', 'NSGA-II_rank: 2', 'change: 0.06316873403168262', 'is_elite: False']\n", + "Id: 16_93 Identity: {'ancestor_count': 8, 'ancestor_ids': ['15_91', '12_23'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_93', 'origin': '15_91~CUW~12_23#MGNP'} Metrics: ['ELUC: -4.38278791073638', 'NSGA-II_crowding_distance: 0.2225503012127267', 'NSGA-II_rank: 1', 'change: 0.06032080560269918', 'is_elite: True']\n", + "Id: 17_25 Identity: {'ancestor_count': 13, 'ancestor_ids': ['16_24', '15_81'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_25', 'origin': '16_24~CUW~15_81#MGNP'} Metrics: ['ELUC: -4.412091825355615', 'NSGA-II_crowding_distance: 0.8345906468872466', 'NSGA-II_rank: 7', 'change: 0.19331755213312363', 'is_elite: False']\n", + "Id: 17_53 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_77', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_53', 'origin': '16_77~CUW~16_90#MGNP'} Metrics: ['ELUC: -4.748700516443953', 'NSGA-II_crowding_distance: 0.23813505993275624', 'NSGA-II_rank: 4', 'change: 0.11534103048117492', 'is_elite: False']\n", + "Id: 17_64 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_77', '16_23'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_64', 'origin': '16_77~CUW~16_23#MGNP'} Metrics: ['ELUC: -4.949201185752015', 'NSGA-II_crowding_distance: 0.1775657391529613', 'NSGA-II_rank: 2', 'change: 0.0902482850488944', 'is_elite: False']\n", + "Id: 17_44 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_90', '1_1'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_44', 'origin': '16_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.102033636570195', 'NSGA-II_crowding_distance: 0.32446979244129037', 'NSGA-II_rank: 4', 'change: 0.11992904544404077', 'is_elite: False']\n", + "Id: 17_68 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_68', 'origin': '16_23~CUW~16_90#MGNP'} Metrics: ['ELUC: -5.285022670363588', 'NSGA-II_crowding_distance: 0.06286724374858571', 'NSGA-II_rank: 2', 'change: 0.09233909635081886', 'is_elite: False']\n", + "Id: 17_85 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_85', 'origin': '16_23~CUW~16_93#MGNP'} Metrics: ['ELUC: -5.344585391507659', 'NSGA-II_crowding_distance: 0.20418129791648953', 'NSGA-II_rank: 1', 'change: 0.08051020102415904', 'is_elite: True']\n", + "Id: 17_43 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_93', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_43', 'origin': '16_93~CUW~16_90#MGNP'} Metrics: ['ELUC: -5.412736571577593', 'NSGA-II_crowding_distance: 0.20138597112991052', 'NSGA-II_rank: 3', 'change: 0.09912678435481213', 'is_elite: False']\n", + "Id: 17_31 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_31', 'origin': '16_23~CUW~16_93#MGNP'} Metrics: ['ELUC: -5.537275133890857', 'NSGA-II_crowding_distance: 0.43922953867853554', 'NSGA-II_rank: 3', 'change: 0.10124206456086714', 'is_elite: False']\n", + "Id: 16_90 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_47', '12_23'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_90', 'origin': '15_47~CUW~12_23#MGNP'} Metrics: ['ELUC: -5.6393197088583715', 'NSGA-II_crowding_distance: 0.4221267286640105', 'NSGA-II_rank: 2', 'change: 0.0962673445678932', 'is_elite: False']\n", + "Id: 17_39 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_81', '16_23'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_39', 'origin': '15_81~CUW~16_23#MGNP'} Metrics: ['ELUC: -5.72348833856657', 'NSGA-II_crowding_distance: 0.9319838151611898', 'NSGA-II_rank: 6', 'change: 0.1712113923911308', 'is_elite: False']\n", + "Id: 17_96 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_96', 'origin': '16_23~CUW~16_93#MGNP'} Metrics: ['ELUC: -6.086041535163455', 'NSGA-II_crowding_distance: 0.14270169519658293', 'NSGA-II_rank: 1', 'change: 0.09233921569817309', 'is_elite: False']\n", + "Id: 17_65 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_65', 'origin': '16_23~CUW~16_90#MGNP'} Metrics: ['ELUC: -6.299749523710083', 'NSGA-II_crowding_distance: 0.07554188772459058', 'NSGA-II_rank: 1', 'change: 0.1068797769996951', 'is_elite: False']\n", + "Id: 17_52 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_52', 'origin': '16_39~CUW~16_93#MGNP'} Metrics: ['ELUC: -6.319969350651742', 'NSGA-II_crowding_distance: 0.07770168305533466', 'NSGA-II_rank: 1', 'change: 0.11090940437897606', 'is_elite: False']\n", + "Id: 17_57 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_93', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_57', 'origin': '16_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.94750138529227', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2708455983925204', 'is_elite: False']\n", + "Id: 16_23 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_47', '15_47'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_23', 'origin': '15_47~CUW~15_47#MGNP'} Metrics: ['ELUC: -7.228773498269304', 'NSGA-II_crowding_distance: 0.3107503444004352', 'NSGA-II_rank: 1', 'change: 0.11429840444908353', 'is_elite: True']\n", + "Id: 17_24 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_81', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_24', 'origin': '15_81~CUW~16_90#MGNP'} Metrics: ['ELUC: -7.847880388747802', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.20213393500451052', 'is_elite: False']\n", + "Id: 17_62 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_79', '16_23'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_62', 'origin': '16_79~CUW~16_23#MGNP'} Metrics: ['ELUC: -7.877623823776712', 'NSGA-II_crowding_distance: 1.0516155345828997', 'NSGA-II_rank: 5', 'change: 0.16847966713888554', 'is_elite: False']\n", + "Id: 17_20 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_39', '16_23'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_20', 'origin': '16_39~CUW~16_23#MGNP'} Metrics: ['ELUC: -8.379523265755143', 'NSGA-II_crowding_distance: 0.3833910743451733', 'NSGA-II_rank: 4', 'change: 0.1361137778195935', 'is_elite: False']\n", + "Id: 17_99 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_56'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_99', 'origin': '16_39~CUW~16_56#MGNP'} Metrics: ['ELUC: -8.632800446714269', 'NSGA-II_crowding_distance: 0.24319765609453242', 'NSGA-II_rank: 4', 'change: 0.15532077840781774', 'is_elite: False']\n", + "Id: 17_40 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_77', '1_1'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_40', 'origin': '16_77~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.082356771408561', 'NSGA-II_crowding_distance: 0.8932627693761086', 'NSGA-II_rank: 4', 'change: 0.1805157463477486', 'is_elite: False']\n", + "Id: 17_42 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_39', '16_77'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_42', 'origin': '16_39~CUW~16_77#MGNP'} Metrics: ['ELUC: -10.162517278257534', 'NSGA-II_crowding_distance: 0.7846488951456079', 'NSGA-II_rank: 3', 'change: 0.12910340233295822', 'is_elite: False']\n", + "Id: 17_35 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_12', '15_81'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_35', 'origin': '16_12~CUW~15_81#MGNP'} Metrics: ['ELUC: -10.17703390529524', 'NSGA-II_crowding_distance: 0.8987499135434469', 'NSGA-II_rank: 3', 'change: 0.20894086873758094', 'is_elite: False']\n", + "Id: 17_38 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_93', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_38', 'origin': '16_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.213041861614249', 'NSGA-II_crowding_distance: 0.7927932724398435', 'NSGA-II_rank: 5', 'change: 0.28542207403548053', 'is_elite: False']\n", + "Id: 17_49 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_49', 'origin': '16_39~CUW~16_93#MGNP'} Metrics: ['ELUC: -10.2670030600229', 'NSGA-II_crowding_distance: 0.708058840998672', 'NSGA-II_rank: 2', 'change: 0.12730207687152262', 'is_elite: False']\n", + "Id: 16_39 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_30', '14_68'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_39', 'origin': '15_30~CUW~14_68#MGNP'} Metrics: ['ELUC: -10.836219152912104', 'NSGA-II_crowding_distance: 0.5048744069932736', 'NSGA-II_rank: 1', 'change: 0.12698823097443232', 'is_elite: True']\n", + "Id: 17_80 Identity: {'ancestor_count': 14, 'ancestor_ids': ['2_49', '16_12'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_80', 'origin': '2_49~CUW~16_12#MGNP'} Metrics: ['ELUC: -12.217012421400808', 'NSGA-II_crowding_distance: 0.23354843561406294', 'NSGA-II_rank: 5', 'change: 0.2884125634483768', 'is_elite: False']\n", + "Id: 17_67 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_67', 'origin': '15_31~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.697040856336052', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.298559826453584', 'is_elite: False']\n", + "Id: 17_28 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_81', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_28', 'origin': '15_81~CUW~16_93#MGNP'} Metrics: ['ELUC: -12.744387160823612', 'NSGA-II_crowding_distance: 0.7569598045367163', 'NSGA-II_rank: 2', 'change: 0.17451420368311918', 'is_elite: False']\n", + "Id: 17_92 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_14', '16_77'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_92', 'origin': '16_14~CUW~16_77#MGNP'} Metrics: ['ELUC: -12.816296316029963', 'NSGA-II_crowding_distance: 0.4442895836119636', 'NSGA-II_rank: 1', 'change: 0.1701196919408194', 'is_elite: True']\n", + "Id: 17_79 Identity: {'ancestor_count': 13, 'ancestor_ids': ['16_39', '15_81'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_79', 'origin': '16_39~CUW~15_81#MGNP'} Metrics: ['ELUC: -14.284992721750353', 'NSGA-II_crowding_distance: 0.20055702320810942', 'NSGA-II_rank: 1', 'change: 0.2010275911879217', 'is_elite: False']\n", + "Id: 17_14 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_77', '16_79'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_14', 'origin': '16_77~CUW~16_79#MGNP'} Metrics: ['ELUC: -14.342501295911662', 'NSGA-II_crowding_distance: 0.18304360350035812', 'NSGA-II_rank: 1', 'change: 0.20406126929118099', 'is_elite: False']\n", + "Id: 17_94 Identity: {'ancestor_count': 14, 'ancestor_ids': ['2_49', '16_90'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_94', 'origin': '2_49~CUW~16_90#MGNP'} Metrics: ['ELUC: -14.7302159454014', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2681886899478905', 'is_elite: False']\n", + "Id: 17_78 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_12', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_78', 'origin': '16_12~CUW~16_85#MGNP'} Metrics: ['ELUC: -14.949600798178903', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.25988956832873594', 'is_elite: False']\n", + "Id: 17_58 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_81', '16_23'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_58', 'origin': '15_81~CUW~16_23#MGNP'} Metrics: ['ELUC: -15.186568253241274', 'NSGA-II_crowding_distance: 0.19486326047528862', 'NSGA-II_rank: 1', 'change: 0.24034370862493198', 'is_elite: False']\n", + "Id: 17_69 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_12', '1_1'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_69', 'origin': '16_12~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.599462515549034', 'NSGA-II_crowding_distance: 0.03986598235446419', 'NSGA-II_rank: 1', 'change: 0.24087310431475656', 'is_elite: False']\n", + "Id: 17_15 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_81', '16_39'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_15', 'origin': '15_81~CUW~16_39#MGNP'} Metrics: ['ELUC: -15.686878401028043', 'NSGA-II_crowding_distance: 0.6130192574692577', 'NSGA-II_rank: 2', 'change: 0.24503202646548752', 'is_elite: False']\n", + "Id: 15_81 Identity: {'ancestor_count': 12, 'ancestor_ids': ['13_75', '14_68'], 'birth_generation': 15, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '15_81', 'origin': '13_75~CUW~14_68#MGNP'} Metrics: ['ELUC: -15.723820826513172', 'NSGA-II_crowding_distance: 0.06482217452475028', 'NSGA-II_rank: 1', 'change: 0.24312148758869404', 'is_elite: False']\n", + "Id: 17_21 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_12', '16_39'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_21', 'origin': '16_12~CUW~16_39#MGNP'} Metrics: ['ELUC: -15.84419782422616', 'NSGA-II_crowding_distance: 0.15206980996509786', 'NSGA-II_rank: 1', 'change: 0.256061362982323', 'is_elite: False']\n", + "Id: 17_89 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_88', '16_24'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_89', 'origin': '16_88~CUW~16_24#MGNP'} Metrics: ['ELUC: -15.957720444295237', 'NSGA-II_crowding_distance: 0.3213963325933108', 'NSGA-II_rank: 2', 'change: 0.28827447879516976', 'is_elite: False']\n", + "Id: 17_63 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_31', '16_12'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_63', 'origin': '15_31~CUW~16_12#MGNP'} Metrics: ['ELUC: -16.325091636105334', 'NSGA-II_crowding_distance: 0.12851181102470627', 'NSGA-II_rank: 1', 'change: 0.27829197898007807', 'is_elite: False']\n", + "Id: 17_83 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_12', '16_12'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_83', 'origin': '16_12~CUW~16_12#MGNP'} Metrics: ['ELUC: -16.776328295323662', 'NSGA-II_crowding_distance: 0.04508392738509605', 'NSGA-II_rank: 1', 'change: 0.2785878820786241', 'is_elite: False']\n", + "Id: 16_12 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_82', '15_81'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_12', 'origin': '15_82~CUW~15_81#MGNP'} Metrics: ['ELUC: -16.88418382461264', 'NSGA-II_crowding_distance: 0.024140393182397954', 'NSGA-II_rank: 1', 'change: 0.28225605145499094', 'is_elite: False']\n", + "Id: 17_12 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_12', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_12', 'origin': '16_12~CUW~16_93#MGNP'} Metrics: ['ELUC: -16.920251103719902', 'NSGA-II_crowding_distance: 0.06037107054626716', 'NSGA-II_rank: 1', 'change: 0.28334842300958324', 'is_elite: False']\n", + "Id: 17_56 Identity: {'ancestor_count': 14, 'ancestor_ids': ['15_81', '16_12'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_56', 'origin': '15_81~CUW~16_12#MGNP'} Metrics: ['ELUC: -17.26293226260431', 'NSGA-II_crowding_distance: 0.10349051717367436', 'NSGA-II_rank: 1', 'change: 0.2938419557880178', 'is_elite: False']\n", + "Id: 17_55 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_12', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_55', 'origin': '16_12~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.47028904905064', 'NSGA-II_crowding_distance: 0.15046202032533812', 'NSGA-II_rank: 2', 'change: 0.3031287266699481', 'is_elite: False']\n", + "Id: 17_84 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_88', '16_12'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_84', 'origin': '16_88~CUW~16_12#MGNP'} Metrics: ['ELUC: -17.533684859981268', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30386595198229793', 'is_elite: False']\n", + "Id: 17_45 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_51', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_45', 'origin': '16_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59060993322931', 'NSGA-II_crowding_distance: 0.04978355569390812', 'NSGA-II_rank: 1', 'change: 0.30285149106331477', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 16_88 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_88', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 17_32 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '16_88'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_32', 'origin': '1_1~CUW~16_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 17_41 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_90', '16_88'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_41', 'origin': '16_90~CUW~16_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 17_66 Identity: {'ancestor_count': 13, 'ancestor_ids': ['2_49', '15_81'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_66', 'origin': '2_49~CUW~15_81#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 17_70 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_70', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 17_76 Identity: {'ancestor_count': 3, 'ancestor_ids': ['16_88', '2_49'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_76', 'origin': '16_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 17_81 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_45', '16_88'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_81', 'origin': '16_45~CUW~16_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 17.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 18...:\n", + "PopulationResponse:\n", + " Generation: 18\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/18/20240219-215008\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 18 and asking ESP for generation 19...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 18 data persisted.\n", + "Evaluated candidates:\n", + "Id: 18_18 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_81', '17_52'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_18', 'origin': '17_81~CUW~17_52#MGNP'} Metrics: ['ELUC: 23.48209170678168', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3017116233789387', 'is_elite: False']\n", + "Id: 18_80 Identity: {'ancestor_count': 15, 'ancestor_ids': ['2_49', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_80', 'origin': '2_49~CUW~17_81#MGNP'} Metrics: ['ELUC: 23.32219486794697', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3020696044583879', 'is_elite: False']\n", + "Id: 18_43 Identity: {'ancestor_count': 15, 'ancestor_ids': ['1_1', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_43', 'origin': '1_1~CUW~17_81#MGNP'} Metrics: ['ELUC: 17.37611776275598', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2888778393762135', 'is_elite: False']\n", + "Id: 18_58 Identity: {'ancestor_count': 16, 'ancestor_ids': ['2_49', '17_14'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_58', 'origin': '2_49~CUW~17_14#MGNP'} Metrics: ['ELUC: 12.528852105415355', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27051421711358464', 'is_elite: False']\n", + "Id: 18_66 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_81', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_66', 'origin': '17_81~CUW~16_39#MGNP'} Metrics: ['ELUC: 9.504176046781456', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2636823761856271', 'is_elite: False']\n", + "Id: 18_79 Identity: {'ancestor_count': 15, 'ancestor_ids': ['1_1', '17_63'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_79', 'origin': '1_1~CUW~17_63#MGNP'} Metrics: ['ELUC: 9.159337277907795', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.18838060721475183', 'is_elite: False']\n", + "Id: 18_13 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_23', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_13', 'origin': '16_23~CUW~17_81#MGNP'} Metrics: ['ELUC: 8.556860551543755', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.30639023668148746', 'is_elite: False']\n", + "Id: 18_69 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_93', '17_63'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_69', 'origin': '17_93~CUW~17_63#MGNP'} Metrics: ['ELUC: 3.630838352916531', 'NSGA-II_crowding_distance: 1.1927173253592578', 'NSGA-II_rank: 8', 'change: 0.23152791409990234', 'is_elite: False']\n", + "Id: 18_99 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '1_1'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_99', 'origin': '16_39~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.9384926113110907', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08136714582742621', 'is_elite: False']\n", + "Id: 18_67 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_81', '17_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_67', 'origin': '17_81~CUW~17_93#MGNP'} Metrics: ['ELUC: 1.6523090679594548', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.32656211885858666', 'is_elite: False']\n", + "Id: 18_59 Identity: {'ancestor_count': 10, 'ancestor_ids': ['17_93', '1_1'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_59', 'origin': '17_93~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.3942824973188235', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05631349937039523', 'is_elite: False']\n", + "Id: 18_46 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_85', '17_79'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_46', 'origin': '17_85~CUW~17_79#MGNP'} Metrics: ['ELUC: 0.7773127685087478', 'NSGA-II_crowding_distance: 0.1724166155673648', 'NSGA-II_rank: 4', 'change: 0.08069049759658335', 'is_elite: False']\n", + "Id: 18_44 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '17_92'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_44', 'origin': '1_1~CUW~17_92#MGNP'} Metrics: ['ELUC: 0.6158144394917932', 'NSGA-II_crowding_distance: 0.4028587792963806', 'NSGA-II_rank: 4', 'change: 0.08747977458605469', 'is_elite: False']\n", + "Id: 18_52 Identity: {'ancestor_count': 12, 'ancestor_ids': ['1_1', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_52', 'origin': '1_1~CUW~16_39#MGNP'} Metrics: ['ELUC: 0.23618803911492262', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15202516245368816', 'is_elite: False']\n", + "Id: 18_93 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_93', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.20832830285446935', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.020356976719036555', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 18_81 Identity: {'ancestor_count': 12, 'ancestor_ids': ['1_1', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_81', 'origin': '1_1~CUW~16_39#MGNP'} Metrics: ['ELUC: -0.35085727649440873', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.12015925764780985', 'is_elite: False']\n", + "Id: 18_83 Identity: {'ancestor_count': 15, 'ancestor_ids': ['2_49', '17_58'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_83', 'origin': '2_49~CUW~17_58#MGNP'} Metrics: ['ELUC: -0.3808337766799963', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26246623365274635', 'is_elite: False']\n", + "Id: 18_73 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '17_74'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_73', 'origin': '1_1~CUW~17_74#MGNP'} Metrics: ['ELUC: -0.4786553347588498', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04453475820357172', 'is_elite: False']\n", + "Id: 18_85 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_85', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5099181575551536', 'NSGA-II_crowding_distance: 0.11431687023304048', 'NSGA-II_rank: 1', 'change: 0.025118560399270004', 'is_elite: False']\n", + "Id: 18_38 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_93', '1_1'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_38', 'origin': '16_93~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5410436235618417', 'NSGA-II_crowding_distance: 0.046199885153366996', 'NSGA-II_rank: 1', 'change: 0.02982604041097462', 'is_elite: False']\n", + "Id: 18_27 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_93', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_27', 'origin': '16_93~CUW~17_81#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.9361171969222661', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 17_93 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_93', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_93', 'origin': '16_93~CUW~16_85#MGNP'} Metrics: ['ELUC: -0.8501377994037809', 'NSGA-II_crowding_distance: 0.09702124773009399', 'NSGA-II_rank: 1', 'change: 0.03312994436869362', 'is_elite: False']\n", + "Id: 18_22 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_22', 'origin': '16_23~CUW~16_39#MGNP'} Metrics: ['ELUC: -0.8649268352797502', 'NSGA-II_crowding_distance: 0.13674474463837957', 'NSGA-II_rank: 6', 'change: 0.12150837612683181', 'is_elite: False']\n", + "Id: 18_21 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_21', 'origin': '17_92~CUW~16_23#MGNP'} Metrics: ['ELUC: -1.0143975198944462', 'NSGA-II_crowding_distance: 0.6070435566274882', 'NSGA-II_rank: 6', 'change: 0.13062302315903265', 'is_elite: False']\n", + "Id: 18_12 Identity: {'ancestor_count': 10, 'ancestor_ids': ['17_93', '17_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_12', 'origin': '17_93~CUW~17_93#MGNP'} Metrics: ['ELUC: -1.127263519268355', 'NSGA-II_crowding_distance: 0.3094281332511486', 'NSGA-II_rank: 2', 'change: 0.03922404690434182', 'is_elite: False']\n", + "Id: 18_92 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_21', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_92', 'origin': '17_21~CUW~16_23#MGNP'} Metrics: ['ELUC: -1.47605466846175', 'NSGA-II_crowding_distance: 0.6976725316375849', 'NSGA-II_rank: 6', 'change: 0.21841841637100165', 'is_elite: False']\n", + "Id: 18_29 Identity: {'ancestor_count': 10, 'ancestor_ids': ['2_49', '17_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_29', 'origin': '2_49~CUW~17_93#MGNP'} Metrics: ['ELUC: -1.4919395585343644', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.29410367011323135', 'is_elite: False']\n", + "Id: 18_70 Identity: {'ancestor_count': 10, 'ancestor_ids': ['17_93', '17_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_70', 'origin': '17_93~CUW~17_93#MGNP'} Metrics: ['ELUC: -1.7250449409737587', 'NSGA-II_crowding_distance: 0.10794513745496997', 'NSGA-II_rank: 1', 'change: 0.038682151326667885', 'is_elite: False']\n", + "Id: 18_16 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '17_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_16', 'origin': '1_1~CUW~17_93#MGNP'} Metrics: ['ELUC: -2.0687097723200116', 'NSGA-II_crowding_distance: 0.11086045009719081', 'NSGA-II_rank: 1', 'change: 0.04465882585508328', 'is_elite: False']\n", + "Id: 18_91 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_93', '17_56'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_91', 'origin': '17_93~CUW~17_56#MGNP'} Metrics: ['ELUC: -2.0950933927158983', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.22412918252851824', 'is_elite: False']\n", + "Id: 18_14 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_21', '17_74'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_14', 'origin': '17_21~CUW~17_74#MGNP'} Metrics: ['ELUC: -2.6085482478722866', 'NSGA-II_crowding_distance: 0.8395303977485362', 'NSGA-II_rank: 6', 'change: 0.22272585722400837', 'is_elite: False']\n", + "Id: 18_75 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '16_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_75', 'origin': '1_1~CUW~16_93#MGNP'} Metrics: ['ELUC: -2.6566303324290246', 'NSGA-II_crowding_distance: 0.3830744223082047', 'NSGA-II_rank: 3', 'change: 0.06846492434457366', 'is_elite: False']\n", + "Id: 17_74 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_93', '16_85'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_74', 'origin': '16_93~CUW~16_85#MGNP'} Metrics: ['ELUC: -2.9910728758205263', 'NSGA-II_crowding_distance: 0.2624866455258259', 'NSGA-II_rank: 2', 'change: 0.05404598348340827', 'is_elite: False']\n", + "Id: 18_53 Identity: {'ancestor_count': 10, 'ancestor_ids': ['16_93', '17_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_53', 'origin': '16_93~CUW~17_93#MGNP'} Metrics: ['ELUC: -3.042512416101152', 'NSGA-II_crowding_distance: 0.13798073185116844', 'NSGA-II_rank: 1', 'change: 0.049402609986988845', 'is_elite: False']\n", + "Id: 18_72 Identity: {'ancestor_count': 13, 'ancestor_ids': ['17_74', '17_52'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_72', 'origin': '17_74~CUW~17_52#MGNP'} Metrics: ['ELUC: -3.678122050532041', 'NSGA-II_crowding_distance: 0.22049959863655735', 'NSGA-II_rank: 2', 'change: 0.07044976463992449', 'is_elite: False']\n", + "Id: 18_28 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_96', '17_74'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_28', 'origin': '17_96~CUW~17_74#MGNP'} Metrics: ['ELUC: -3.7113715322156704', 'NSGA-II_crowding_distance: 0.11282036884100419', 'NSGA-II_rank: 1', 'change: 0.05795272497136448', 'is_elite: False']\n", + "Id: 18_15 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '17_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_15', 'origin': '16_23~CUW~17_93#MGNP'} Metrics: ['ELUC: -3.9675392268234595', 'NSGA-II_crowding_distance: 0.17537598343443356', 'NSGA-II_rank: 3', 'change: 0.08676976227987933', 'is_elite: False']\n", + "Id: 18_34 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_34', 'origin': '16_23~CUW~16_93#MGNP'} Metrics: ['ELUC: -4.231235093124825', 'NSGA-II_crowding_distance: 0.14388597730997077', 'NSGA-II_rank: 3', 'change: 0.0881566719787025', 'is_elite: False']\n", + "Id: 18_94 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_93', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_94', 'origin': '16_93~CUW~17_81#MGNP'} Metrics: ['ELUC: -4.241034188279847', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2709119606424586', 'is_elite: False']\n", + "Id: 16_93 Identity: {'ancestor_count': 8, 'ancestor_ids': ['15_91', '12_23'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_93', 'origin': '15_91~CUW~12_23#MGNP'} Metrics: ['ELUC: -4.38278791073638', 'NSGA-II_crowding_distance: 0.16848985740991157', 'NSGA-II_rank: 1', 'change: 0.06032080560269918', 'is_elite: False']\n", + "Id: 18_33 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '17_96'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_33', 'origin': '17_92~CUW~17_96#MGNP'} Metrics: ['ELUC: -4.680932684765789', 'NSGA-II_crowding_distance: 0.9469989800886829', 'NSGA-II_rank: 5', 'change: 0.10855851146210427', 'is_elite: False']\n", + "Id: 18_60 Identity: {'ancestor_count': 14, 'ancestor_ids': ['17_79', '16_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_60', 'origin': '17_79~CUW~16_93#MGNP'} Metrics: ['ELUC: -4.786545016248649', 'NSGA-II_crowding_distance: 0.4471771555997497', 'NSGA-II_rank: 4', 'change: 0.10246903144133176', 'is_elite: False']\n", + "Id: 18_51 Identity: {'ancestor_count': 15, 'ancestor_ids': ['1_1', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_51', 'origin': '1_1~CUW~17_81#MGNP'} Metrics: ['ELUC: -4.87674228879482', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2955573924791617', 'is_elite: False']\n", + "Id: 18_100 Identity: {'ancestor_count': 16, 'ancestor_ids': ['16_23', '17_92'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_100', 'origin': '16_23~CUW~17_92#MGNP'} Metrics: ['ELUC: -4.947904852479304', 'NSGA-II_crowding_distance: 0.32908861163065567', 'NSGA-II_rank: 4', 'change: 0.11999856779682998', 'is_elite: False']\n", + "Id: 18_39 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_96', '17_96'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_39', 'origin': '17_96~CUW~17_96#MGNP'} Metrics: ['ELUC: -5.054352513715158', 'NSGA-II_crowding_distance: 0.20661870166995927', 'NSGA-II_rank: 2', 'change: 0.08156745009310311', 'is_elite: False']\n", + "Id: 18_30 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_85', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_30', 'origin': '17_85~CUW~16_23#MGNP'} Metrics: ['ELUC: -5.3353843787035355', 'NSGA-II_crowding_distance: 0.26240030789275137', 'NSGA-II_rank: 3', 'change: 0.1017312764638889', 'is_elite: False']\n", + "Id: 17_85 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_93'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_85', 'origin': '16_23~CUW~16_93#MGNP'} Metrics: ['ELUC: -5.344585391507659', 'NSGA-II_crowding_distance: 0.127111860886208', 'NSGA-II_rank: 1', 'change: 0.08051020102415904', 'is_elite: False']\n", + "Id: 18_96 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_96', '17_96'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_96', 'origin': '17_96~CUW~17_96#MGNP'} Metrics: ['ELUC: -5.411319627605325', 'NSGA-II_crowding_distance: 0.2458500837482791', 'NSGA-II_rank: 2', 'change: 0.099486684251095', 'is_elite: False']\n", + "Id: 18_86 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_52', '17_65'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_86', 'origin': '17_52~CUW~17_65#MGNP'} Metrics: ['ELUC: -5.425811909720902', 'NSGA-II_crowding_distance: 0.04628680169836473', 'NSGA-II_rank: 1', 'change: 0.08054771343437774', 'is_elite: False']\n", + "Id: 18_64 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_96', '17_74'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_64', 'origin': '17_96~CUW~17_74#MGNP'} Metrics: ['ELUC: -5.644636971938881', 'NSGA-II_crowding_distance: 0.223047047270252', 'NSGA-II_rank: 1', 'change: 0.0892291833343783', 'is_elite: False']\n", + "Id: 18_88 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_21', '16_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_88', 'origin': '17_21~CUW~16_93#MGNP'} Metrics: ['ELUC: -6.188339581992862', 'NSGA-II_crowding_distance: 0.21753411579854814', 'NSGA-II_rank: 3', 'change: 0.12389045213031262', 'is_elite: False']\n", + "Id: 18_50 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_23', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_50', 'origin': '16_23~CUW~17_81#MGNP'} Metrics: ['ELUC: -6.343122336859255', 'NSGA-II_crowding_distance: 0.8072826746407421', 'NSGA-II_rank: 8', 'change: 0.25850146909719', 'is_elite: False']\n", + "Id: 18_37 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_93', '17_58'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_37', 'origin': '16_93~CUW~17_58#MGNP'} Metrics: ['ELUC: -6.370832274391518', 'NSGA-II_crowding_distance: 0.4202297211695397', 'NSGA-II_rank: 5', 'change: 0.16049832933035071', 'is_elite: False']\n", + "Id: 18_74 Identity: {'ancestor_count': 14, 'ancestor_ids': ['17_79', '2_49'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_74', 'origin': '17_79~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.740464059476664', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.277128181239654', 'is_elite: False']\n", + "Id: 18_26 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '17_14'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_26', 'origin': '1_1~CUW~17_14#MGNP'} Metrics: ['ELUC: -6.86302597495694', 'NSGA-II_crowding_distance: 0.4324693574871443', 'NSGA-II_rank: 4', 'change: 0.15390534440775333', 'is_elite: False']\n", + "Id: 18_76 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_21', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_76', 'origin': '17_21~CUW~17_81#MGNP'} Metrics: ['ELUC: -6.881959653255413', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2741881474130163', 'is_elite: False']\n", + "Id: 18_97 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_14', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_97', 'origin': '17_14~CUW~16_23#MGNP'} Metrics: ['ELUC: -7.117122432094274', 'NSGA-II_crowding_distance: 0.33124948341200655', 'NSGA-II_rank: 5', 'change: 0.16659380390425269', 'is_elite: False']\n", + "Id: 18_87 Identity: {'ancestor_count': 14, 'ancestor_ids': ['17_79', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_87', 'origin': '17_79~CUW~16_23#MGNP'} Metrics: ['ELUC: -7.131342414536844', 'NSGA-II_crowding_distance: 0.20293289685893834', 'NSGA-II_rank: 3', 'change: 0.12862758056716794', 'is_elite: False']\n", + "Id: 16_23 Identity: {'ancestor_count': 13, 'ancestor_ids': ['15_47', '15_47'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_23', 'origin': '15_47~CUW~15_47#MGNP'} Metrics: ['ELUC: -7.228773498269304', 'NSGA-II_crowding_distance: 0.18440179871882276', 'NSGA-II_rank: 2', 'change: 0.11429840444908353', 'is_elite: False']\n", + "Id: 18_68 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_68', 'origin': '16_23~CUW~16_23#MGNP'} Metrics: ['ELUC: -7.300140673713553', 'NSGA-II_crowding_distance: 0.16075391322052707', 'NSGA-II_rank: 2', 'change: 0.11985292022694319', 'is_elite: False']\n", + "Id: 18_61 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_61', 'origin': '16_23~CUW~16_23#MGNP'} Metrics: ['ELUC: -7.426158630280423', 'NSGA-II_crowding_distance: 0.42182036749763596', 'NSGA-II_rank: 1', 'change: 0.11315348130605205', 'is_elite: True']\n", + "Id: 18_40 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '17_14'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_40', 'origin': '1_1~CUW~17_14#MGNP'} Metrics: ['ELUC: -7.791393798730591', 'NSGA-II_crowding_distance: 0.31876662149914226', 'NSGA-II_rank: 3', 'change: 0.15011903248030276', 'is_elite: False']\n", + "Id: 18_65 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '17_21'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_65', 'origin': '17_92~CUW~17_21#MGNP'} Metrics: ['ELUC: -7.918447695339485', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2507903830685099', 'is_elite: False']\n", + "Id: 18_19 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_21', '17_74'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_19', 'origin': '17_21~CUW~17_74#MGNP'} Metrics: ['ELUC: -8.089852149926399', 'NSGA-II_crowding_distance: 1.028877657787928', 'NSGA-II_rank: 6', 'change: 0.2277575484538709', 'is_elite: False']\n", + "Id: 18_20 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_39', '17_21'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_20', 'origin': '16_39~CUW~17_21#MGNP'} Metrics: ['ELUC: -8.169603315130258', 'NSGA-II_crowding_distance: 0.6020838221143142', 'NSGA-II_rank: 5', 'change: 0.20788932257856746', 'is_elite: False']\n", + "Id: 18_77 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '17_52'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_77', 'origin': '16_23~CUW~17_52#MGNP'} Metrics: ['ELUC: -8.199195820600655', 'NSGA-II_crowding_distance: 0.2816215847505384', 'NSGA-II_rank: 2', 'change: 0.14302320795555754', 'is_elite: False']\n", + "Id: 18_63 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_58', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_63', 'origin': '17_58~CUW~17_81#MGNP'} Metrics: ['ELUC: -8.666052323454625', 'NSGA-II_crowding_distance: 0.4847364547627283', 'NSGA-II_rank: 6', 'change: 0.2784370623330209', 'is_elite: False']\n", + "Id: 18_36 Identity: {'ancestor_count': 9, 'ancestor_ids': ['2_49', '16_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_36', 'origin': '2_49~CUW~16_93#MGNP'} Metrics: ['ELUC: -8.743495548258078', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3015618155104276', 'is_elite: False']\n", + "Id: 18_49 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_85', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_49', 'origin': '17_85~CUW~17_81#MGNP'} Metrics: ['ELUC: -8.97835187529633', 'NSGA-II_crowding_distance: 0.4397877803708573', 'NSGA-II_rank: 5', 'change: 0.27177765589053543', 'is_elite: False']\n", + "Id: 18_84 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_84', 'origin': '17_92~CUW~16_39#MGNP'} Metrics: ['ELUC: -9.714809413264456', 'NSGA-II_crowding_distance: 0.8347818594367632', 'NSGA-II_rank: 4', 'change: 0.15981409797629997', 'is_elite: False']\n", + "Id: 18_35 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '2_49'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_35', 'origin': '17_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.899959917046115', 'NSGA-II_crowding_distance: 0.3761463303153341', 'NSGA-II_rank: 5', 'change: 0.2797048752896943', 'is_elite: False']\n", + "Id: 18_89 Identity: {'ancestor_count': 16, 'ancestor_ids': ['16_39', '17_92'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_89', 'origin': '16_39~CUW~17_92#MGNP'} Metrics: ['ELUC: -10.272386489018684', 'NSGA-II_crowding_distance: 0.2009575180089393', 'NSGA-II_rank: 2', 'change: 0.149535251833449', 'is_elite: False']\n", + "Id: 18_62 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_62', 'origin': '17_92~CUW~16_23#MGNP'} Metrics: ['ELUC: -10.465986055371069', 'NSGA-II_crowding_distance: 0.861970111870483', 'NSGA-II_rank: 3', 'change: 0.1569891802627751', 'is_elite: False']\n", + "Id: 16_39 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_30', '14_68'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_39', 'origin': '15_30~CUW~14_68#MGNP'} Metrics: ['ELUC: -10.836219152912104', 'NSGA-II_crowding_distance: 0.26989236025067087', 'NSGA-II_rank: 1', 'change: 0.12698823097443232', 'is_elite: True']\n", + "Id: 18_48 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_14', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_48', 'origin': '17_14~CUW~16_39#MGNP'} Metrics: ['ELUC: -10.878777900793333', 'NSGA-II_crowding_distance: 0.36502328857093036', 'NSGA-II_rank: 2', 'change: 0.15513979592224494', 'is_elite: False']\n", + "Id: 18_82 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_82', 'origin': '16_39~CUW~16_39#MGNP'} Metrics: ['ELUC: -11.023772665326469', 'NSGA-II_crowding_distance: 0.2571706160491905', 'NSGA-II_rank: 1', 'change: 0.13263072804064843', 'is_elite: True']\n", + "Id: 18_11 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_79', '17_63'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_11', 'origin': '17_79~CUW~17_63#MGNP'} Metrics: ['ELUC: -11.865567946738192', 'NSGA-II_crowding_distance: 0.7100253887810314', 'NSGA-II_rank: 2', 'change: 0.2246630090534666', 'is_elite: False']\n", + "Id: 17_92 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_14', '16_77'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_92', 'origin': '16_14~CUW~16_77#MGNP'} Metrics: ['ELUC: -12.816296316029963', 'NSGA-II_crowding_distance: 0.23986791983565448', 'NSGA-II_rank: 1', 'change: 0.1701196919408194', 'is_elite: True']\n", + "Id: 18_78 Identity: {'ancestor_count': 10, 'ancestor_ids': ['2_49', '17_74'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_78', 'origin': '2_49~CUW~17_74#MGNP'} Metrics: ['ELUC: -12.85934006377579', 'NSGA-II_crowding_distance: 0.8905033410559711', 'NSGA-II_rank: 4', 'change: 0.2744448205442899', 'is_elite: False']\n", + "Id: 18_17 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_39', '17_85'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_17', 'origin': '16_39~CUW~17_85#MGNP'} Metrics: ['ELUC: -12.989900177126414', 'NSGA-II_crowding_distance: 0.07843022708577368', 'NSGA-II_rank: 1', 'change: 0.17083617994005296', 'is_elite: False']\n", + "Id: 18_56 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_81', '17_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_56', 'origin': '17_81~CUW~17_93#MGNP'} Metrics: ['ELUC: -13.070417933920355', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2978742422299824', 'is_elite: False']\n", + "Id: 18_98 Identity: {'ancestor_count': 16, 'ancestor_ids': ['16_39', '17_92'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_98', 'origin': '16_39~CUW~17_92#MGNP'} Metrics: ['ELUC: -13.459820128066127', 'NSGA-II_crowding_distance: 0.2349710969145321', 'NSGA-II_rank: 1', 'change: 0.18260072643281455', 'is_elite: True']\n", + "Id: 18_24 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_23', '17_81'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_24', 'origin': '16_23~CUW~17_81#MGNP'} Metrics: ['ELUC: -13.804289910324599', 'NSGA-II_crowding_distance: 0.697918939905856', 'NSGA-II_rank: 3', 'change: 0.27404415183845576', 'is_elite: False']\n", + "Id: 18_31 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_81', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_31', 'origin': '17_81~CUW~16_39#MGNP'} Metrics: ['ELUC: -14.241678524574054', 'NSGA-II_crowding_distance: 0.226210177253361', 'NSGA-II_rank: 3', 'change: 0.27451021832917866', 'is_elite: False']\n", + "Id: 18_54 Identity: {'ancestor_count': 14, 'ancestor_ids': ['17_79', '17_79'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_54', 'origin': '17_79~CUW~17_79#MGNP'} Metrics: ['ELUC: -14.729305461542118', 'NSGA-II_crowding_distance: 0.2214299023141666', 'NSGA-II_rank: 1', 'change: 0.21142807507577416', 'is_elite: False']\n", + "Id: 18_25 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_58', '17_14'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_25', 'origin': '17_58~CUW~17_14#MGNP'} Metrics: ['ELUC: -14.947190778265314', 'NSGA-II_crowding_distance: 0.2612442416019846', 'NSGA-II_rank: 1', 'change: 0.22342933628542452', 'is_elite: True']\n", + "Id: 18_42 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_58', '2_49'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_42', 'origin': '17_58~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.581345914514076', 'NSGA-II_crowding_distance: 0.29795874282265483', 'NSGA-II_rank: 4', 'change: 0.2956237717010264', 'is_elite: False']\n", + "Id: 18_41 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_41', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.228251088262656', 'NSGA-II_crowding_distance: 0.23881992317827833', 'NSGA-II_rank: 3', 'change: 0.2932657983482207', 'is_elite: False']\n", + "Id: 18_57 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_63', '17_14'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_57', 'origin': '17_63~CUW~17_14#MGNP'} Metrics: ['ELUC: -16.24766924807193', 'NSGA-II_crowding_distance: 0.5375315435164367', 'NSGA-II_rank: 2', 'change: 0.2644472052903946', 'is_elite: False']\n", + "Id: 18_95 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_63', '17_92'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_95', 'origin': '17_63~CUW~17_92#MGNP'} Metrics: ['ELUC: -16.27648787615776', 'NSGA-II_crowding_distance: 0.30071108264300367', 'NSGA-II_rank: 1', 'change: 0.2631213724101363', 'is_elite: True']\n", + "Id: 18_90 Identity: {'ancestor_count': 10, 'ancestor_ids': ['17_93', '2_49'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_90', 'origin': '17_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.382955315800547', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2986141572271528', 'is_elite: False']\n", + "Id: 18_71 Identity: {'ancestor_count': 16, 'ancestor_ids': ['2_49', '17_14'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_71', 'origin': '2_49~CUW~17_14#MGNP'} Metrics: ['ELUC: -16.598824842671757', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2979781942326918', 'is_elite: False']\n", + "Id: 18_45 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_81', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_45', 'origin': '17_81~CUW~16_39#MGNP'} Metrics: ['ELUC: -16.659252967714785', 'NSGA-II_crowding_distance: 0.15248536435351734', 'NSGA-II_rank: 2', 'change: 0.2955859720687483', 'is_elite: False']\n", + "Id: 18_23 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_81', '16_93'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_23', 'origin': '17_81~CUW~16_93#MGNP'} Metrics: ['ELUC: -16.771453522260728', 'NSGA-II_crowding_distance: 0.10066454632099436', 'NSGA-II_rank: 1', 'change: 0.2821965208662987', 'is_elite: False']\n", + "Id: 18_55 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_81', '17_79'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_55', 'origin': '17_81~CUW~17_79#MGNP'} Metrics: ['ELUC: -16.84207188760519', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.29698529526986706', 'is_elite: False']\n", + "Id: 18_32 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_39', '17_63'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_32', 'origin': '16_39~CUW~17_63#MGNP'} Metrics: ['ELUC: -16.91383896956728', 'NSGA-II_crowding_distance: 0.11676570496502059', 'NSGA-II_rank: 1', 'change: 0.28234138519349883', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 17_81 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_45', '16_88'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_81', 'origin': '16_45~CUW~16_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 18_47 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_47', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 18.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 19...:\n", + "PopulationResponse:\n", + " Generation: 19\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/19/20240219-215720\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 19 and asking ESP for generation 20...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 19 data persisted.\n", + "Evaluated candidates:\n", + "Id: 19_54 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_47', '18_64'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_54', 'origin': '18_47~CUW~18_64#MGNP'} Metrics: ['ELUC: 23.83088259435244', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3037806926179459', 'is_elite: False']\n", + "Id: 19_41 Identity: {'ancestor_count': 9, 'ancestor_ids': ['16_93', '18_47'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_41', 'origin': '16_93~CUW~18_47#MGNP'} Metrics: ['ELUC: 16.044115974547392', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2976507094435097', 'is_elite: False']\n", + "Id: 19_98 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_85', '18_47'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_98', 'origin': '17_85~CUW~18_47#MGNP'} Metrics: ['ELUC: 14.631563275326535', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28669194229865325', 'is_elite: False']\n", + "Id: 19_52 Identity: {'ancestor_count': 16, 'ancestor_ids': ['2_49', '17_92'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_52', 'origin': '2_49~CUW~17_92#MGNP'} Metrics: ['ELUC: 4.852011120279665', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2501972870478521', 'is_elite: False']\n", + "Id: 19_51 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_25', '18_85'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_51', 'origin': '18_25~CUW~18_85#MGNP'} Metrics: ['ELUC: 3.1173306459915975', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1331288396651481', 'is_elite: False']\n", + "Id: 19_34 Identity: {'ancestor_count': 15, 'ancestor_ids': ['2_49', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_34', 'origin': '2_49~CUW~18_61#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 19_63 Identity: {'ancestor_count': 16, 'ancestor_ids': ['2_49', '18_64'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_63', 'origin': '2_49~CUW~18_64#MGNP'} Metrics: ['ELUC: 2.0487745551419017', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.2523248145610158', 'is_elite: False']\n", + "Id: 19_80 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_85', '18_28'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_80', 'origin': '18_85~CUW~18_28#MGNP'} Metrics: ['ELUC: 1.2599502833060214', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05728303757523982', 'is_elite: False']\n", + "Id: 19_59 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_53', '17_92'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_59', 'origin': '18_53~CUW~17_92#MGNP'} Metrics: ['ELUC: 1.1874431126384062', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11696110550701219', 'is_elite: False']\n", + "Id: 19_99 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_99', 'origin': '18_64~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.5908480440171074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2395023739850955', 'is_elite: False']\n", + "Id: 19_67 Identity: {'ancestor_count': 13, 'ancestor_ids': ['18_16', '18_82'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_67', 'origin': '18_16~CUW~18_82#MGNP'} Metrics: ['ELUC: 0.3709497742533205', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06834534001431918', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 19_24 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_24', 'origin': '18_64~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.06567923338495682', 'NSGA-II_crowding_distance: 0.3283832080257416', 'NSGA-II_rank: 4', 'change: 0.062342450610749583', 'is_elite: False']\n", + "Id: 19_83 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '18_64'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_83', 'origin': '1_1~CUW~18_64#MGNP'} Metrics: ['ELUC: -0.3407953888936116', 'NSGA-II_crowding_distance: 0.20992412322721227', 'NSGA-II_rank: 1', 'change: 0.032063668024333754', 'is_elite: True']\n", + "Id: 19_76 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '18_98'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_76', 'origin': '1_1~CUW~18_98#MGNP'} Metrics: ['ELUC: -0.4185491541960968', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05364793445894275', 'is_elite: False']\n", + "Id: 19_69 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_47', '18_95'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_69', 'origin': '18_47~CUW~18_95#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 19_88 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '18_47'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_88', 'origin': '18_64~CUW~18_47#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 19_64 Identity: {'ancestor_count': 9, 'ancestor_ids': ['18_47', '16_93'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_64', 'origin': '18_47~CUW~16_93#MGNP'} Metrics: ['ELUC: -0.572733295603155', 'NSGA-II_crowding_distance: 1.6419278242356585', 'NSGA-II_rank: 7', 'change: 0.23235270209598233', 'is_elite: False']\n", + "Id: 19_19 Identity: {'ancestor_count': 12, 'ancestor_ids': ['18_47', '16_39'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_19', 'origin': '18_47~CUW~16_39#MGNP'} Metrics: ['ELUC: -0.6017864087096534', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.28096732293032', 'is_elite: False']\n", + "Id: 19_30 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_30', 'origin': '17_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6188348852065101', 'NSGA-II_crowding_distance: 0.4787185543520228', 'NSGA-II_rank: 6', 'change: 0.12184869469692478', 'is_elite: False']\n", + "Id: 19_68 Identity: {'ancestor_count': 9, 'ancestor_ids': ['18_85', '16_93'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_68', 'origin': '18_85~CUW~16_93#MGNP'} Metrics: ['ELUC: -1.3411763876289298', 'NSGA-II_crowding_distance: 0.11710828030037385', 'NSGA-II_rank: 3', 'change: 0.05632975822927234', 'is_elite: False']\n", + "Id: 19_45 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_61', '18_25'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_45', 'origin': '18_61~CUW~18_25#MGNP'} Metrics: ['ELUC: -1.4723298828562268', 'NSGA-II_crowding_distance: 0.48274794701183366', 'NSGA-II_rank: 5', 'change: 0.11459353346618502', 'is_elite: False']\n", + "Id: 19_84 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_84', 'origin': '18_64~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5910316764481789', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.044822555708123685', 'is_elite: False']\n", + "Id: 19_33 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_33', 'origin': '18_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6314634390002674', 'NSGA-II_crowding_distance: 0.11073576246061534', 'NSGA-II_rank: 3', 'change: 0.06522523366955475', 'is_elite: False']\n", + "Id: 19_49 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_28', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_49', 'origin': '18_28~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.942257266450099', 'NSGA-II_crowding_distance: 0.17583302175804968', 'NSGA-II_rank: 1', 'change: 0.03457408670804184', 'is_elite: False']\n", + "Id: 19_18 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '18_54'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_18', 'origin': '18_64~CUW~18_54#MGNP'} Metrics: ['ELUC: -1.9830340866902774', 'NSGA-II_crowding_distance: 0.7559577449651542', 'NSGA-II_rank: 6', 'change: 0.1482805050941278', 'is_elite: False']\n", + "Id: 19_66 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_47', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_66', 'origin': '18_47~CUW~18_61#MGNP'} Metrics: ['ELUC: -2.2433133110970225', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27315276210728917', 'is_elite: False']\n", + "Id: 19_71 Identity: {'ancestor_count': 13, 'ancestor_ids': ['18_82', '16_93'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_71', 'origin': '18_82~CUW~16_93#MGNP'} Metrics: ['ELUC: -2.254628943259018', 'NSGA-II_crowding_distance: 0.5161936007467265', 'NSGA-II_rank: 4', 'change: 0.07137069000451395', 'is_elite: False']\n", + "Id: 19_77 Identity: {'ancestor_count': 15, 'ancestor_ids': ['1_1', '18_54'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_77', 'origin': '1_1~CUW~18_54#MGNP'} Metrics: ['ELUC: -2.5197720669049244', 'NSGA-II_crowding_distance: 0.7638866405021817', 'NSGA-II_rank: 5', 'change: 0.12156817736077202', 'is_elite: False']\n", + "Id: 19_91 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_25', '18_28'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_91', 'origin': '18_25~CUW~18_28#MGNP'} Metrics: ['ELUC: -2.5964116701941062', 'NSGA-II_crowding_distance: 0.3155096003204324', 'NSGA-II_rank: 3', 'change: 0.06557427419919433', 'is_elite: False']\n", + "Id: 19_14 Identity: {'ancestor_count': 15, 'ancestor_ids': ['1_1', '17_85'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_14', 'origin': '1_1~CUW~17_85#MGNP'} Metrics: ['ELUC: -2.626594273477358', 'NSGA-II_crowding_distance: 0.19876068840720867', 'NSGA-II_rank: 2', 'change: 0.04794392899315181', 'is_elite: False']\n", + "Id: 19_87 Identity: {'ancestor_count': 9, 'ancestor_ids': ['1_1', '16_93'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_87', 'origin': '1_1~CUW~16_93#MGNP'} Metrics: ['ELUC: -2.71947028316858', 'NSGA-II_crowding_distance: 0.14323242181736778', 'NSGA-II_rank: 1', 'change: 0.044161477180812106', 'is_elite: False']\n", + "Id: 19_79 Identity: {'ancestor_count': 11, 'ancestor_ids': ['18_53', '18_53'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_79', 'origin': '18_53~CUW~18_53#MGNP'} Metrics: ['ELUC: -3.262193037622384', 'NSGA-II_crowding_distance: 0.1216689869909374', 'NSGA-II_rank: 1', 'change: 0.054911732555438235', 'is_elite: False']\n", + "Id: 19_39 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '18_28'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_39', 'origin': '18_64~CUW~18_28#MGNP'} Metrics: ['ELUC: -3.482465835195778', 'NSGA-II_crowding_distance: 0.2753291263917523', 'NSGA-II_rank: 2', 'change: 0.06561929363064939', 'is_elite: False']\n", + "Id: 19_97 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '16_93'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_97', 'origin': '18_64~CUW~16_93#MGNP'} Metrics: ['ELUC: -3.628832126757202', 'NSGA-II_crowding_distance: 0.21852051250545185', 'NSGA-II_rank: 1', 'change: 0.06503264070744653', 'is_elite: True']\n", + "Id: 19_17 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '18_28'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_17', 'origin': '1_1~CUW~18_28#MGNP'} Metrics: ['ELUC: -4.2054741628243395', 'NSGA-II_crowding_distance: 0.21109634873372005', 'NSGA-II_rank: 2', 'change: 0.0935678552426486', 'is_elite: False']\n", + "Id: 19_26 Identity: {'ancestor_count': 15, 'ancestor_ids': ['1_1', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_26', 'origin': '1_1~CUW~18_61#MGNP'} Metrics: ['ELUC: -4.625698830719698', 'NSGA-II_crowding_distance: 0.46598497700333197', 'NSGA-II_rank: 4', 'change: 0.09999459804311889', 'is_elite: False']\n", + "Id: 19_15 Identity: {'ancestor_count': 13, 'ancestor_ids': ['18_82', '18_85'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_15', 'origin': '18_82~CUW~18_85#MGNP'} Metrics: ['ELUC: -4.661940222943215', 'NSGA-II_crowding_distance: 0.3102819111489532', 'NSGA-II_rank: 4', 'change: 0.1328370741305268', 'is_elite: False']\n", + "Id: 19_85 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_85', 'origin': '18_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.84608327618014', 'NSGA-II_crowding_distance: 0.4374361000670789', 'NSGA-II_rank: 3', 'change: 0.09725237577604028', 'is_elite: False']\n", + "Id: 19_42 Identity: {'ancestor_count': 15, 'ancestor_ids': ['17_85', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_42', 'origin': '17_85~CUW~18_61#MGNP'} Metrics: ['ELUC: -5.1261448649486825', 'NSGA-II_crowding_distance: 0.22022923323430157', 'NSGA-II_rank: 2', 'change: 0.09360395584954567', 'is_elite: False']\n", + "Id: 19_28 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_98', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_28', 'origin': '18_98~CUW~18_61#MGNP'} Metrics: ['ELUC: -5.290281630692534', 'NSGA-II_crowding_distance: 0.24863459393110698', 'NSGA-II_rank: 3', 'change: 0.13769220372162075', 'is_elite: False']\n", + "Id: 19_92 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '18_47'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_92', 'origin': '18_61~CUW~18_47#MGNP'} Metrics: ['ELUC: -5.340180502121819', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.25135522216936623', 'is_elite: False']\n", + "Id: 19_81 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_85', '18_95'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_81', 'origin': '18_85~CUW~18_95#MGNP'} Metrics: ['ELUC: -5.751370397286511', 'NSGA-II_crowding_distance: 0.5936860843006255', 'NSGA-II_rank: 6', 'change: 0.16916317512942797', 'is_elite: False']\n", + "Id: 19_70 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_93', '17_85'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_70', 'origin': '16_93~CUW~17_85#MGNP'} Metrics: ['ELUC: -5.973529773684329', 'NSGA-II_crowding_distance: 0.2545780047164946', 'NSGA-II_rank: 1', 'change: 0.07410116366262981', 'is_elite: True']\n", + "Id: 19_72 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '18_25'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_72', 'origin': '1_1~CUW~18_25#MGNP'} Metrics: ['ELUC: -6.026985896340117', 'NSGA-II_crowding_distance: 0.18240534839131176', 'NSGA-II_rank: 1', 'change: 0.10029563538065052', 'is_elite: False']\n", + "Id: 19_90 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '18_85'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_90', 'origin': '17_92~CUW~18_85#MGNP'} Metrics: ['ELUC: -6.247575865333612', 'NSGA-II_crowding_distance: 0.44695340197468353', 'NSGA-II_rank: 4', 'change: 0.14061829749428342', 'is_elite: False']\n", + "Id: 19_31 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '16_93'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_31', 'origin': '18_95~CUW~16_93#MGNP'} Metrics: ['ELUC: -6.304894860300919', 'NSGA-II_crowding_distance: 0.2753184598048618', 'NSGA-II_rank: 3', 'change: 0.1393809948627861', 'is_elite: False']\n", + "Id: 19_20 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_53', '18_32'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_20', 'origin': '18_53~CUW~18_32#MGNP'} Metrics: ['ELUC: -6.888134032820539', 'NSGA-II_crowding_distance: 0.34136732845182177', 'NSGA-II_rank: 6', 'change: 0.1705633453945201', 'is_elite: False']\n", + "Id: 19_75 Identity: {'ancestor_count': 3, 'ancestor_ids': ['18_47', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_75', 'origin': '18_47~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.89022830150412', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25802260411693956', 'is_elite: False']\n", + "Id: 19_48 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_48', 'origin': '18_61~CUW~18_61#MGNP'} Metrics: ['ELUC: -6.926662638312275', 'NSGA-II_crowding_distance: 0.47742800802105645', 'NSGA-II_rank: 2', 'change: 0.1065094918406861', 'is_elite: False']\n", + "Id: 19_27 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_25', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_27', 'origin': '18_25~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.979198073428359', 'NSGA-II_crowding_distance: 1.0571728952028043', 'NSGA-II_rank: 7', 'change: 0.24371661971953099', 'is_elite: False']\n", + "Id: 19_86 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_86', 'origin': '18_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.005560324421222', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.30470724414391975', 'is_elite: False']\n", + "Id: 19_25 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_85', '18_64'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_25', 'origin': '17_85~CUW~18_64#MGNP'} Metrics: ['ELUC: -7.367499311629576', 'NSGA-II_crowding_distance: 0.12267081835299845', 'NSGA-II_rank: 1', 'change: 0.1048707619694893', 'is_elite: False']\n", + "Id: 18_61 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_61', 'origin': '16_23~CUW~16_23#MGNP'} Metrics: ['ELUC: -7.426158630280423', 'NSGA-II_crowding_distance: 0.27141006100150117', 'NSGA-II_rank: 1', 'change: 0.11315348130605205', 'is_elite: True']\n", + "Id: 19_56 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_98', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_56', 'origin': '18_98~CUW~18_61#MGNP'} Metrics: ['ELUC: -7.462107479057579', 'NSGA-II_crowding_distance: 0.8714858929502534', 'NSGA-II_rank: 5', 'change: 0.16485094856807248', 'is_elite: False']\n", + "Id: 19_100 Identity: {'ancestor_count': 17, 'ancestor_ids': ['16_93', '18_25'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_100', 'origin': '16_93~CUW~18_25#MGNP'} Metrics: ['ELUC: -8.545356863237231', 'NSGA-II_crowding_distance: 0.9275953613473518', 'NSGA-II_rank: 6', 'change: 0.18242537180172155', 'is_elite: False']\n", + "Id: 19_82 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '16_39'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_82', 'origin': '18_64~CUW~16_39#MGNP'} Metrics: ['ELUC: -9.058337805587465', 'NSGA-II_crowding_distance: 0.33593763753447425', 'NSGA-II_rank: 4', 'change: 0.1582360102299384', 'is_elite: False']\n", + "Id: 19_37 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_37', 'origin': '17_92~CUW~18_61#MGNP'} Metrics: ['ELUC: -9.08074942181909', 'NSGA-II_crowding_distance: 0.28241826567678013', 'NSGA-II_rank: 3', 'change: 0.15015028773496242', 'is_elite: False']\n", + "Id: 19_35 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_47', '18_54'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_35', 'origin': '18_47~CUW~18_54#MGNP'} Metrics: ['ELUC: -9.280687405737403', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.295064964722748', 'is_elite: False']\n", + "Id: 19_40 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '18_82'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_40', 'origin': '18_61~CUW~18_82#MGNP'} Metrics: ['ELUC: -9.296447070560754', 'NSGA-II_crowding_distance: 0.3282565756401592', 'NSGA-II_rank: 2', 'change: 0.14958183311488463', 'is_elite: False']\n", + "Id: 19_95 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '18_95'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_95', 'origin': '1_1~CUW~18_95#MGNP'} Metrics: ['ELUC: -9.355974258624684', 'NSGA-II_crowding_distance: 0.0807087458330419', 'NSGA-II_rank: 2', 'change: 0.15207088966586002', 'is_elite: False']\n", + "Id: 19_94 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_61', '18_95'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_94', 'origin': '18_61~CUW~18_95#MGNP'} Metrics: ['ELUC: -9.389389336023159', 'NSGA-II_crowding_distance: 0.8798033791230128', 'NSGA-II_rank: 5', 'change: 0.17803785282594653', 'is_elite: False']\n", + "Id: 19_23 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_23', 'origin': '16_39~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.479200235170143', 'NSGA-II_crowding_distance: 0.758678412996243', 'NSGA-II_rank: 4', 'change: 0.16087859425513176', 'is_elite: False']\n", + "Id: 19_62 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_98', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_62', 'origin': '18_98~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.657869217731092', 'NSGA-II_crowding_distance: 0.6524148604089537', 'NSGA-II_rank: 3', 'change: 0.1605741684918716', 'is_elite: False']\n", + "Id: 19_50 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_50', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.212612836649217', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.3222531711084156', 'is_elite: False']\n", + "Id: 19_16 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '16_39'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_16', 'origin': '18_61~CUW~16_39#MGNP'} Metrics: ['ELUC: -10.276147967806015', 'NSGA-II_crowding_distance: 0.10953329682453201', 'NSGA-II_rank: 2', 'change: 0.15460806682681263', 'is_elite: False']\n", + "Id: 19_12 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_82', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_12', 'origin': '18_82~CUW~18_61#MGNP'} Metrics: ['ELUC: -10.718056338690669', 'NSGA-II_crowding_distance: 0.12509348193970116', 'NSGA-II_rank: 2', 'change: 0.15836751105953492', 'is_elite: False']\n", + "Id: 16_39 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_30', '14_68'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_39', 'origin': '15_30~CUW~14_68#MGNP'} Metrics: ['ELUC: -10.836219152912104', 'NSGA-II_crowding_distance: 0.26989236025067087', 'NSGA-II_rank: 1', 'change: 0.12698823097443232', 'is_elite: True']\n", + "Id: 18_82 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_39'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_82', 'origin': '16_39~CUW~16_39#MGNP'} Metrics: ['ELUC: -11.023772665326469', 'NSGA-II_crowding_distance: 0.1377450473238507', 'NSGA-II_rank: 1', 'change: 0.13263072804064843', 'is_elite: False']\n", + "Id: 19_29 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '16_93'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_29', 'origin': '18_95~CUW~16_93#MGNP'} Metrics: ['ELUC: -11.22617944387956', 'NSGA-II_crowding_distance: 0.18038521606398356', 'NSGA-II_rank: 2', 'change: 0.17157902153996443', 'is_elite: False']\n", + "Id: 19_53 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_82', '18_61'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_53', 'origin': '18_82~CUW~18_61#MGNP'} Metrics: ['ELUC: -11.799523167929589', 'NSGA-II_crowding_distance: 0.16815900558595087', 'NSGA-II_rank: 1', 'change: 0.15174071736693015', 'is_elite: False']\n", + "Id: 19_65 Identity: {'ancestor_count': 11, 'ancestor_ids': ['18_16', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_65', 'origin': '18_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.111307380438799', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2722390118811147', 'is_elite: False']\n", + "Id: 19_13 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_61', '18_98'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_13', 'origin': '18_61~CUW~18_98#MGNP'} Metrics: ['ELUC: -12.420421314048511', 'NSGA-II_crowding_distance: 0.11942556872533981', 'NSGA-II_rank: 1', 'change: 0.15910406980757524', 'is_elite: False']\n", + "Id: 19_61 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '17_92'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_61', 'origin': '17_92~CUW~17_92#MGNP'} Metrics: ['ELUC: -12.77375998734499', 'NSGA-II_crowding_distance: 0.13280381256057516', 'NSGA-II_rank: 2', 'change: 0.17176443892360607', 'is_elite: False']\n", + "Id: 17_92 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_14', '16_77'], 'birth_generation': 17, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '17_92', 'origin': '16_14~CUW~16_77#MGNP'} Metrics: ['ELUC: -12.816296316029963', 'NSGA-II_crowding_distance: 0.08827053107594958', 'NSGA-II_rank: 1', 'change: 0.1701196919408194', 'is_elite: False']\n", + "Id: 19_21 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_92', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_21', 'origin': '17_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.924525986100619', 'NSGA-II_crowding_distance: 1.0363292597713067', 'NSGA-II_rank: 3', 'change: 0.2604459432256956', 'is_elite: False']\n", + "Id: 19_46 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_98', '17_92'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_46', 'origin': '18_98~CUW~17_92#MGNP'} Metrics: ['ELUC: -12.961438390758502', 'NSGA-II_crowding_distance: 0.08941006184846141', 'NSGA-II_rank: 2', 'change: 0.17785995572061075', 'is_elite: False']\n", + "Id: 19_74 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_98', '18_98'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_74', 'origin': '18_98~CUW~18_98#MGNP'} Metrics: ['ELUC: -13.225439706242222', 'NSGA-II_crowding_distance: 0.07843022708577368', 'NSGA-II_rank: 1', 'change: 0.1717806189201831', 'is_elite: False']\n", + "Id: 19_43 Identity: {'ancestor_count': 17, 'ancestor_ids': ['17_92', '18_98'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_43', 'origin': '17_92~CUW~18_98#MGNP'} Metrics: ['ELUC: -13.426614060779915', 'NSGA-II_crowding_distance: 0.1290502365511637', 'NSGA-II_rank: 2', 'change: 0.18431713189920979', 'is_elite: False']\n", + "Id: 18_98 Identity: {'ancestor_count': 16, 'ancestor_ids': ['16_39', '17_92'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_98', 'origin': '16_39~CUW~17_92#MGNP'} Metrics: ['ELUC: -13.459820128066127', 'NSGA-II_crowding_distance: 0.13460042182991355', 'NSGA-II_rank: 1', 'change: 0.18260072643281455', 'is_elite: False']\n", + "Id: 19_58 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_54', '18_82'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_58', 'origin': '18_54~CUW~18_82#MGNP'} Metrics: ['ELUC: -13.529246941241404', 'NSGA-II_crowding_distance: 0.23202248382616103', 'NSGA-II_rank: 2', 'change: 0.20202609413039038', 'is_elite: False']\n", + "Id: 19_38 Identity: {'ancestor_count': 17, 'ancestor_ids': ['17_85', '18_95'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_38', 'origin': '17_85~CUW~18_95#MGNP'} Metrics: ['ELUC: -13.946047008004074', 'NSGA-II_crowding_distance: 0.21887914281913884', 'NSGA-II_rank: 1', 'change: 0.1997134571605113', 'is_elite: True']\n", + "Id: 19_73 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_98', '18_32'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_73', 'origin': '18_98~CUW~18_32#MGNP'} Metrics: ['ELUC: -14.635118017896565', 'NSGA-II_crowding_distance: 0.4847783776311132', 'NSGA-II_rank: 2', 'change: 0.22473573981922398', 'is_elite: False']\n", + "Id: 19_36 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_54', '18_82'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_36', 'origin': '18_54~CUW~18_82#MGNP'} Metrics: ['ELUC: -14.940686288735835', 'NSGA-II_crowding_distance: 0.1364230485917012', 'NSGA-II_rank: 1', 'change: 0.22277862968917322', 'is_elite: False']\n", + "Id: 18_25 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_58', '17_14'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_25', 'origin': '17_58~CUW~17_14#MGNP'} Metrics: ['ELUC: -14.947190778265314', 'NSGA-II_crowding_distance: 0.008734776177712941', 'NSGA-II_rank: 1', 'change: 0.22342933628542452', 'is_elite: False']\n", + "Id: 19_32 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_25', '18_64'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_32', 'origin': '18_25~CUW~18_64#MGNP'} Metrics: ['ELUC: -14.964852102933538', 'NSGA-II_crowding_distance: 0.051489849240110214', 'NSGA-II_rank: 1', 'change: 0.22497479092657527', 'is_elite: False']\n", + "Id: 19_57 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_25', '18_98'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_57', 'origin': '18_25~CUW~18_98#MGNP'} Metrics: ['ELUC: -15.217680535055363', 'NSGA-II_crowding_distance: 0.20244623458597075', 'NSGA-II_rank: 1', 'change: 0.23420246528611674', 'is_elite: False']\n", + "Id: 19_22 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_22', 'origin': '16_39~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.089110654877974', 'NSGA-II_crowding_distance: 0.4310585314627844', 'NSGA-II_rank: 2', 'change: 0.2859120189726088', 'is_elite: False']\n", + "Id: 18_95 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_63', '17_92'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_95', 'origin': '17_63~CUW~17_92#MGNP'} Metrics: ['ELUC: -16.27648787615776', 'NSGA-II_crowding_distance: 0.31432557284378243', 'NSGA-II_rank: 1', 'change: 0.2631213724101363', 'is_elite: True']\n", + "Id: 19_11 Identity: {'ancestor_count': 12, 'ancestor_ids': ['2_49', '16_39'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_11', 'origin': '2_49~CUW~16_39#MGNP'} Metrics: ['ELUC: -16.797272238827958', 'NSGA-II_crowding_distance: 0.16028030032241958', 'NSGA-II_rank: 2', 'change: 0.3011678373443743', 'is_elite: False']\n", + "Id: 19_60 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_47', '17_85'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_60', 'origin': '18_47~CUW~17_85#MGNP'} Metrics: ['ELUC: -16.901052964353497', 'NSGA-II_crowding_distance: 0.2082255235118376', 'NSGA-II_rank: 1', 'change: 0.29942286239372656', 'is_elite: False']\n", + "Id: 19_47 Identity: {'ancestor_count': 13, 'ancestor_ids': ['2_49', '18_82'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_47', 'origin': '2_49~CUW~18_82#MGNP'} Metrics: ['ELUC: -17.064659546872925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3153199358050395', 'is_elite: False']\n", + "Id: 19_89 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_89', 'origin': '18_61~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.585758776621415', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3031443993978469', 'is_elite: False']\n", + "Id: 19_96 Identity: {'ancestor_count': 17, 'ancestor_ids': ['2_49', '18_25'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_96', 'origin': '2_49~CUW~18_25#MGNP'} Metrics: ['ELUC: -17.58873217391003', 'NSGA-II_crowding_distance: 0.05166136552413164', 'NSGA-II_rank: 1', 'change: 0.30298203806532864', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 18_47 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_47', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 19_44 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_44', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 19_55 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_55', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 19_78 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '18_47'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_78', 'origin': '2_49~CUW~18_47#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 19_93 Identity: {'ancestor_count': 3, 'ancestor_ids': ['18_47', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_93', 'origin': '18_47~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 19.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 20...:\n", + "PopulationResponse:\n", + " Generation: 20\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/20/20240219-220431\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 20 and asking ESP for generation 21...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 20 data persisted.\n", + "Evaluated candidates:\n", + "Id: 20_95 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_93', '19_70'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_95', 'origin': '19_93~CUW~19_70#MGNP'} Metrics: ['ELUC: 23.832748235123404', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.30378709381264773', 'is_elite: False']\n", + "Id: 20_72 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_72', 'origin': '16_39~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.820132491095997', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3037374665389416', 'is_elite: False']\n", + "Id: 20_42 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_57', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_42', 'origin': '19_57~CUW~2_49#MGNP'} Metrics: ['ELUC: 14.929967583714701', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2907879361214068', 'is_elite: False']\n", + "Id: 20_25 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_25', 'origin': '1_1~CUW~19_60#MGNP'} Metrics: ['ELUC: 12.463805413753862', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25031095263756886', 'is_elite: False']\n", + "Id: 20_86 Identity: {'ancestor_count': 4, 'ancestor_ids': ['19_93', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_86', 'origin': '19_93~CUW~1_1#MGNP'} Metrics: ['ELUC: 10.250431923012465', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.3095991601221923', 'is_elite: False']\n", + "Id: 20_56 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_93', '18_98'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_56', 'origin': '19_93~CUW~18_98#MGNP'} Metrics: ['ELUC: 7.587934551170945', 'NSGA-II_crowding_distance: 0.5891181915961726', 'NSGA-II_rank: 8', 'change: 0.2548158452413967', 'is_elite: False']\n", + "Id: 20_91 Identity: {'ancestor_count': 4, 'ancestor_ids': ['2_49', '19_93'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_91', 'origin': '2_49~CUW~19_93#MGNP'} Metrics: ['ELUC: 7.074462759086354', 'NSGA-II_crowding_distance: 1.688955946886835', 'NSGA-II_rank: 8', 'change: 0.26843563066741816', 'is_elite: False']\n", + "Id: 20_13 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_13', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.2507996831493915', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.047669465083449374', 'is_elite: False']\n", + "Id: 20_62 Identity: {'ancestor_count': 4, 'ancestor_ids': ['19_93', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_62', 'origin': '19_93~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.9663027653728375', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2436003903977392', 'is_elite: False']\n", + "Id: 20_52 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_97', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_52', 'origin': '19_97~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.9446838478885535', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3479255677027348', 'is_elite: False']\n", + "Id: 20_74 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_97', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_74', 'origin': '19_97~CUW~19_60#MGNP'} Metrics: ['ELUC: 1.8590035997047678', 'NSGA-II_crowding_distance: 0.7705009816604617', 'NSGA-II_rank: 7', 'change: 0.2550024108705096', 'is_elite: False']\n", + "Id: 20_73 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_73', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.7229251339682417', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05494248119856059', 'is_elite: False']\n", + "Id: 20_76 Identity: {'ancestor_count': 18, 'ancestor_ids': ['2_49', '19_72'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_76', 'origin': '2_49~CUW~19_72#MGNP'} Metrics: ['ELUC: 0.7166093011143707', 'NSGA-II_crowding_distance: 1.6926624321125172', 'NSGA-II_rank: 7', 'change: 0.288601137201457', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 20_21 Identity: {'ancestor_count': 18, 'ancestor_ids': ['1_1', '19_57'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_21', 'origin': '1_1~CUW~19_57#MGNP'} Metrics: ['ELUC: -0.0837282917591488', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.13799970060896177', 'is_elite: False']\n", + "Id: 20_94 Identity: {'ancestor_count': 13, 'ancestor_ids': ['1_1', '18_82'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_94', 'origin': '1_1~CUW~18_82#MGNP'} Metrics: ['ELUC: -0.2277529104037133', 'NSGA-II_crowding_distance: 0.3264020158304133', 'NSGA-II_rank: 4', 'change: 0.06511867026413695', 'is_elite: False']\n", + "Id: 19_83 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '18_64'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_83', 'origin': '1_1~CUW~18_64#MGNP'} Metrics: ['ELUC: -0.3407953888936116', 'NSGA-II_crowding_distance: 0.16669197570257224', 'NSGA-II_rank: 1', 'change: 0.032063668024333754', 'is_elite: False']\n", + "Id: 20_44 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_72', '19_83'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_44', 'origin': '19_72~CUW~19_83#MGNP'} Metrics: ['ELUC: -0.49630461205189663', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05061549640075027', 'is_elite: False']\n", + "Id: 20_20 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '19_93'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_20', 'origin': '18_61~CUW~19_93#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.6099990761906958', 'NSGA-II_rank: 6', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 20_22 Identity: {'ancestor_count': 13, 'ancestor_ids': ['2_49', '18_82'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_22', 'origin': '2_49~CUW~18_82#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 6', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 20_68 Identity: {'ancestor_count': 16, 'ancestor_ids': ['2_49', '19_53'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_68', 'origin': '2_49~CUW~19_53#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.04049605938381636', 'NSGA-II_rank: 6', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 20_28 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_36', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_28', 'origin': '19_36~CUW~19_60#MGNP'} Metrics: ['ELUC: -0.5888199245451184', 'NSGA-II_crowding_distance: 0.23246152881459348', 'NSGA-II_rank: 6', 'change: 0.23889889764085714', 'is_elite: False']\n", + "Id: 20_66 Identity: {'ancestor_count': 10, 'ancestor_ids': ['19_87', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_66', 'origin': '19_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.651442048184405', 'NSGA-II_crowding_distance: 0.15828362465815587', 'NSGA-II_rank: 1', 'change: 0.043580109383918', 'is_elite: False']\n", + "Id: 20_58 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_38', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_58', 'origin': '19_38~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.678111209304615', 'NSGA-II_crowding_distance: 0.3456106280933403', 'NSGA-II_rank: 4', 'change: 0.09558625020902052', 'is_elite: False']\n", + "Id: 20_69 Identity: {'ancestor_count': 10, 'ancestor_ids': ['1_1', '19_87'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_69', 'origin': '1_1~CUW~19_87#MGNP'} Metrics: ['ELUC: -2.026965952865477', 'NSGA-II_crowding_distance: 0.27945153847542414', 'NSGA-II_rank: 3', 'change: 0.05263151965798909', 'is_elite: False']\n", + "Id: 20_15 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '19_97'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_15', 'origin': '1_1~CUW~19_97#MGNP'} Metrics: ['ELUC: -2.0378712232312224', 'NSGA-II_crowding_distance: 0.3650263988994883', 'NSGA-II_rank: 2', 'change: 0.04874341081298975', 'is_elite: False']\n", + "Id: 20_75 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_97', '19_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_75', 'origin': '19_97~CUW~19_49#MGNP'} Metrics: ['ELUC: -2.1761941440268004', 'NSGA-II_crowding_distance: 0.1336531223489522', 'NSGA-II_rank: 1', 'change: 0.04814469168699524', 'is_elite: False']\n", + "Id: 20_92 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_93', '19_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_92', 'origin': '19_93~CUW~19_49#MGNP'} Metrics: ['ELUC: -2.5473586778085306', 'NSGA-II_crowding_distance: 0.5685812865467184', 'NSGA-II_rank: 6', 'change: 0.2501557463370447', 'is_elite: False']\n", + "Id: 20_30 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_49', '19_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_30', 'origin': '19_49~CUW~19_49#MGNP'} Metrics: ['ELUC: -2.566267874972999', 'NSGA-II_crowding_distance: 0.12915650938486406', 'NSGA-II_rank: 1', 'change: 0.05096403818084455', 'is_elite: False']\n", + "Id: 20_35 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '19_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_35', 'origin': '18_95~CUW~19_49#MGNP'} Metrics: ['ELUC: -3.018286033714183', 'NSGA-II_crowding_distance: 0.33713876715522795', 'NSGA-II_rank: 4', 'change: 0.10478054699034464', 'is_elite: False']\n", + "Id: 20_63 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_97', '19_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_63', 'origin': '19_97~CUW~19_49#MGNP'} Metrics: ['ELUC: -3.204687674639312', 'NSGA-II_crowding_distance: 0.23352043746332146', 'NSGA-II_rank: 3', 'change: 0.07775516101699455', 'is_elite: False']\n", + "Id: 19_97 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_64', '16_93'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_97', 'origin': '18_64~CUW~16_93#MGNP'} Metrics: ['ELUC: -3.628832126757202', 'NSGA-II_crowding_distance: 0.22854732434528946', 'NSGA-II_rank: 2', 'change: 0.06503264070744653', 'is_elite: False']\n", + "Id: 20_78 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_97', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_78', 'origin': '19_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.711133621167099', 'NSGA-II_crowding_distance: 0.27133195949850747', 'NSGA-II_rank: 1', 'change: 0.06063371980756515', 'is_elite: True']\n", + "Id: 20_32 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_72', '19_70'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_32', 'origin': '19_72~CUW~19_70#MGNP'} Metrics: ['ELUC: -4.012960481675903', 'NSGA-II_crowding_distance: 0.2487697197256074', 'NSGA-II_rank: 3', 'change: 0.08020177291652067', 'is_elite: False']\n", + "Id: 20_84 Identity: {'ancestor_count': 13, 'ancestor_ids': ['18_82', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_84', 'origin': '18_82~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.028173010768095', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11382021520050516', 'is_elite: False']\n", + "Id: 20_87 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_61', '19_97'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_87', 'origin': '18_61~CUW~19_97#MGNP'} Metrics: ['ELUC: -4.314218734049846', 'NSGA-II_crowding_distance: 0.10353613650698494', 'NSGA-II_rank: 2', 'change: 0.07770342397672739', 'is_elite: False']\n", + "Id: 20_39 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_53', '19_83'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_39', 'origin': '19_53~CUW~19_83#MGNP'} Metrics: ['ELUC: -4.603378227589585', 'NSGA-II_crowding_distance: 0.11344914260495587', 'NSGA-II_rank: 2', 'change: 0.07888182333130393', 'is_elite: False']\n", + "Id: 20_19 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '16_39'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_19', 'origin': '18_61~CUW~16_39#MGNP'} Metrics: ['ELUC: -5.305784316187099', 'NSGA-II_crowding_distance: 0.3927899221190005', 'NSGA-II_rank: 4', 'change: 0.10837369981090073', 'is_elite: False']\n", + "Id: 20_50 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_70', '18_61'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_50', 'origin': '19_70~CUW~18_61#MGNP'} Metrics: ['ELUC: -5.583513155571663', 'NSGA-II_crowding_distance: 0.41481273680281017', 'NSGA-II_rank: 3', 'change: 0.1024831240675775', 'is_elite: False']\n", + "Id: 20_38 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_70', '19_97'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_38', 'origin': '19_70~CUW~19_97#MGNP'} Metrics: ['ELUC: -5.930455220941734', 'NSGA-II_crowding_distance: 0.25573897773379595', 'NSGA-II_rank: 2', 'change: 0.08581820532593869', 'is_elite: False']\n", + "Id: 19_70 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_93', '17_85'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_70', 'origin': '16_93~CUW~17_85#MGNP'} Metrics: ['ELUC: -5.973529773684329', 'NSGA-II_crowding_distance: 0.31470978050343057', 'NSGA-II_rank: 1', 'change: 0.07410116366262981', 'is_elite: True']\n", + "Id: 20_17 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_93', '19_72'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_17', 'origin': '19_93~CUW~19_72#MGNP'} Metrics: ['ELUC: -6.183958782826768', 'NSGA-II_crowding_distance: 0.9261870679351392', 'NSGA-II_rank: 6', 'change: 0.25676524568498155', 'is_elite: False']\n", + "Id: 20_34 Identity: {'ancestor_count': 15, 'ancestor_ids': ['1_1', '18_61'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_34', 'origin': '1_1~CUW~18_61#MGNP'} Metrics: ['ELUC: -6.372290106593158', 'NSGA-II_crowding_distance: 0.2135007875077576', 'NSGA-II_rank: 1', 'change: 0.10937545916441486', 'is_elite: False']\n", + "Id: 20_60 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '16_39'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_60', 'origin': '18_61~CUW~16_39#MGNP'} Metrics: ['ELUC: -6.590837536943257', 'NSGA-II_crowding_distance: 0.24188213425753308', 'NSGA-II_rank: 2', 'change: 0.11849371625604242', 'is_elite: False']\n", + "Id: 20_77 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_49', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_77', 'origin': '19_49~CUW~18_95#MGNP'} Metrics: ['ELUC: -6.696024857846419', 'NSGA-II_crowding_distance: 1.2274755781527926', 'NSGA-II_rank: 5', 'change: 0.1380900412853406', 'is_elite: False']\n", + "Id: 20_70 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_38', '18_61'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_70', 'origin': '19_38~CUW~18_61#MGNP'} Metrics: ['ELUC: -7.264666012784981', 'NSGA-II_crowding_distance: 0.37878197959695725', 'NSGA-II_rank: 4', 'change: 0.13524531005441598', 'is_elite: False']\n", + "Id: 18_61 Identity: {'ancestor_count': 14, 'ancestor_ids': ['16_23', '16_23'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_61', 'origin': '16_23~CUW~16_23#MGNP'} Metrics: ['ELUC: -7.426158630280423', 'NSGA-II_crowding_distance: 0.19276004997765006', 'NSGA-II_rank: 1', 'change: 0.11315348130605205', 'is_elite: False']\n", + "Id: 20_67 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_97', '19_72'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_67', 'origin': '19_97~CUW~19_72#MGNP'} Metrics: ['ELUC: -7.736560774123738', 'NSGA-II_crowding_distance: 0.3619239958477328', 'NSGA-II_rank: 3', 'change: 0.1257216752214397', 'is_elite: False']\n", + "Id: 20_64 Identity: {'ancestor_count': 15, 'ancestor_ids': ['18_61', '19_87'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_64', 'origin': '18_61~CUW~19_87#MGNP'} Metrics: ['ELUC: -7.79338397937598', 'NSGA-II_crowding_distance: 0.31398900557198134', 'NSGA-II_rank: 2', 'change: 0.12350063732094253', 'is_elite: False']\n", + "Id: 20_45 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_83', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_45', 'origin': '19_83~CUW~18_95#MGNP'} Metrics: ['ELUC: -8.131729114347015', 'NSGA-II_crowding_distance: 0.22281639709369705', 'NSGA-II_rank: 4', 'change: 0.1550015972635062', 'is_elite: False']\n", + "Id: 20_54 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_83', '19_53'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_54', 'origin': '19_83~CUW~19_53#MGNP'} Metrics: ['ELUC: -8.146406454095864', 'NSGA-II_crowding_distance: 0.23988795594265486', 'NSGA-II_rank: 3', 'change: 0.15430153883752218', 'is_elite: False']\n", + "Id: 20_55 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '19_93'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_55', 'origin': '18_95~CUW~19_93#MGNP'} Metrics: ['ELUC: -8.48699668594748', 'NSGA-II_crowding_distance: 1.4007167310292268', 'NSGA-II_rank: 5', 'change: 0.2495759690952788', 'is_elite: False']\n", + "Id: 20_18 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_98', '19_97'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_18', 'origin': '18_98~CUW~19_97#MGNP'} Metrics: ['ELUC: -8.673744213506493', 'NSGA-II_crowding_distance: 0.6931700702050823', 'NSGA-II_rank: 4', 'change: 0.1661166060184476', 'is_elite: False']\n", + "Id: 20_31 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_93', '19_53'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_31', 'origin': '19_93~CUW~19_53#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 20_41 Identity: {'ancestor_count': 15, 'ancestor_ids': ['19_93', '18_61'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_41', 'origin': '19_93~CUW~18_61#MGNP'} Metrics: ['ELUC: -9.018430321578958', 'NSGA-II_crowding_distance: 1.2294990183395385', 'NSGA-II_rank: 7', 'change: 0.30389563381646056', 'is_elite: False']\n", + "Id: 20_83 Identity: {'ancestor_count': 16, 'ancestor_ids': ['2_49', '19_70'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_83', 'origin': '2_49~CUW~19_70#MGNP'} Metrics: ['ELUC: -9.161086637557812', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.3119705182309403', 'is_elite: False']\n", + "Id: 20_26 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '18_98'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_26', 'origin': '1_1~CUW~18_98#MGNP'} Metrics: ['ELUC: -9.165634710076883', 'NSGA-II_crowding_distance: 0.2635100017365797', 'NSGA-II_rank: 3', 'change: 0.16482500864973382', 'is_elite: False']\n", + "Id: 20_81 Identity: {'ancestor_count': 17, 'ancestor_ids': ['16_39', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_81', 'origin': '16_39~CUW~18_95#MGNP'} Metrics: ['ELUC: -9.271583900826883', 'NSGA-II_crowding_distance: 0.2403146218850553', 'NSGA-II_rank: 1', 'change: 0.11768885314187973', 'is_elite: True']\n", + "Id: 20_89 Identity: {'ancestor_count': 18, 'ancestor_ids': ['1_1', '19_38'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_89', 'origin': '1_1~CUW~19_38#MGNP'} Metrics: ['ELUC: -10.124190713727295', 'NSGA-II_crowding_distance: 0.3959938626912225', 'NSGA-II_rank: 3', 'change: 0.19005720487496577', 'is_elite: False']\n", + "Id: 20_33 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_70', '16_39'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_33', 'origin': '19_70~CUW~16_39#MGNP'} Metrics: ['ELUC: -10.778971040002109', 'NSGA-II_crowding_distance: 0.388448690993783', 'NSGA-II_rank: 2', 'change: 0.1446228783315881', 'is_elite: False']\n", + "Id: 16_39 Identity: {'ancestor_count': 11, 'ancestor_ids': ['15_30', '14_68'], 'birth_generation': 16, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '16_39', 'origin': '15_30~CUW~14_68#MGNP'} Metrics: ['ELUC: -10.836219152912104', 'NSGA-II_crowding_distance: 0.1954865234035748', 'NSGA-II_rank: 1', 'change: 0.12698823097443232', 'is_elite: False']\n", + "Id: 20_36 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_39'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_36', 'origin': '16_39~CUW~16_39#MGNP'} Metrics: ['ELUC: -11.394431902903849', 'NSGA-II_crowding_distance: 0.2766109413413344', 'NSGA-II_rank: 1', 'change: 0.13999229039699218', 'is_elite: True']\n", + "Id: 20_80 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_61', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_80', 'origin': '18_61~CUW~19_60#MGNP'} Metrics: ['ELUC: -11.808079663951942', 'NSGA-II_crowding_distance: 0.7809235778787694', 'NSGA-II_rank: 6', 'change: 0.2772591516538153', 'is_elite: False']\n", + "Id: 20_93 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_38', '19_70'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_93', 'origin': '19_38~CUW~19_70#MGNP'} Metrics: ['ELUC: -11.830885301890666', 'NSGA-II_crowding_distance: 0.2119684994891221', 'NSGA-II_rank: 2', 'change: 0.1705525565106174', 'is_elite: False']\n", + "Id: 20_65 Identity: {'ancestor_count': 18, 'ancestor_ids': ['2_49', '19_38'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_65', 'origin': '2_49~CUW~19_38#MGNP'} Metrics: ['ELUC: -12.027087916159923', 'NSGA-II_crowding_distance: 0.7248117097754729', 'NSGA-II_rank: 4', 'change: 0.2576768393564489', 'is_elite: False']\n", + "Id: 20_61 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_93', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_61', 'origin': '19_93~CUW~18_95#MGNP'} Metrics: ['ELUC: -12.226945145953325', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.30370687730682616', 'is_elite: False']\n", + "Id: 20_100 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '19_97'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_100', 'origin': '18_95~CUW~19_97#MGNP'} Metrics: ['ELUC: -12.463346147607432', 'NSGA-II_crowding_distance: 0.4559733169731114', 'NSGA-II_rank: 3', 'change: 0.21281339921671727', 'is_elite: False']\n", + "Id: 20_23 Identity: {'ancestor_count': 17, 'ancestor_ids': ['16_39', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_23', 'origin': '16_39~CUW~18_95#MGNP'} Metrics: ['ELUC: -12.87189269722355', 'NSGA-II_crowding_distance: 0.21614863458163583', 'NSGA-II_rank: 2', 'change: 0.17171773743649366', 'is_elite: False']\n", + "Id: 20_57 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_60', '19_93'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_57', 'origin': '19_60~CUW~19_93#MGNP'} Metrics: ['ELUC: -13.00079670066567', 'NSGA-II_crowding_distance: 0.7725244218472075', 'NSGA-II_rank: 5', 'change: 0.271048836883977', 'is_elite: False']\n", + "Id: 20_29 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_49', '19_57'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_29', 'origin': '19_49~CUW~19_57#MGNP'} Metrics: ['ELUC: -13.21634781941735', 'NSGA-II_crowding_distance: 0.3038630918412264', 'NSGA-II_rank: 1', 'change: 0.16913125447266142', 'is_elite: True']\n", + "Id: 20_71 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_71', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.365840374468869', 'NSGA-II_crowding_distance: 0.2552793835883531', 'NSGA-II_rank: 4', 'change: 0.26506566890337263', 'is_elite: False']\n", + "Id: 20_51 Identity: {'ancestor_count': 15, 'ancestor_ids': ['19_93', '18_61'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_51', 'origin': '19_93~CUW~18_61#MGNP'} Metrics: ['ELUC: -13.36824982772749', 'NSGA-II_crowding_distance: 0.43535393553952584', 'NSGA-II_rank: 3', 'change: 0.2550733969466496', 'is_elite: False']\n", + "Id: 20_14 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_57', '19_53'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_14', 'origin': '19_57~CUW~19_53#MGNP'} Metrics: ['ELUC: -13.372273396646808', 'NSGA-II_crowding_distance: 0.1439967555160952', 'NSGA-II_rank: 1', 'change: 0.19709368556686677', 'is_elite: False']\n", + "Id: 20_47 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_38', '19_38'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_47', 'origin': '19_38~CUW~19_38#MGNP'} Metrics: ['ELUC: -13.680839493538105', 'NSGA-II_crowding_distance: 0.5592400363964555', 'NSGA-II_rank: 2', 'change: 0.20184131912601852', 'is_elite: False']\n", + "Id: 20_90 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_72', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_90', 'origin': '19_72~CUW~19_60#MGNP'} Metrics: ['ELUC: -13.788945481098057', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2899742457458701', 'is_elite: False']\n", + "Id: 19_38 Identity: {'ancestor_count': 17, 'ancestor_ids': ['17_85', '18_95'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_38', 'origin': '17_85~CUW~18_95#MGNP'} Metrics: ['ELUC: -13.946047008004074', 'NSGA-II_crowding_distance: 0.04516519847612198', 'NSGA-II_rank: 1', 'change: 0.1997134571605113', 'is_elite: False']\n", + "Id: 20_85 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_38', '19_38'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_85', 'origin': '19_38~CUW~19_38#MGNP'} Metrics: ['ELUC: -13.97736921358573', 'NSGA-II_crowding_distance: 0.31777620336254286', 'NSGA-II_rank: 1', 'change: 0.20030131177284127', 'is_elite: True']\n", + "Id: 20_49 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_83', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_49', 'origin': '19_83~CUW~19_60#MGNP'} Metrics: ['ELUC: -14.704006211033091', 'NSGA-II_crowding_distance: 0.15054189457727343', 'NSGA-II_rank: 4', 'change: 0.27860262141794784', 'is_elite: False']\n", + "Id: 20_82 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_57', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_82', 'origin': '19_57~CUW~19_60#MGNP'} Metrics: ['ELUC: -14.793732005572538', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2794547218989631', 'is_elite: False']\n", + "Id: 20_16 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_60', '18_98'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_16', 'origin': '19_60~CUW~18_98#MGNP'} Metrics: ['ELUC: -15.360793901933768', 'NSGA-II_crowding_distance: 0.3903714272415445', 'NSGA-II_rank: 3', 'change: 0.27841663185627746', 'is_elite: False']\n", + "Id: 20_46 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_49', '19_93'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_46', 'origin': '19_49~CUW~19_93#MGNP'} Metrics: ['ELUC: -15.692613599199602', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.31872733397857744', 'is_elite: False']\n", + "Id: 20_43 Identity: {'ancestor_count': 12, 'ancestor_ids': ['19_93', '16_39'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_43', 'origin': '19_93~CUW~16_39#MGNP'} Metrics: ['ELUC: -15.735780573795475', 'NSGA-II_crowding_distance: 0.46565812938565976', 'NSGA-II_rank: 2', 'change: 0.27742281386311907', 'is_elite: False']\n", + "Id: 20_48 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_36', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_48', 'origin': '19_36~CUW~18_95#MGNP'} Metrics: ['ELUC: -16.115977023354095', 'NSGA-II_crowding_distance: 0.3413016721762985', 'NSGA-II_rank: 1', 'change: 0.2577064133387535', 'is_elite: True']\n", + "Id: 18_95 Identity: {'ancestor_count': 16, 'ancestor_ids': ['17_63', '17_92'], 'birth_generation': 18, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '18_95', 'origin': '17_63~CUW~17_92#MGNP'} Metrics: ['ELUC: -16.27648787615776', 'NSGA-II_crowding_distance: 0.05959111775172865', 'NSGA-II_rank: 1', 'change: 0.2631213724101363', 'is_elite: False']\n", + "Id: 20_98 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_98', 'origin': '18_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.310980200563016', 'NSGA-II_crowding_distance: 0.14258332670421303', 'NSGA-II_rank: 2', 'change: 0.28669730776958935', 'is_elite: False']\n", + "Id: 20_96 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_96', 'origin': '18_95~CUW~18_95#MGNP'} Metrics: ['ELUC: -16.47661302902669', 'NSGA-II_crowding_distance: 0.1802853644370037', 'NSGA-II_rank: 1', 'change: 0.26936697069775106', 'is_elite: False']\n", + "Id: 20_27 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_57', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_27', 'origin': '19_57~CUW~19_60#MGNP'} Metrics: ['ELUC: -16.691519656458638', 'NSGA-II_crowding_distance: 0.12507541225468155', 'NSGA-II_rank: 2', 'change: 0.30146915567387705', 'is_elite: False']\n", + "Id: 20_40 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '19_60'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_40', 'origin': '1_1~CUW~19_60#MGNP'} Metrics: ['ELUC: -17.410222048830825', 'NSGA-II_crowding_distance: 0.17237650449655179', 'NSGA-II_rank: 1', 'change: 0.2976746890950414', 'is_elite: False']\n", + "Id: 20_37 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_38', '19_93'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_37', 'origin': '19_38~CUW~19_93#MGNP'} Metrics: ['ELUC: -17.551157903383118', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30261791198658383', 'is_elite: False']\n", + "Id: 20_88 Identity: {'ancestor_count': 16, 'ancestor_ids': ['2_49', '19_36'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_88', 'origin': '2_49~CUW~19_36#MGNP'} Metrics: ['ELUC: -17.566593820752335', 'NSGA-II_crowding_distance: 0.02645884352204686', 'NSGA-II_rank: 1', 'change: 0.3023029681883923', 'is_elite: False']\n", + "Id: 20_97 Identity: {'ancestor_count': 17, 'ancestor_ids': ['2_49', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_97', 'origin': '2_49~CUW~18_95#MGNP'} Metrics: ['ELUC: -17.569975353464127', 'NSGA-II_crowding_distance: 0.004156010588902163', 'NSGA-II_rank: 1', 'change: 0.302858355539639', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 19_93 Identity: {'ancestor_count': 3, 'ancestor_ids': ['18_47', '1_1'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_93', 'origin': '18_47~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 20_11 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_11', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 20_12 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_60', '16_39'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_12', 'origin': '19_60~CUW~16_39#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 20_24 Identity: {'ancestor_count': 17, 'ancestor_ids': ['18_95', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_24', 'origin': '18_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 20_53 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_93', '19_38'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_53', 'origin': '19_93~CUW~19_38#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 20_59 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_70', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_59', 'origin': '19_70~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 20_79 Identity: {'ancestor_count': 4, 'ancestor_ids': ['19_93', '19_93'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_79', 'origin': '19_93~CUW~19_93#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 20_99 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_99', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 20.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 21...:\n", + "PopulationResponse:\n", + " Generation: 21\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/21/20240219-221142\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 21 and asking ESP for generation 22...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 21 data persisted.\n", + "Evaluated candidates:\n", + "Id: 21_65 Identity: {'ancestor_count': 13, 'ancestor_ids': ['2_49', '20_36'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_65', 'origin': '2_49~CUW~20_36#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 21_73 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '20_29'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_73', 'origin': '2_49~CUW~20_29#MGNP'} Metrics: ['ELUC: 18.75323563556797', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2851755960684142', 'is_elite: False']\n", + "Id: 21_45 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_48', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_45', 'origin': '20_48~CUW~20_99#MGNP'} Metrics: ['ELUC: 6.466940296530286', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2528449687638198', 'is_elite: False']\n", + "Id: 21_49 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_70', '16_39'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_49', 'origin': '19_70~CUW~16_39#MGNP'} Metrics: ['ELUC: 5.402202431797294', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.12186817820423823', 'is_elite: False']\n", + "Id: 21_37 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_48', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_37', 'origin': '20_48~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.340985788337104', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.24860397743684187', 'is_elite: False']\n", + "Id: 21_12 Identity: {'ancestor_count': 11, 'ancestor_ids': ['20_99', '20_66'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_12', 'origin': '20_99~CUW~20_66#MGNP'} Metrics: ['ELUC: 3.4364592705305728', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2686028795897248', 'is_elite: False']\n", + "Id: 21_14 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_48', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_14', 'origin': '20_48~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.1514205608504393', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.24936423507089314', 'is_elite: False']\n", + "Id: 21_33 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_33', 'origin': '20_78~CUW~20_99#MGNP'} Metrics: ['ELUC: 2.9001016313941625', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.24015787018652673', 'is_elite: False']\n", + "Id: 21_100 Identity: {'ancestor_count': 16, 'ancestor_ids': ['16_39', '20_34'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_100', 'origin': '16_39~CUW~20_34#MGNP'} Metrics: ['ELUC: 2.6477747959896787', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.1338392494027316', 'is_elite: False']\n", + "Id: 21_80 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_48', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_80', 'origin': '20_48~CUW~20_99#MGNP'} Metrics: ['ELUC: 2.094283235456471', 'NSGA-II_crowding_distance: 1.016560094253028', 'NSGA-II_rank: 8', 'change: 0.23663293322281118', 'is_elite: False']\n", + "Id: 21_62 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_62', 'origin': '20_78~CUW~20_99#MGNP'} Metrics: ['ELUC: 1.7129521692070362', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24769454361945478', 'is_elite: False']\n", + "Id: 21_56 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_34', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_56', 'origin': '20_34~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.5097601277149786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.30164520979053866', 'is_elite: False']\n", + "Id: 21_91 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_91', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.38994574660032555', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04177865951908602', 'is_elite: False']\n", + "Id: 21_71 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '19_83'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_71', 'origin': '1_1~CUW~19_83#MGNP'} Metrics: ['ELUC: 0.16518312317333725', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.040408850630459646', 'is_elite: False']\n", + "Id: 21_96 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_99', '20_78'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_96', 'origin': '20_99~CUW~20_78#MGNP'} Metrics: ['ELUC: 0.0837026002214056', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26339929827008157', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 21_87 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_87', 'origin': '20_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.07709585036232353', 'NSGA-II_crowding_distance: 0.21759720857705206', 'NSGA-II_rank: 1', 'change: 0.04276661565544487', 'is_elite: True']\n", + "Id: 21_21 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_34', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_21', 'origin': '20_34~CUW~20_99#MGNP'} Metrics: ['ELUC: -0.39870140071174487', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.24121301939459386', 'is_elite: False']\n", + "Id: 21_57 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_83', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_57', 'origin': '19_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 1.32831295236238', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 21_85 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_85', 'origin': '1_1~CUW~19_70#MGNP'} Metrics: ['ELUC: -0.6213767981836712', 'NSGA-II_crowding_distance: 0.11819272447515572', 'NSGA-II_rank: 2', 'change: 0.04582889960451304', 'is_elite: False']\n", + "Id: 21_67 Identity: {'ancestor_count': 18, 'ancestor_ids': ['1_1', '20_96'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_67', 'origin': '1_1~CUW~20_96#MGNP'} Metrics: ['ELUC: -0.7598054579131767', 'NSGA-II_crowding_distance: 1.3803691678853318', 'NSGA-II_rank: 7', 'change: 0.1227500106145133', 'is_elite: False']\n", + "Id: 21_84 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_66', '20_34'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_84', 'origin': '20_66~CUW~20_34#MGNP'} Metrics: ['ELUC: -0.8512672965898964', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06824917656757068', 'is_elite: False']\n", + "Id: 21_95 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_40', '20_85'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_95', 'origin': '20_40~CUW~20_85#MGNP'} Metrics: ['ELUC: -1.0675037906855702', 'NSGA-II_crowding_distance: 1.1614389012764972', 'NSGA-II_rank: 7', 'change: 0.24040489627580347', 'is_elite: False']\n", + "Id: 21_88 Identity: {'ancestor_count': 19, 'ancestor_ids': ['1_1', '20_14'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_88', 'origin': '1_1~CUW~20_14#MGNP'} Metrics: ['ELUC: -1.1436566297558681', 'NSGA-II_crowding_distance: 0.14836702041798153', 'NSGA-II_rank: 4', 'change: 0.07227458323735167', 'is_elite: False']\n", + "Id: 21_25 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_25', 'origin': '20_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.447934252682714', 'NSGA-II_crowding_distance: 0.09241600704801865', 'NSGA-II_rank: 2', 'change: 0.04759800984801783', 'is_elite: False']\n", + "Id: 21_78 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_83', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_78', 'origin': '19_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5686729457063595', 'NSGA-II_crowding_distance: 0.1793132285503509', 'NSGA-II_rank: 1', 'change: 0.04320340542660836', 'is_elite: False']\n", + "Id: 21_79 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_70', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_79', 'origin': '19_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.756315540999827', 'NSGA-II_crowding_distance: 0.1544965341408405', 'NSGA-II_rank: 2', 'change: 0.0533185774186977', 'is_elite: False']\n", + "Id: 21_17 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_85', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_17', 'origin': '20_85~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8330531215653876', 'NSGA-II_crowding_distance: 0.35645706236514435', 'NSGA-II_rank: 4', 'change: 0.08881157426482461', 'is_elite: False']\n", + "Id: 21_23 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_23', 'origin': '1_1~CUW~19_70#MGNP'} Metrics: ['ELUC: -2.644099860165166', 'NSGA-II_crowding_distance: 0.18026993870527727', 'NSGA-II_rank: 1', 'change: 0.05270683783267013', 'is_elite: False']\n", + "Id: 21_27 Identity: {'ancestor_count': 16, 'ancestor_ids': ['1_1', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_27', 'origin': '1_1~CUW~19_70#MGNP'} Metrics: ['ELUC: -2.7545880543674595', 'NSGA-II_crowding_distance: 0.3177005471849634', 'NSGA-II_rank: 3', 'change: 0.06439710908201658', 'is_elite: False']\n", + "Id: 21_30 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_36', '20_34'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_30', 'origin': '20_36~CUW~20_34#MGNP'} Metrics: ['ELUC: -2.809948328965191', 'NSGA-II_crowding_distance: 0.17282414971945315', 'NSGA-II_rank: 3', 'change: 0.07441518331335988', 'is_elite: False']\n", + "Id: 21_38 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_66', '20_78'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_38', 'origin': '20_66~CUW~20_78#MGNP'} Metrics: ['ELUC: -3.212694760907301', 'NSGA-II_crowding_distance: 0.2624269885399195', 'NSGA-II_rank: 2', 'change: 0.06207897625701977', 'is_elite: False']\n", + "Id: 21_50 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '20_36'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_50', 'origin': '20_78~CUW~20_36#MGNP'} Metrics: ['ELUC: -3.266496570534933', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11645400902776909', 'is_elite: False']\n", + "Id: 21_83 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_34', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_83', 'origin': '20_34~CUW~20_99#MGNP'} Metrics: ['ELUC: -3.6080252589602173', 'NSGA-II_crowding_distance: 0.47883045899549914', 'NSGA-II_rank: 7', 'change: 0.259928310952705', 'is_elite: False']\n", + "Id: 20_78 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_97', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_78', 'origin': '19_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.711133621167099', 'NSGA-II_crowding_distance: 0.2063565625627034', 'NSGA-II_rank: 1', 'change: 0.06063371980756515', 'is_elite: True']\n", + "Id: 21_34 Identity: {'ancestor_count': 12, 'ancestor_ids': ['20_99', '16_39'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_34', 'origin': '20_99~CUW~16_39#MGNP'} Metrics: ['ELUC: -3.9118902429179916', 'NSGA-II_crowding_distance: 0.2536500631889047', 'NSGA-II_rank: 7', 'change: 0.2728657969553496', 'is_elite: False']\n", + "Id: 21_94 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_75', '20_34'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_94', 'origin': '20_75~CUW~20_34#MGNP'} Metrics: ['ELUC: -4.107613384022853', 'NSGA-II_crowding_distance: 0.2329421578173383', 'NSGA-II_rank: 3', 'change: 0.0890930202516883', 'is_elite: False']\n", + "Id: 21_98 Identity: {'ancestor_count': 16, 'ancestor_ids': ['2_49', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_98', 'origin': '2_49~CUW~19_70#MGNP'} Metrics: ['ELUC: -4.57542611534344', 'NSGA-II_crowding_distance: 0.9834399057469718', 'NSGA-II_rank: 8', 'change: 0.3125693088775407', 'is_elite: False']\n", + "Id: 21_29 Identity: {'ancestor_count': 19, 'ancestor_ids': ['18_61', '20_85'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_29', 'origin': '18_61~CUW~20_85#MGNP'} Metrics: ['ELUC: -4.671988845860085', 'NSGA-II_crowding_distance: 0.2988305039665683', 'NSGA-II_rank: 4', 'change: 0.10096341289232835', 'is_elite: False']\n", + "Id: 21_92 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_92', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.688709144466352', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3149861717988592', 'is_elite: False']\n", + "Id: 21_97 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_75', '20_36'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_97', 'origin': '20_75~CUW~20_36#MGNP'} Metrics: ['ELUC: -4.829044769000594', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.1055726201680252', 'is_elite: False']\n", + "Id: 21_15 Identity: {'ancestor_count': 16, 'ancestor_ids': ['19_70', '20_34'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_15', 'origin': '19_70~CUW~20_34#MGNP'} Metrics: ['ELUC: -4.993151856252798', 'NSGA-II_crowding_distance: 0.25641887769182', 'NSGA-II_rank: 2', 'change: 0.07437898362779011', 'is_elite: False']\n", + "Id: 21_90 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_90', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.237251993436683', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.27535690539381436', 'is_elite: False']\n", + "Id: 21_74 Identity: {'ancestor_count': 19, 'ancestor_ids': ['18_61', '20_29'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_74', 'origin': '18_61~CUW~20_29#MGNP'} Metrics: ['ELUC: -5.241174680420717', 'NSGA-II_crowding_distance: 0.39259888884030536', 'NSGA-II_rank: 4', 'change: 0.10488936814629057', 'is_elite: False']\n", + "Id: 21_11 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_36', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_11', 'origin': '20_36~CUW~19_70#MGNP'} Metrics: ['ELUC: -5.266687192944319', 'NSGA-II_crowding_distance: 0.17380991026770257', 'NSGA-II_rank: 1', 'change: 0.0697729220816203', 'is_elite: False']\n", + "Id: 21_42 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '20_34'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_42', 'origin': '20_78~CUW~20_34#MGNP'} Metrics: ['ELUC: -5.292845651984451', 'NSGA-II_crowding_distance: 0.36563322721824987', 'NSGA-II_rank: 3', 'change: 0.09589686619366845', 'is_elite: False']\n", + "Id: 21_72 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_34', '20_75'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_72', 'origin': '20_34~CUW~20_75#MGNP'} Metrics: ['ELUC: -5.651857820093903', 'NSGA-II_crowding_distance: 0.15106606041803455', 'NSGA-II_rank: 2', 'change: 0.09335506444062858', 'is_elite: False']\n", + "Id: 21_36 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_96', '20_78'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_36', 'origin': '20_96~CUW~20_78#MGNP'} Metrics: ['ELUC: -5.709491027847277', 'NSGA-II_crowding_distance: 1.3566595539109911', 'NSGA-II_rank: 6', 'change: 0.20125762796990174', 'is_elite: False']\n", + "Id: 21_61 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_78', '20_29'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_61', 'origin': '20_78~CUW~20_29#MGNP'} Metrics: ['ELUC: -5.907903806788979', 'NSGA-II_crowding_distance: 0.2771979870273932', 'NSGA-II_rank: 2', 'change: 0.10052632142920774', 'is_elite: False']\n", + "Id: 19_70 Identity: {'ancestor_count': 15, 'ancestor_ids': ['16_93', '17_85'], 'birth_generation': 19, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '19_70', 'origin': '16_93~CUW~17_85#MGNP'} Metrics: ['ELUC: -5.973529773684329', 'NSGA-II_crowding_distance: 0.12038603363535791', 'NSGA-II_rank: 1', 'change: 0.07410116366262981', 'is_elite: False']\n", + "Id: 21_28 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_96', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_28', 'origin': '20_96~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.975857305993449', 'NSGA-II_crowding_distance: 1.0883626730413645', 'NSGA-II_rank: 6', 'change: 0.274694999499873', 'is_elite: False']\n", + "Id: 21_18 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_18', 'origin': '20_81~CUW~19_70#MGNP'} Metrics: ['ELUC: -6.1254121519001385', 'NSGA-II_crowding_distance: 0.1611723599857648', 'NSGA-II_rank: 1', 'change: 0.091120604455248', 'is_elite: False']\n", + "Id: 21_19 Identity: {'ancestor_count': 16, 'ancestor_ids': ['16_39', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_19', 'origin': '16_39~CUW~19_70#MGNP'} Metrics: ['ELUC: -6.190005399842276', 'NSGA-II_crowding_distance: 1.3443566584808464', 'NSGA-II_rank: 5', 'change: 0.15482371089772423', 'is_elite: False']\n", + "Id: 21_81 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_61', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_81', 'origin': '18_61~CUW~19_70#MGNP'} Metrics: ['ELUC: -7.1497333512433885', 'NSGA-II_crowding_distance: 0.26798165199083535', 'NSGA-II_rank: 1', 'change: 0.10223086687595745', 'is_elite: True']\n", + "Id: 21_58 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_96', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_58', 'origin': '20_96~CUW~19_70#MGNP'} Metrics: ['ELUC: -7.3910659642970975', 'NSGA-II_crowding_distance: 0.9064004212534487', 'NSGA-II_rank: 4', 'change: 0.1532288233295791', 'is_elite: False']\n", + "Id: 21_99 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_78', '20_85'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_99', 'origin': '20_78~CUW~20_85#MGNP'} Metrics: ['ELUC: -7.580876465816638', 'NSGA-II_crowding_distance: 0.5502386901341124', 'NSGA-II_rank: 3', 'change: 0.1304035684554471', 'is_elite: False']\n", + "Id: 21_52 Identity: {'ancestor_count': 13, 'ancestor_ids': ['20_36', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_52', 'origin': '20_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.206833004609798', 'NSGA-II_crowding_distance: 0.999528200836392', 'NSGA-II_rank: 5', 'change: 0.24795695230946949', 'is_elite: False']\n", + "Id: 21_53 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_53', 'origin': '20_78~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.501115430170596', 'NSGA-II_crowding_distance: 0.6556433415191538', 'NSGA-II_rank: 5', 'change: 0.2660554831422651', 'is_elite: False']\n", + "Id: 21_46 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '20_81'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_46', 'origin': '20_81~CUW~20_81#MGNP'} Metrics: ['ELUC: -8.625774095358205', 'NSGA-II_crowding_distance: 0.5237832980823818', 'NSGA-II_rank: 2', 'change: 0.12218175312687225', 'is_elite: False']\n", + "Id: 21_41 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_99', '20_34'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_41', 'origin': '20_99~CUW~20_34#MGNP'} Metrics: ['ELUC: -8.635375665196404', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.302178997921869', 'is_elite: False']\n", + "Id: 20_81 Identity: {'ancestor_count': 17, 'ancestor_ids': ['16_39', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_81', 'origin': '16_39~CUW~18_95#MGNP'} Metrics: ['ELUC: -9.271583900826883', 'NSGA-II_crowding_distance: 0.2817773517793547', 'NSGA-II_rank: 1', 'change: 0.11768885314187973', 'is_elite: True']\n", + "Id: 21_47 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_85', '20_36'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_47', 'origin': '20_85~CUW~20_36#MGNP'} Metrics: ['ELUC: -10.231668334758446', 'NSGA-II_crowding_distance: 0.1954865234035748', 'NSGA-II_rank: 1', 'change: 0.13400556263840216', 'is_elite: True']\n", + "Id: 21_31 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_31', 'origin': '16_39~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.266399442374908', 'NSGA-II_crowding_distance: 0.3976831955047341', 'NSGA-II_rank: 3', 'change: 0.1626013716415487', 'is_elite: False']\n", + "Id: 21_69 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_85', '20_78'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_69', 'origin': '20_85~CUW~20_78#MGNP'} Metrics: ['ELUC: -10.458101403842432', 'NSGA-II_crowding_distance: 0.30552431714422756', 'NSGA-II_rank: 3', 'change: 0.19146077365550937', 'is_elite: False']\n", + "Id: 21_35 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '20_40'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_35', 'origin': '1_1~CUW~20_40#MGNP'} Metrics: ['ELUC: -10.70253695953664', 'NSGA-II_crowding_distance: 0.7656959240449632', 'NSGA-II_rank: 4', 'change: 0.24001094514968052', 'is_elite: False']\n", + "Id: 21_76 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_83', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_76', 'origin': '19_83~CUW~20_99#MGNP'} Metrics: ['ELUC: -11.292247199152337', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2788447335660152', 'is_elite: False']\n", + "Id: 20_36 Identity: {'ancestor_count': 12, 'ancestor_ids': ['16_39', '16_39'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_36', 'origin': '16_39~CUW~16_39#MGNP'} Metrics: ['ELUC: -11.394431902903849', 'NSGA-II_crowding_distance: 0.1795739763117717', 'NSGA-II_rank: 1', 'change: 0.13999229039699218', 'is_elite: False']\n", + "Id: 21_89 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_29', '20_96'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_89', 'origin': '20_29~CUW~20_96#MGNP'} Metrics: ['ELUC: -11.641949079784299', 'NSGA-II_crowding_distance: 0.4649469108609714', 'NSGA-II_rank: 2', 'change: 0.15330124609963147', 'is_elite: False']\n", + "Id: 21_26 Identity: {'ancestor_count': 17, 'ancestor_ids': ['20_99', '19_83'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_26', 'origin': '20_99~CUW~19_83#MGNP'} Metrics: ['ELUC: -11.905017834862232', 'NSGA-II_crowding_distance: 0.3669190387760167', 'NSGA-II_rank: 4', 'change: 0.2691391634459638', 'is_elite: False']\n", + "Id: 21_20 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_29', '20_85'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_20', 'origin': '20_29~CUW~20_85#MGNP'} Metrics: ['ELUC: -11.912497087995986', 'NSGA-II_crowding_distance: 0.6267353187403929', 'NSGA-II_rank: 3', 'change: 0.2196155059094522', 'is_elite: False']\n", + "Id: 21_64 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_85', '20_81'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_64', 'origin': '20_85~CUW~20_81#MGNP'} Metrics: ['ELUC: -12.439589857810397', 'NSGA-II_crowding_distance: 0.21631021459136862', 'NSGA-II_rank: 2', 'change: 0.1878958363352418', 'is_elite: False']\n", + "Id: 21_63 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_96', '20_29'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_63', 'origin': '20_96~CUW~20_29#MGNP'} Metrics: ['ELUC: -12.475419051213164', 'NSGA-II_crowding_distance: 0.18629200936372026', 'NSGA-II_rank: 1', 'change: 0.14950929414109448', 'is_elite: False']\n", + "Id: 21_82 Identity: {'ancestor_count': 18, 'ancestor_ids': ['2_49', '20_48'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_82', 'origin': '2_49~CUW~20_48#MGNP'} Metrics: ['ELUC: -13.018248866121834', 'NSGA-II_crowding_distance: 0.4492659975237484', 'NSGA-II_rank: 4', 'change: 0.29285151641873103', 'is_elite: False']\n", + "Id: 21_68 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_36', '20_29'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_68', 'origin': '20_36~CUW~20_29#MGNP'} Metrics: ['ELUC: -13.096214061607526', 'NSGA-II_crowding_distance: 0.10790266265725613', 'NSGA-II_rank: 1', 'change: 0.1666979066891201', 'is_elite: False']\n", + "Id: 21_39 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '20_48'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_39', 'origin': '20_78~CUW~20_48#MGNP'} Metrics: ['ELUC: -13.13827628485408', 'NSGA-II_crowding_distance: 0.4399516353175467', 'NSGA-II_rank: 2', 'change: 0.187983997931309', 'is_elite: False']\n", + "Id: 20_29 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_49', '19_57'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_29', 'origin': '19_49~CUW~19_57#MGNP'} Metrics: ['ELUC: -13.21634781941735', 'NSGA-II_crowding_distance: 0.07316184187517777', 'NSGA-II_rank: 1', 'change: 0.16913125447266142', 'is_elite: False']\n", + "Id: 21_44 Identity: {'ancestor_count': 19, 'ancestor_ids': ['16_39', '20_85'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_44', 'origin': '16_39~CUW~20_85#MGNP'} Metrics: ['ELUC: -13.43938055670798', 'NSGA-II_crowding_distance: 0.08705011322489282', 'NSGA-II_rank: 1', 'change: 0.18270412867240657', 'is_elite: False']\n", + "Id: 21_77 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_85', '20_36'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_77', 'origin': '20_85~CUW~20_36#MGNP'} Metrics: ['ELUC: -13.755390082174905', 'NSGA-II_crowding_distance: 0.08957443907845031', 'NSGA-II_rank: 1', 'change: 0.1859573549781118', 'is_elite: False']\n", + "Id: 20_85 Identity: {'ancestor_count': 18, 'ancestor_ids': ['19_38', '19_38'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_85', 'origin': '19_38~CUW~19_38#MGNP'} Metrics: ['ELUC: -13.97736921358573', 'NSGA-II_crowding_distance: 0.17154750299257748', 'NSGA-II_rank: 1', 'change: 0.20030131177284127', 'is_elite: False']\n", + "Id: 21_13 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_34', '20_48'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_13', 'origin': '20_34~CUW~20_48#MGNP'} Metrics: ['ELUC: -14.693117940265957', 'NSGA-II_crowding_distance: 0.27509573068725085', 'NSGA-II_rank: 1', 'change: 0.22122977609802216', 'is_elite: True']\n", + "Id: 21_70 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_40', '20_48'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_70', 'origin': '20_40~CUW~20_48#MGNP'} Metrics: ['ELUC: -14.913596952252817', 'NSGA-II_crowding_distance: 0.46626705503176347', 'NSGA-II_rank: 2', 'change: 0.2668547325627068', 'is_elite: False']\n", + "Id: 21_59 Identity: {'ancestor_count': 3, 'ancestor_ids': ['20_99', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_59', 'origin': '20_99~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.294067170201211', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.3240338188146766', 'is_elite: False']\n", + "Id: 21_32 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_99', '20_29'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_32', 'origin': '20_99~CUW~20_29#MGNP'} Metrics: ['ELUC: -15.355515697625744', 'NSGA-II_crowding_distance: 0.5935942877193583', 'NSGA-II_rank: 3', 'change: 0.28118436514943573', 'is_elite: False']\n", + "Id: 21_66 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_99', '20_81'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_66', 'origin': '20_99~CUW~20_81#MGNP'} Metrics: ['ELUC: -15.41865139177309', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.32487110973234623', 'is_elite: False']\n", + "Id: 21_22 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_36', '20_48'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_22', 'origin': '20_36~CUW~20_48#MGNP'} Metrics: ['ELUC: -15.83755800836448', 'NSGA-II_crowding_distance: 0.20317534266116777', 'NSGA-II_rank: 1', 'change: 0.25081577003125693', 'is_elite: True']\n", + "Id: 21_40 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_40', '20_48'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_40', 'origin': '20_40~CUW~20_48#MGNP'} Metrics: ['ELUC: -16.0173585718194', 'NSGA-II_crowding_distance: 0.14813312230444264', 'NSGA-II_rank: 2', 'change: 0.26786466946720905', 'is_elite: False']\n", + "Id: 20_48 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_36', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_48', 'origin': '19_36~CUW~18_95#MGNP'} Metrics: ['ELUC: -16.115977023354095', 'NSGA-II_crowding_distance: 0.10027664072166656', 'NSGA-II_rank: 1', 'change: 0.2577064133387535', 'is_elite: False']\n", + "Id: 21_55 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_96', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_55', 'origin': '20_96~CUW~20_99#MGNP'} Metrics: ['ELUC: -16.20353511254884', 'NSGA-II_crowding_distance: 0.22280873460635406', 'NSGA-II_rank: 2', 'change: 0.28668476952917576', 'is_elite: False']\n", + "Id: 21_86 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_48', '20_96'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_86', 'origin': '20_48~CUW~20_96#MGNP'} Metrics: ['ELUC: -16.498932876385705', 'NSGA-II_crowding_distance: 0.11865443840467889', 'NSGA-II_rank: 1', 'change: 0.2695123495699843', 'is_elite: False']\n", + "Id: 21_51 Identity: {'ancestor_count': 17, 'ancestor_ids': ['16_39', '20_40'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_51', 'origin': '16_39~CUW~20_40#MGNP'} Metrics: ['ELUC: -16.771185358058908', 'NSGA-II_crowding_distance: 0.12455193419916297', 'NSGA-II_rank: 1', 'change: 0.28199116611605024', 'is_elite: False']\n", + "Id: 21_16 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '20_29'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_16', 'origin': '2_49~CUW~20_29#MGNP'} Metrics: ['ELUC: -16.991686204334105', 'NSGA-II_crowding_distance: 0.1174691944325037', 'NSGA-II_rank: 1', 'change: 0.298313695191027', 'is_elite: False']\n", + "Id: 21_43 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_34', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_43', 'origin': '20_34~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597067969891185', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302121910936747', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 20_99 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_99', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 21_24 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_24', 'origin': '2_49~CUW~20_99#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 21_48 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_48', 'origin': '2_49~CUW~20_99#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 21_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_54', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 21_60 Identity: {'ancestor_count': 12, 'ancestor_ids': ['20_99', '16_39'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_60', 'origin': '20_99~CUW~16_39#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 21_75 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_29', '20_99'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_75', 'origin': '20_29~CUW~20_99#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 21_93 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_34', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_93', 'origin': '20_34~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 21.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 22...:\n", + "PopulationResponse:\n", + " Generation: 22\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/22/20240219-221853\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 22 and asking ESP for generation 23...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 22 data persisted.\n", + "Evaluated candidates:\n", + "Id: 22_66 Identity: {'ancestor_count': 17, 'ancestor_ids': ['21_81', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_66', 'origin': '21_81~CUW~2_49#MGNP'} Metrics: ['ELUC: 22.671422294784822', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2888116515459672', 'is_elite: False']\n", + "Id: 22_41 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_41', 'origin': '20_78~CUW~2_49#MGNP'} Metrics: ['ELUC: 21.945163643032913', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 12', 'change: 0.3000340128576399', 'is_elite: False']\n", + "Id: 22_88 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_93', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_88', 'origin': '21_93~CUW~21_87#MGNP'} Metrics: ['ELUC: 18.783554440484366', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2790611564280028', 'is_elite: False']\n", + "Id: 22_77 Identity: {'ancestor_count': 17, 'ancestor_ids': ['21_93', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_77', 'origin': '21_93~CUW~1_1#MGNP'} Metrics: ['ELUC: 17.633719932211793', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.2942665351155004', 'is_elite: False']\n", + "Id: 22_89 Identity: {'ancestor_count': 17, 'ancestor_ids': ['2_49', '21_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_89', 'origin': '2_49~CUW~21_81#MGNP'} Metrics: ['ELUC: 8.135002940197788', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26484312862911946', 'is_elite: False']\n", + "Id: 22_55 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_78', '21_22'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_55', 'origin': '21_78~CUW~21_22#MGNP'} Metrics: ['ELUC: 4.70258083580021', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.0996202028359437', 'is_elite: False']\n", + "Id: 22_78 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_78', 'origin': '20_81~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.654903096983746', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.2769975201941396', 'is_elite: False']\n", + "Id: 22_72 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_93', '21_47'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_72', 'origin': '21_93~CUW~21_47#MGNP'} Metrics: ['ELUC: 2.455121480855958', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.35077186318045334', 'is_elite: False']\n", + "Id: 22_54 Identity: {'ancestor_count': 17, 'ancestor_ids': ['2_49', '21_23'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_54', 'origin': '2_49~CUW~21_23#MGNP'} Metrics: ['ELUC: 1.6767316700811172', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3472276606126218', 'is_elite: False']\n", + "Id: 22_50 Identity: {'ancestor_count': 19, 'ancestor_ids': ['1_1', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_50', 'origin': '1_1~CUW~21_87#MGNP'} Metrics: ['ELUC: 1.540686427348342', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06399137747618468', 'is_elite: False']\n", + "Id: 22_69 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_69', 'origin': '20_81~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.2697793082839255', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.16325506908404203', 'is_elite: False']\n", + "Id: 22_60 Identity: {'ancestor_count': 18, 'ancestor_ids': ['1_1', '20_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_60', 'origin': '1_1~CUW~20_81#MGNP'} Metrics: ['ELUC: 0.6674440751510196', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.11269844184370427', 'is_elite: False']\n", + "Id: 22_34 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_34', 'origin': '20_81~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.36636829669002563', 'NSGA-II_crowding_distance: 0.7193819415462617', 'NSGA-II_rank: 6', 'change: 0.10875933884377897', 'is_elite: False']\n", + "Id: 22_20 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '20_36'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_20', 'origin': '20_78~CUW~20_36#MGNP'} Metrics: ['ELUC: 0.176331744599734', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07131580424183954', 'is_elite: False']\n", + "Id: 22_15 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_93', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_15', 'origin': '21_93~CUW~21_87#MGNP'} Metrics: ['ELUC: 0.11299852854734761', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3073141979607875', 'is_elite: False']\n", + "Id: 22_70 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_47', '21_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_70', 'origin': '21_47~CUW~21_81#MGNP'} Metrics: ['ELUC: 0.09015862017439809', 'NSGA-II_crowding_distance: 0.7911838265988858', 'NSGA-II_rank: 4', 'change: 0.06635058330885195', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 22_53 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_87', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_53', 'origin': '21_87~CUW~21_87#MGNP'} Metrics: ['ELUC: -0.07341682494873256', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.047474328611196465', 'is_elite: False']\n", + "Id: 21_87 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '1_1'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_87', 'origin': '20_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.07709585036232353', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04276661565544487', 'is_elite: False']\n", + "Id: 22_86 Identity: {'ancestor_count': 18, 'ancestor_ids': ['1_1', '20_78'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_86', 'origin': '1_1~CUW~20_78#MGNP'} Metrics: ['ELUC: -0.092754737788134', 'NSGA-II_crowding_distance: 0.22263374440245476', 'NSGA-II_rank: 1', 'change: 0.03962973424156547', 'is_elite: True']\n", + "Id: 22_13 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_13', 'origin': '2_49~CUW~21_87#MGNP'} Metrics: ['ELUC: -0.22495240492096866', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2543964561250036', 'is_elite: False']\n", + "Id: 22_35 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_87', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_35', 'origin': '21_87~CUW~21_87#MGNP'} Metrics: ['ELUC: -1.1393687134378991', 'NSGA-II_crowding_distance: 0.1451189653196957', 'NSGA-II_rank: 2', 'change: 0.05776510832020794', 'is_elite: False']\n", + "Id: 22_28 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_78', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_28', 'origin': '21_78~CUW~21_87#MGNP'} Metrics: ['ELUC: -1.1459878019416978', 'NSGA-II_crowding_distance: 0.04522133525896417', 'NSGA-II_rank: 2', 'change: 0.05878528152758909', 'is_elite: False']\n", + "Id: 22_52 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '21_23'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_52', 'origin': '1_1~CUW~21_23#MGNP'} Metrics: ['ELUC: -1.148767354193168', 'NSGA-II_crowding_distance: 0.2137614855497887', 'NSGA-II_rank: 1', 'change: 0.05183212276392621', 'is_elite: True']\n", + "Id: 22_73 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_81', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_73', 'origin': '21_81~CUW~21_63#MGNP'} Metrics: ['ELUC: -1.3764591990298463', 'NSGA-II_crowding_distance: 0.1181222526068928', 'NSGA-II_rank: 2', 'change: 0.06402719459288232', 'is_elite: False']\n", + "Id: 22_16 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_81', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_16', 'origin': '20_81~CUW~21_87#MGNP'} Metrics: ['ELUC: -1.5091565100091993', 'NSGA-II_crowding_distance: 0.44692463016607814', 'NSGA-II_rank: 3', 'change: 0.0981028613935477', 'is_elite: False']\n", + "Id: 22_65 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_87', '21_23'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_65', 'origin': '21_87~CUW~21_23#MGNP'} Metrics: ['ELUC: -1.9361013582225495', 'NSGA-II_crowding_distance: 0.27418575807185686', 'NSGA-II_rank: 2', 'change: 0.0728818137021163', 'is_elite: False']\n", + "Id: 22_25 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_78', '20_85'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_25', 'origin': '21_78~CUW~20_85#MGNP'} Metrics: ['ELUC: -2.6013424579403392', 'NSGA-II_crowding_distance: 0.19239846036120395', 'NSGA-II_rank: 3', 'change: 0.10532372415891934', 'is_elite: False']\n", + "Id: 22_76 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_87', '19_70'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_76', 'origin': '21_87~CUW~19_70#MGNP'} Metrics: ['ELUC: -2.6835491065076353', 'NSGA-II_crowding_distance: 0.17523340287987454', 'NSGA-II_rank: 1', 'change: 0.05944481888416992', 'is_elite: False']\n", + "Id: 22_67 Identity: {'ancestor_count': 20, 'ancestor_ids': ['2_49', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_67', 'origin': '2_49~CUW~21_63#MGNP'} Metrics: ['ELUC: -3.48569469007005', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30063043647950866', 'is_elite: False']\n", + "Id: 22_79 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_93', '21_51'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_79', 'origin': '21_93~CUW~21_51#MGNP'} Metrics: ['ELUC: -3.554140508132947', 'NSGA-II_crowding_distance: 1.2523979452564864', 'NSGA-II_rank: 8', 'change: 0.23718533617489773', 'is_elite: False']\n", + "Id: 22_36 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_78', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_36', 'origin': '21_78~CUW~21_63#MGNP'} Metrics: ['ELUC: -3.5807985705034406', 'NSGA-II_crowding_distance: 0.6355342641196915', 'NSGA-II_rank: 6', 'change: 0.15806551928481088', 'is_elite: False']\n", + "Id: 20_78 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_97', '1_1'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_78', 'origin': '19_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.711133621167099', 'NSGA-II_crowding_distance: 0.16896708713954425', 'NSGA-II_rank: 1', 'change: 0.06063371980756515', 'is_elite: False']\n", + "Id: 22_80 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_80', 'origin': '21_22~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.840709594237501', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2644518702825367', 'is_elite: False']\n", + "Id: 22_82 Identity: {'ancestor_count': 19, 'ancestor_ids': ['1_1', '20_85'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_82', 'origin': '1_1~CUW~20_85#MGNP'} Metrics: ['ELUC: -3.875967611065697', 'NSGA-II_crowding_distance: 0.41196243678279676', 'NSGA-II_rank: 3', 'change: 0.1063560643338155', 'is_elite: False']\n", + "Id: 22_11 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_13', '21_93'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_11', 'origin': '21_13~CUW~21_93#MGNP'} Metrics: ['ELUC: -4.265463392766649', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2685608390268234', 'is_elite: False']\n", + "Id: 22_27 Identity: {'ancestor_count': 17, 'ancestor_ids': ['21_81', '21_23'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_27', 'origin': '21_81~CUW~21_23#MGNP'} Metrics: ['ELUC: -4.534892330685631', 'NSGA-II_crowding_distance: 0.25679856178774474', 'NSGA-II_rank: 2', 'change: 0.07922006887114783', 'is_elite: False']\n", + "Id: 22_19 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_93', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_19', 'origin': '21_93~CUW~21_87#MGNP'} Metrics: ['ELUC: -4.553696295231763', 'NSGA-II_crowding_distance: 0.5169658320529938', 'NSGA-II_rank: 8', 'change: 0.25602032388972434', 'is_elite: False']\n", + "Id: 22_85 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_78', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_85', 'origin': '20_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.576599065324621', 'NSGA-II_crowding_distance: 0.13592794756835522', 'NSGA-II_rank: 1', 'change: 0.07773519097085455', 'is_elite: False']\n", + "Id: 22_58 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_93', '20_78'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_58', 'origin': '21_93~CUW~20_78#MGNP'} Metrics: ['ELUC: -4.614378590518332', 'NSGA-II_crowding_distance: 0.7476020547435136', 'NSGA-II_rank: 8', 'change: 0.29402223214701356', 'is_elite: False']\n", + "Id: 22_84 Identity: {'ancestor_count': 20, 'ancestor_ids': ['1_1', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_84', 'origin': '1_1~CUW~21_63#MGNP'} Metrics: ['ELUC: -4.938374252053996', 'NSGA-II_crowding_distance: 0.31317650269236963', 'NSGA-II_rank: 2', 'change: 0.08652722993723437', 'is_elite: False']\n", + "Id: 22_57 Identity: {'ancestor_count': 17, 'ancestor_ids': ['21_81', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_57', 'origin': '21_81~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.026915274983746', 'NSGA-II_crowding_distance: 0.1723419254141701', 'NSGA-II_rank: 1', 'change: 0.07886236997553689', 'is_elite: False']\n", + "Id: 22_39 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_87', '21_22'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_39', 'origin': '21_87~CUW~21_22#MGNP'} Metrics: ['ELUC: -5.138546513041076', 'NSGA-II_crowding_distance: 0.8919491695890267', 'NSGA-II_rank: 4', 'change: 0.14280244749658674', 'is_elite: False']\n", + "Id: 22_21 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '21_23'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_21', 'origin': '21_22~CUW~21_23#MGNP'} Metrics: ['ELUC: -5.701302611140245', 'NSGA-II_crowding_distance: 0.42952327634082393', 'NSGA-II_rank: 6', 'change: 0.17345126277834697', 'is_elite: False']\n", + "Id: 22_29 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_51', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_29', 'origin': '21_51~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.88672714757121', 'NSGA-II_crowding_distance: 1.4355869706015616', 'NSGA-II_rank: 7', 'change: 0.21832335600904917', 'is_elite: False']\n", + "Id: 22_97 Identity: {'ancestor_count': 20, 'ancestor_ids': ['1_1', '21_47'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_97', 'origin': '1_1~CUW~21_47#MGNP'} Metrics: ['ELUC: -5.8896212064970435', 'NSGA-II_crowding_distance: 0.3892964962306598', 'NSGA-II_rank: 2', 'change: 0.1263888450614208', 'is_elite: False']\n", + "Id: 22_87 Identity: {'ancestor_count': 17, 'ancestor_ids': ['19_70', '21_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_87', 'origin': '19_70~CUW~21_81#MGNP'} Metrics: ['ELUC: -6.276591071523714', 'NSGA-II_crowding_distance: 0.19905432268511214', 'NSGA-II_rank: 1', 'change: 0.1003087925384775', 'is_elite: False']\n", + "Id: 22_18 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_18', 'origin': '20_81~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.55411253300128', 'NSGA-II_crowding_distance: 0.5716975683482117', 'NSGA-II_rank: 3', 'change: 0.13751650930777262', 'is_elite: False']\n", + "Id: 22_95 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '20_85'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_95', 'origin': '2_49~CUW~20_85#MGNP'} Metrics: ['ELUC: -6.77816748558492', 'NSGA-II_crowding_distance: 0.5113067301819585', 'NSGA-II_rank: 7', 'change: 0.26500426518923775', 'is_elite: False']\n", + "Id: 22_64 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '19_70'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_64', 'origin': '20_81~CUW~19_70#MGNP'} Metrics: ['ELUC: -7.042402155574386', 'NSGA-II_crowding_distance: 0.8860590372821515', 'NSGA-II_rank: 5', 'change: 0.15600208996932693', 'is_elite: False']\n", + "Id: 21_81 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_61', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_81', 'origin': '18_61~CUW~19_70#MGNP'} Metrics: ['ELUC: -7.1497333512433885', 'NSGA-II_crowding_distance: 0.22858949777975407', 'NSGA-II_rank: 1', 'change: 0.10223086687595745', 'is_elite: True']\n", + "Id: 22_47 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_51', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_47', 'origin': '21_51~CUW~21_63#MGNP'} Metrics: ['ELUC: -7.200506515815056', 'NSGA-II_crowding_distance: 0.3240298593920331', 'NSGA-II_rank: 6', 'change: 0.20681240784541663', 'is_elite: False']\n", + "Id: 22_42 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_18', '21_51'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_42', 'origin': '21_18~CUW~21_51#MGNP'} Metrics: ['ELUC: -7.307243015449019', 'NSGA-II_crowding_distance: 0.5762924230058278', 'NSGA-II_rank: 6', 'change: 0.22197358420671667', 'is_elite: False']\n", + "Id: 22_94 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_63', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_94', 'origin': '21_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.355111876289774', 'NSGA-II_crowding_distance: 0.9239997413548919', 'NSGA-II_rank: 5', 'change: 0.15835800764752792', 'is_elite: False']\n", + "Id: 22_59 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_11', '20_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_59', 'origin': '21_11~CUW~20_81#MGNP'} Metrics: ['ELUC: -7.673494609082589', 'NSGA-II_crowding_distance: 0.22703901669143167', 'NSGA-II_rank: 4', 'change: 0.1524837938817879', 'is_elite: False']\n", + "Id: 22_98 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_63', '21_87'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_98', 'origin': '21_63~CUW~21_87#MGNP'} Metrics: ['ELUC: -7.879838084129322', 'NSGA-II_crowding_distance: 0.06523964034251727', 'NSGA-II_rank: 4', 'change: 0.15583949890032137', 'is_elite: False']\n", + "Id: 22_48 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_78', '20_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_48', 'origin': '21_78~CUW~20_81#MGNP'} Metrics: ['ELUC: -7.91308010606071', 'NSGA-II_crowding_distance: 0.3130978379648428', 'NSGA-II_rank: 2', 'change: 0.12807896329509944', 'is_elite: False']\n", + "Id: 22_44 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_47', '21_23'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_44', 'origin': '21_47~CUW~21_23#MGNP'} Metrics: ['ELUC: -8.401797763776159', 'NSGA-II_crowding_distance: 0.1737657542788293', 'NSGA-II_rank: 4', 'change: 0.1569200564005489', 'is_elite: False']\n", + "Id: 22_26 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_26', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.47257207769911', 'NSGA-II_crowding_distance: 0.38132197541039714', 'NSGA-II_rank: 7', 'change: 0.2737955874425133', 'is_elite: False']\n", + "Id: 22_38 Identity: {'ancestor_count': 17, 'ancestor_ids': ['21_93', '21_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_38', 'origin': '21_93~CUW~21_81#MGNP'} Metrics: ['ELUC: -8.746391197265044', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.30150627813303305', 'is_elite: False']\n", + "Id: 22_63 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_85', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_63', 'origin': '20_85~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.01234475379971', 'NSGA-II_crowding_distance: 0.3655216729699838', 'NSGA-II_rank: 7', 'change: 0.30069717449879', 'is_elite: False']\n", + "Id: 22_99 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_47', '20_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_99', 'origin': '21_47~CUW~20_81#MGNP'} Metrics: ['ELUC: -9.26834098055011', 'NSGA-II_crowding_distance: 0.1642080335188344', 'NSGA-II_rank: 4', 'change: 0.17405974377369132', 'is_elite: False']\n", + "Id: 20_81 Identity: {'ancestor_count': 17, 'ancestor_ids': ['16_39', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_81', 'origin': '16_39~CUW~18_95#MGNP'} Metrics: ['ELUC: -9.271583900826883', 'NSGA-II_crowding_distance: 0.2084120741137991', 'NSGA-II_rank: 1', 'change: 0.11768885314187973', 'is_elite: True']\n", + "Id: 22_22 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_87', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_22', 'origin': '21_87~CUW~21_63#MGNP'} Metrics: ['ELUC: -9.5046276592981', 'NSGA-II_crowding_distance: 0.08258237735039425', 'NSGA-II_rank: 4', 'change: 0.1765693539549589', 'is_elite: False']\n", + "Id: 22_14 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_18', '20_36'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_14', 'origin': '21_18~CUW~20_36#MGNP'} Metrics: ['ELUC: -9.66236812492111', 'NSGA-II_crowding_distance: 0.10326756914987101', 'NSGA-II_rank: 1', 'change: 0.12177619877518421', 'is_elite: False']\n", + "Id: 22_75 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_13', '21_47'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_75', 'origin': '21_13~CUW~21_47#MGNP'} Metrics: ['ELUC: -9.755562908194678', 'NSGA-II_crowding_distance: 0.29546360740899524', 'NSGA-II_rank: 3', 'change: 0.1458980574423698', 'is_elite: False']\n", + "Id: 21_47 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_85', '20_36'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_47', 'origin': '20_85~CUW~20_36#MGNP'} Metrics: ['ELUC: -10.231668334758446', 'NSGA-II_crowding_distance: 0.31213922091099044', 'NSGA-II_rank: 2', 'change: 0.13400556263840216', 'is_elite: False']\n", + "Id: 22_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_100', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.232014435525219', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.31510643646698094', 'is_elite: False']\n", + "Id: 22_37 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_13', '20_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_37', 'origin': '21_13~CUW~20_81#MGNP'} Metrics: ['ELUC: -10.24430460667992', 'NSGA-II_crowding_distance: 0.18578377561427473', 'NSGA-II_rank: 1', 'change: 0.13199422425408747', 'is_elite: False']\n", + "Id: 22_24 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_81', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_24', 'origin': '21_81~CUW~21_63#MGNP'} Metrics: ['ELUC: -10.37080863921111', 'NSGA-II_crowding_distance: 0.23173196818987687', 'NSGA-II_rank: 3', 'change: 0.1478204186250518', 'is_elite: False']\n", + "Id: 22_92 Identity: {'ancestor_count': 17, 'ancestor_ids': ['21_81', '20_36'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_92', 'origin': '21_81~CUW~20_36#MGNP'} Metrics: ['ELUC: -10.374648490353753', 'NSGA-II_crowding_distance: 0.43160613331052494', 'NSGA-II_rank: 4', 'change: 0.17753333416012987', 'is_elite: False']\n", + "Id: 22_32 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_51', '20_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_32', 'origin': '21_51~CUW~20_81#MGNP'} Metrics: ['ELUC: -10.703086870604738', 'NSGA-II_crowding_distance: 0.7254290250804589', 'NSGA-II_rank: 4', 'change: 0.24796561114781931', 'is_elite: False']\n", + "Id: 22_23 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_78', '21_13'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_23', 'origin': '20_78~CUW~21_13#MGNP'} Metrics: ['ELUC: -11.087990035384399', 'NSGA-II_crowding_distance: 0.8456493256421299', 'NSGA-II_rank: 3', 'change: 0.17561071400571138', 'is_elite: False']\n", + "Id: 22_30 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_81', '20_81'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_30', 'origin': '21_81~CUW~20_81#MGNP'} Metrics: ['ELUC: -11.63598922133295', 'NSGA-II_crowding_distance: 0.5204080762361262', 'NSGA-II_rank: 2', 'change: 0.14369041048799638', 'is_elite: False']\n", + "Id: 22_40 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_63', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_40', 'origin': '21_63~CUW~21_63#MGNP'} Metrics: ['ELUC: -11.78103137121908', 'NSGA-II_crowding_distance: 0.49940172115331294', 'NSGA-II_rank: 1', 'change: 0.14125556891696645', 'is_elite: True']\n", + "Id: 22_43 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '1_1'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_43', 'origin': '21_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.910511686519149', 'NSGA-II_crowding_distance: 0.7706860144695971', 'NSGA-II_rank: 2', 'change: 0.2199607155130203', 'is_elite: False']\n", + "Id: 22_96 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_87', '21_93'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_96', 'origin': '21_87~CUW~21_93#MGNP'} Metrics: ['ELUC: -11.953083024843211', 'NSGA-II_crowding_distance: 0.6082392618347413', 'NSGA-II_rank: 6', 'change: 0.27330244645963886', 'is_elite: False']\n", + "Id: 22_56 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_93', '21_47'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_56', 'origin': '21_93~CUW~21_47#MGNP'} Metrics: ['ELUC: -13.129378553634309', 'NSGA-II_crowding_distance: 0.27480235910708656', 'NSGA-II_rank: 6', 'change: 0.28372981338078207', 'is_elite: False']\n", + "Id: 22_62 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_93', '21_51'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_62', 'origin': '21_93~CUW~21_51#MGNP'} Metrics: ['ELUC: -13.761680560912144', 'NSGA-II_crowding_distance: 1.0156298782660333', 'NSGA-II_rank: 5', 'change: 0.2634013094172259', 'is_elite: False']\n", + "Id: 22_49 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_13', '21_13'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_49', 'origin': '21_13~CUW~21_13#MGNP'} Metrics: ['ELUC: -14.252417370508274', 'NSGA-II_crowding_distance: 0.43365575723777905', 'NSGA-II_rank: 1', 'change: 0.21298565959202997', 'is_elite: True']\n", + "Id: 22_68 Identity: {'ancestor_count': 17, 'ancestor_ids': ['21_93', '21_23'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_68', 'origin': '21_93~CUW~21_23#MGNP'} Metrics: ['ELUC: -14.590258510741084', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.30113353942426613', 'is_elite: False']\n", + "Id: 22_17 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_18', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_17', 'origin': '21_18~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.63190626587098', 'NSGA-II_crowding_distance: 0.22108433856690607', 'NSGA-II_rank: 5', 'change: 0.27800247434135694', 'is_elite: False']\n", + "Id: 21_13 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_34', '20_48'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_13', 'origin': '20_34~CUW~20_48#MGNP'} Metrics: ['ELUC: -14.693117940265957', 'NSGA-II_crowding_distance: 0.16382412728855167', 'NSGA-II_rank: 1', 'change: 0.22122977609802216', 'is_elite: False']\n", + "Id: 22_51 Identity: {'ancestor_count': 17, 'ancestor_ids': ['2_49', '21_93'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_51', 'origin': '2_49~CUW~21_93#MGNP'} Metrics: ['ELUC: -15.02619420552016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.29412864227096297', 'is_elite: False']\n", + "Id: 22_33 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '21_18'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_33', 'origin': '21_22~CUW~21_18#MGNP'} Metrics: ['ELUC: -15.374545717186285', 'NSGA-II_crowding_distance: 0.1528982858466067', 'NSGA-II_rank: 1', 'change: 0.24282426440451008', 'is_elite: False']\n", + "Id: 22_61 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '21_93'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_61', 'origin': '1_1~CUW~21_93#MGNP'} Metrics: ['ELUC: -15.476783710658385', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2616658838151547', 'is_elite: False']\n", + "Id: 22_93 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '21_11'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_93', 'origin': '21_22~CUW~21_11#MGNP'} Metrics: ['ELUC: -15.668920311683383', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.25057481826169076', 'is_elite: False']\n", + "Id: 22_12 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '21_22'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_12', 'origin': '21_22~CUW~21_22#MGNP'} Metrics: ['ELUC: -15.758710150834306', 'NSGA-II_crowding_distance: 0.3941208573037801', 'NSGA-II_rank: 2', 'change: 0.24932567111906978', 'is_elite: False']\n", + "Id: 22_71 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_22', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_71', 'origin': '21_22~CUW~21_63#MGNP'} Metrics: ['ELUC: -15.783261001931237', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.25063008799502673', 'is_elite: False']\n", + "Id: 22_31 Identity: {'ancestor_count': 19, 'ancestor_ids': ['20_85', '21_13'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_31', 'origin': '20_85~CUW~21_13#MGNP'} Metrics: ['ELUC: -15.794746099807321', 'NSGA-II_crowding_distance: 0.05311712681643833', 'NSGA-II_rank: 1', 'change: 0.24815624780666257', 'is_elite: False']\n", + "Id: 21_22 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_36', '20_48'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_22', 'origin': '20_36~CUW~20_48#MGNP'} Metrics: ['ELUC: -15.83755800836448', 'NSGA-II_crowding_distance: 0.1466896420248035', 'NSGA-II_rank: 1', 'change: 0.25081577003125693', 'is_elite: False']\n", + "Id: 22_83 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '21_93'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_83', 'origin': '20_81~CUW~21_93#MGNP'} Metrics: ['ELUC: -16.08729769975913', 'NSGA-II_crowding_distance: 0.24311918722365264', 'NSGA-II_rank: 1', 'change: 0.2869604771100083', 'is_elite: True']\n", + "Id: 22_46 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '21_93'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_46', 'origin': '1_1~CUW~21_93#MGNP'} Metrics: ['ELUC: -17.308177030087723', 'NSGA-II_crowding_distance: 0.13971104762694017', 'NSGA-II_rank: 1', 'change: 0.2984002594390893', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 21_93 Identity: {'ancestor_count': 16, 'ancestor_ids': ['20_34', '2_49'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_93', 'origin': '20_34~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 22_45 Identity: {'ancestor_count': 18, 'ancestor_ids': ['2_49', '20_78'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_45', 'origin': '2_49~CUW~20_78#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 22_74 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_93', '21_47'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_74', 'origin': '21_93~CUW~21_47#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 22_81 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '21_86'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_81', 'origin': '2_49~CUW~21_86#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 22_90 Identity: {'ancestor_count': 18, 'ancestor_ids': ['2_49', '21_78'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_90', 'origin': '2_49~CUW~21_78#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 22_91 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_91', 'origin': '21_22~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 22.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 23...:\n", + "PopulationResponse:\n", + " Generation: 23\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/23/20240219-222605\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 23 and asking ESP for generation 24...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 23 data persisted.\n", + "Evaluated candidates:\n", + "Id: 23_67 Identity: {'ancestor_count': 18, 'ancestor_ids': ['2_49', '22_52'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_67', 'origin': '2_49~CUW~22_52#MGNP'} Metrics: ['ELUC: 14.044762015303998', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2893534899470375', 'is_elite: False']\n", + "Id: 23_19 Identity: {'ancestor_count': 18, 'ancestor_ids': ['2_49', '22_57'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_19', 'origin': '2_49~CUW~22_57#MGNP'} Metrics: ['ELUC: 9.072566077757054', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2633293893343709', 'is_elite: False']\n", + "Id: 23_78 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_78', 'origin': '22_40~CUW~22_91#MGNP'} Metrics: ['ELUC: 7.0739356539250595', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25104533253148653', 'is_elite: False']\n", + "Id: 23_70 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_70', 'origin': '21_22~CUW~22_86#MGNP'} Metrics: ['ELUC: 4.19676492055919', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11398804547002102', 'is_elite: False']\n", + "Id: 23_57 Identity: {'ancestor_count': 20, 'ancestor_ids': ['2_49', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_57', 'origin': '2_49~CUW~22_49#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 23_45 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_37', '22_76'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_45', 'origin': '22_37~CUW~22_76#MGNP'} Metrics: ['ELUC: 2.201243841942424', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09013336192001882', 'is_elite: False']\n", + "Id: 23_11 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_86', '22_37'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_11', 'origin': '22_86~CUW~22_37#MGNP'} Metrics: ['ELUC: 1.785936413948932', 'NSGA-II_crowding_distance: 0.3902328577505168', 'NSGA-II_rank: 6', 'change: 0.12364053585490908', 'is_elite: False']\n", + "Id: 23_98 Identity: {'ancestor_count': 20, 'ancestor_ids': ['1_1', '22_37'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_98', 'origin': '1_1~CUW~22_37#MGNP'} Metrics: ['ELUC: 1.6661654405888915', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08676122568913923', 'is_elite: False']\n", + "Id: 23_100 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_100', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.5668257491577192', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03219012327736107', 'is_elite: False']\n", + "Id: 23_53 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_37', '22_52'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_53', 'origin': '22_37~CUW~22_52#MGNP'} Metrics: ['ELUC: 0.24488214384639573', 'NSGA-II_crowding_distance: 0.4967773745864381', 'NSGA-II_rank: 6', 'change: 0.13547639609618933', 'is_elite: False']\n", + "Id: 23_18 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '1_1'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_18', 'origin': '22_86~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.1765110368901074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.049070456000400664', 'is_elite: False']\n", + "Id: 23_37 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_37', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_37', 'origin': '22_37~CUW~22_86#MGNP'} Metrics: ['ELUC: -1.1294278599139082e-05', 'NSGA-II_crowding_distance: 0.7289695832496355', 'NSGA-II_rank: 5', 'change: 0.12284957803246657', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 22_86 Identity: {'ancestor_count': 18, 'ancestor_ids': ['1_1', '20_78'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_86', 'origin': '1_1~CUW~20_78#MGNP'} Metrics: ['ELUC: -0.092754737788134', 'NSGA-II_crowding_distance: 0.23086448348867647', 'NSGA-II_rank: 1', 'change: 0.03962973424156547', 'is_elite: False']\n", + "Id: 23_74 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_76', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_74', 'origin': '22_76~CUW~22_83#MGNP'} Metrics: ['ELUC: -0.809144493513007', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2585865631884348', 'is_elite: False']\n", + "Id: 22_52 Identity: {'ancestor_count': 17, 'ancestor_ids': ['1_1', '21_23'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_52', 'origin': '1_1~CUW~21_23#MGNP'} Metrics: ['ELUC: -1.148767354193168', 'NSGA-II_crowding_distance: 0.2353330651850008', 'NSGA-II_rank: 3', 'change: 0.05183212276392621', 'is_elite: False']\n", + "Id: 23_33 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_52', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_33', 'origin': '22_52~CUW~22_86#MGNP'} Metrics: ['ELUC: -1.4102155209495586', 'NSGA-II_crowding_distance: 0.36463007859941166', 'NSGA-II_rank: 2', 'change: 0.04478315939263786', 'is_elite: False']\n", + "Id: 23_95 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '20_78'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_95', 'origin': '22_86~CUW~20_78#MGNP'} Metrics: ['ELUC: -1.5862831519666813', 'NSGA-II_crowding_distance: 0.2467251908747255', 'NSGA-II_rank: 3', 'change: 0.08352637222476385', 'is_elite: False']\n", + "Id: 23_59 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_87', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_59', 'origin': '22_87~CUW~22_86#MGNP'} Metrics: ['ELUC: -1.883463714994084', 'NSGA-II_crowding_distance: 0.30410173577855476', 'NSGA-II_rank: 1', 'change: 0.04181996822749041', 'is_elite: True']\n", + "Id: 23_56 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_52', '22_33'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_56', 'origin': '22_52~CUW~22_33#MGNP'} Metrics: ['ELUC: -1.8933153596334695', 'NSGA-II_crowding_distance: 0.4898107740943036', 'NSGA-II_rank: 4', 'change: 0.12096983873437665', 'is_elite: False']\n", + "Id: 23_58 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_49', '22_52'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_58', 'origin': '22_49~CUW~22_52#MGNP'} Metrics: ['ELUC: -2.372461267076969', 'NSGA-II_crowding_distance: 0.5335280482129727', 'NSGA-II_rank: 6', 'change: 0.16037415907341507', 'is_elite: False']\n", + "Id: 23_89 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_37', '22_52'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_89', 'origin': '22_37~CUW~22_52#MGNP'} Metrics: ['ELUC: -2.4244016642509862', 'NSGA-II_crowding_distance: 0.3407026573155531', 'NSGA-II_rank: 4', 'change: 0.13317012592904412', 'is_elite: False']\n", + "Id: 23_71 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_76', '22_57'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_71', 'origin': '22_76~CUW~22_57#MGNP'} Metrics: ['ELUC: -2.666313944826595', 'NSGA-II_crowding_distance: 0.1637561196095581', 'NSGA-II_rank: 3', 'change: 0.09271010012125637', 'is_elite: False']\n", + "Id: 23_51 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_52', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_51', 'origin': '22_52~CUW~22_91#MGNP'} Metrics: ['ELUC: -2.7496646101801803', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2481952484009157', 'is_elite: False']\n", + "Id: 23_92 Identity: {'ancestor_count': 18, 'ancestor_ids': ['22_87', '2_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_92', 'origin': '22_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.0900291903119212', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27344506289950005', 'is_elite: False']\n", + "Id: 23_61 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '21_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_61', 'origin': '20_81~CUW~21_81#MGNP'} Metrics: ['ELUC: -3.3232096694217765', 'NSGA-II_crowding_distance: 0.534138136451597', 'NSGA-II_rank: 3', 'change: 0.10016399051254372', 'is_elite: False']\n", + "Id: 23_25 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '22_87'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_25', 'origin': '22_86~CUW~22_87#MGNP'} Metrics: ['ELUC: -3.3576683072088778', 'NSGA-II_crowding_distance: 0.2676747818687213', 'NSGA-II_rank: 2', 'change: 0.07242566719640098', 'is_elite: False']\n", + "Id: 23_42 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_87', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_42', 'origin': '22_87~CUW~22_86#MGNP'} Metrics: ['ELUC: -3.688337494460454', 'NSGA-II_crowding_distance: 0.26116411783031546', 'NSGA-II_rank: 2', 'change: 0.08330921081624201', 'is_elite: False']\n", + "Id: 23_41 Identity: {'ancestor_count': 20, 'ancestor_ids': ['20_78', '22_76'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_41', 'origin': '20_78~CUW~22_76#MGNP'} Metrics: ['ELUC: -3.7293255869377386', 'NSGA-II_crowding_distance: 0.3103967790570865', 'NSGA-II_rank: 1', 'change: 0.06865318711571738', 'is_elite: True']\n", + "Id: 23_47 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_81', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_47', 'origin': '21_81~CUW~22_49#MGNP'} Metrics: ['ELUC: -4.73545698891159', 'NSGA-II_crowding_distance: 0.47629673599690076', 'NSGA-II_rank: 6', 'change: 0.16939901358939435', 'is_elite: False']\n", + "Id: 23_63 Identity: {'ancestor_count': 18, 'ancestor_ids': ['22_57', '22_57'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_63', 'origin': '22_57~CUW~22_57#MGNP'} Metrics: ['ELUC: -5.043030744265139', 'NSGA-II_crowding_distance: 0.2476330213059451', 'NSGA-II_rank: 1', 'change: 0.0808166235475437', 'is_elite: True']\n", + "Id: 23_46 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '21_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_46', 'origin': '22_40~CUW~21_81#MGNP'} Metrics: ['ELUC: -5.197319298907489', 'NSGA-II_crowding_distance: 0.586545463009287', 'NSGA-II_rank: 5', 'change: 0.14492469880788866', 'is_elite: False']\n", + "Id: 23_12 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_81', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_12', 'origin': '21_81~CUW~22_83#MGNP'} Metrics: ['ELUC: -5.674874420929331', 'NSGA-II_crowding_distance: 1.4885542535618805', 'NSGA-II_rank: 8', 'change: 0.24945971863228275', 'is_elite: False']\n", + "Id: 23_96 Identity: {'ancestor_count': 18, 'ancestor_ids': ['22_87', '20_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_96', 'origin': '22_87~CUW~20_81#MGNP'} Metrics: ['ELUC: -6.097554991680211', 'NSGA-II_crowding_distance: 0.4343333208701358', 'NSGA-II_rank: 2', 'change: 0.10230295869738798', 'is_elite: False']\n", + "Id: 23_68 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_83', '1_1'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_68', 'origin': '22_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.114003169534328', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.20684683168656653', 'is_elite: False']\n", + "Id: 23_27 Identity: {'ancestor_count': 20, 'ancestor_ids': ['20_78', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_27', 'origin': '20_78~CUW~22_91#MGNP'} Metrics: ['ELUC: -6.209419898551763', 'NSGA-II_crowding_distance: 1.1703977878420282', 'NSGA-II_rank: 8', 'change: 0.26446024891517206', 'is_elite: False']\n", + "Id: 23_16 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '22_40'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_16', 'origin': '1_1~CUW~22_40#MGNP'} Metrics: ['ELUC: -6.219467214293304', 'NSGA-II_crowding_distance: 0.3980408379731723', 'NSGA-II_rank: 4', 'change: 0.1348852934744594', 'is_elite: False']\n", + "Id: 23_72 Identity: {'ancestor_count': 20, 'ancestor_ids': ['2_49', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_72', 'origin': '2_49~CUW~22_49#MGNP'} Metrics: ['ELUC: -6.470520628833317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2773060946901641', 'is_elite: False']\n", + "Id: 23_29 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_81', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_29', 'origin': '21_81~CUW~22_86#MGNP'} Metrics: ['ELUC: -6.476111611651547', 'NSGA-II_crowding_distance: 0.19158815499003373', 'NSGA-II_rank: 1', 'change: 0.09592755670570481', 'is_elite: False']\n", + "Id: 23_91 Identity: {'ancestor_count': 18, 'ancestor_ids': ['22_57', '20_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_91', 'origin': '22_57~CUW~20_81#MGNP'} Metrics: ['ELUC: -6.681643129186768', 'NSGA-II_crowding_distance: 0.292462215770864', 'NSGA-II_rank: 5', 'change: 0.15813718267442503', 'is_elite: False']\n", + "Id: 23_52 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_83', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_52', 'origin': '22_83~CUW~22_86#MGNP'} Metrics: ['ELUC: -7.126780563403394', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2589646908720559', 'is_elite: False']\n", + "Id: 21_81 Identity: {'ancestor_count': 16, 'ancestor_ids': ['18_61', '19_70'], 'birth_generation': 21, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '21_81', 'origin': '18_61~CUW~19_70#MGNP'} Metrics: ['ELUC: -7.1497333512433885', 'NSGA-II_crowding_distance: 0.08377616797974309', 'NSGA-II_rank: 1', 'change: 0.10223086687595745', 'is_elite: False']\n", + "Id: 23_82 Identity: {'ancestor_count': 18, 'ancestor_ids': ['21_81', '22_87'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_82', 'origin': '21_81~CUW~22_87#MGNP'} Metrics: ['ELUC: -7.471344788671419', 'NSGA-II_crowding_distance: 0.1770423619754209', 'NSGA-II_rank: 1', 'change: 0.10403508451352605', 'is_elite: False']\n", + "Id: 23_38 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_49', '21_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_38', 'origin': '22_49~CUW~21_81#MGNP'} Metrics: ['ELUC: -7.743726563696858', 'NSGA-II_crowding_distance: 0.2733353307662252', 'NSGA-II_rank: 4', 'change: 0.1461395348832401', 'is_elite: False']\n", + "Id: 23_90 Identity: {'ancestor_count': 18, 'ancestor_ids': ['1_1', '20_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_90', 'origin': '1_1~CUW~20_81#MGNP'} Metrics: ['ELUC: -8.63193053065197', 'NSGA-II_crowding_distance: 0.9297379805563575', 'NSGA-II_rank: 6', 'change: 0.171165432943753', 'is_elite: False']\n", + "Id: 23_54 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '21_22'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_54', 'origin': '22_86~CUW~21_22#MGNP'} Metrics: ['ELUC: -8.753029387712123', 'NSGA-II_crowding_distance: 0.24502576709875484', 'NSGA-II_rank: 5', 'change: 0.15981305193468603', 'is_elite: False']\n", + "Id: 23_35 Identity: {'ancestor_count': 21, 'ancestor_ids': ['20_81', '22_40'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_35', 'origin': '20_81~CUW~22_40#MGNP'} Metrics: ['ELUC: -8.95324051914951', 'NSGA-II_crowding_distance: 0.27674325752843265', 'NSGA-II_rank: 4', 'change: 0.15518926360119012', 'is_elite: False']\n", + "Id: 23_81 Identity: {'ancestor_count': 20, 'ancestor_ids': ['20_81', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_81', 'origin': '20_81~CUW~22_49#MGNP'} Metrics: ['ELUC: -9.210319374530362', 'NSGA-II_crowding_distance: 0.5042446437402404', 'NSGA-II_rank: 3', 'change: 0.13434458693168233', 'is_elite: False']\n", + "Id: 23_32 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_76', '22_40'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_32', 'origin': '22_76~CUW~22_40#MGNP'} Metrics: ['ELUC: -9.252891920472381', 'NSGA-II_crowding_distance: 0.20786268031679556', 'NSGA-II_rank: 3', 'change: 0.1430360433350573', 'is_elite: False']\n", + "Id: 20_81 Identity: {'ancestor_count': 17, 'ancestor_ids': ['16_39', '18_95'], 'birth_generation': 20, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '20_81', 'origin': '16_39~CUW~18_95#MGNP'} Metrics: ['ELUC: -9.271583900826883', 'NSGA-II_crowding_distance: 0.3737232281190702', 'NSGA-II_rank: 2', 'change: 0.11768885314187973', 'is_elite: False']\n", + "Id: 23_21 Identity: {'ancestor_count': 20, 'ancestor_ids': ['1_1', '22_37'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_21', 'origin': '1_1~CUW~22_37#MGNP'} Metrics: ['ELUC: -9.27874069717094', 'NSGA-II_crowding_distance: 0.49610046095227', 'NSGA-II_rank: 5', 'change: 0.17522258345001804', 'is_elite: False']\n", + "Id: 23_31 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '20_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_31', 'origin': '20_81~CUW~20_81#MGNP'} Metrics: ['ELUC: -9.352266002328594', 'NSGA-II_crowding_distance: 0.20459285844465952', 'NSGA-II_rank: 1', 'change: 0.11767870435069881', 'is_elite: False']\n", + "Id: 23_15 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_49', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_15', 'origin': '22_49~CUW~22_91#MGNP'} Metrics: ['ELUC: -9.371932527036279', 'NSGA-II_crowding_distance: 0.8099513875560329', 'NSGA-II_rank: 6', 'change: 0.27196611258342923', 'is_elite: False']\n", + "Id: 23_36 Identity: {'ancestor_count': 21, 'ancestor_ids': ['20_81', '22_40'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_36', 'origin': '20_81~CUW~22_40#MGNP'} Metrics: ['ELUC: -9.440008064710081', 'NSGA-II_crowding_distance: 0.21715348775265292', 'NSGA-II_rank: 1', 'change: 0.13167221152015396', 'is_elite: False']\n", + "Id: 23_94 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_91', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_94', 'origin': '22_91~CUW~22_49#MGNP'} Metrics: ['ELUC: -9.496184586145146', 'NSGA-II_crowding_distance: 0.4603439506942619', 'NSGA-II_rank: 5', 'change: 0.24893321124448237', 'is_elite: False']\n", + "Id: 23_73 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '22_52'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_73', 'origin': '22_40~CUW~22_52#MGNP'} Metrics: ['ELUC: -9.606689352938556', 'NSGA-II_crowding_distance: 0.25923126550022807', 'NSGA-II_rank: 2', 'change: 0.15119473529856597', 'is_elite: False']\n", + "Id: 23_83 Identity: {'ancestor_count': 20, 'ancestor_ids': ['20_78', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_83', 'origin': '20_78~CUW~22_49#MGNP'} Metrics: ['ELUC: -9.8617165269105', 'NSGA-II_crowding_distance: 0.20308887917341756', 'NSGA-II_rank: 4', 'change: 0.17475646632715963', 'is_elite: False']\n", + "Id: 23_22 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_81', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_22', 'origin': '21_81~CUW~22_91#MGNP'} Metrics: ['ELUC: -10.262223366671169', 'NSGA-II_crowding_distance: 0.2029636679808003', 'NSGA-II_rank: 5', 'change: 0.2543702060126613', 'is_elite: False']\n", + "Id: 23_66 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '21_13'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_66', 'origin': '22_86~CUW~21_13#MGNP'} Metrics: ['ELUC: -10.471191759723391', 'NSGA-II_crowding_distance: 0.3237025056653475', 'NSGA-II_rank: 4', 'change: 0.17664060902143283', 'is_elite: False']\n", + "Id: 23_28 Identity: {'ancestor_count': 18, 'ancestor_ids': ['22_46', '20_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_28', 'origin': '22_46~CUW~20_81#MGNP'} Metrics: ['ELUC: -10.526654173007774', 'NSGA-II_crowding_distance: 0.5419498390332422', 'NSGA-II_rank: 4', 'change: 0.23070762215768653', 'is_elite: False']\n", + "Id: 23_23 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_37', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_23', 'origin': '22_37~CUW~22_49#MGNP'} Metrics: ['ELUC: -10.87812557993874', 'NSGA-II_crowding_distance: 0.24473740553169687', 'NSGA-II_rank: 3', 'change: 0.16318530396169553', 'is_elite: False']\n", + "Id: 23_50 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_83', '1_1'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_50', 'origin': '22_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.05291404141207', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2779117051773874', 'is_elite: False']\n", + "Id: 23_49 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_85', '22_46'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_49', 'origin': '22_85~CUW~22_46#MGNP'} Metrics: ['ELUC: -11.109737566962563', 'NSGA-II_crowding_distance: 0.1692273915412833', 'NSGA-II_rank: 5', 'change: 0.26957943424880065', 'is_elite: False']\n", + "Id: 23_13 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_37', '21_13'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_13', 'origin': '22_37~CUW~21_13#MGNP'} Metrics: ['ELUC: -11.368081507006359', 'NSGA-II_crowding_distance: 0.30768568652218153', 'NSGA-II_rank: 3', 'change: 0.1748141420400776', 'is_elite: False']\n", + "Id: 23_88 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '20_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_88', 'origin': '22_40~CUW~20_81#MGNP'} Metrics: ['ELUC: -11.496781518411897', 'NSGA-II_crowding_distance: 0.26058337396393877', 'NSGA-II_rank: 2', 'change: 0.15471727480976558', 'is_elite: False']\n", + "Id: 23_39 Identity: {'ancestor_count': 20, 'ancestor_ids': ['2_49', '22_37'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_39', 'origin': '2_49~CUW~22_37#MGNP'} Metrics: ['ELUC: -11.547389363366836', 'NSGA-II_crowding_distance: 0.0707299332594244', 'NSGA-II_rank: 5', 'change: 0.2723114765296819', 'is_elite: False']\n", + "Id: 23_86 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_13', '20_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_86', 'origin': '21_13~CUW~20_81#MGNP'} Metrics: ['ELUC: -11.57549841842239', 'NSGA-II_crowding_distance: 0.4155790970453307', 'NSGA-II_rank: 2', 'change: 0.19241240585775196', 'is_elite: False']\n", + "Id: 23_93 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_93', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.727726513784988', 'NSGA-II_crowding_distance: 0.23895739558906254', 'NSGA-II_rank: 5', 'change: 0.27610181747511453', 'is_elite: False']\n", + "Id: 23_30 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '22_57'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_30', 'origin': '21_22~CUW~22_57#MGNP'} Metrics: ['ELUC: -11.762947710675855', 'NSGA-II_crowding_distance: 0.400204766022971', 'NSGA-II_rank: 3', 'change: 0.22865477415933816', 'is_elite: False']\n", + "Id: 22_40 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_63', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_40', 'origin': '21_63~CUW~21_63#MGNP'} Metrics: ['ELUC: -11.78103137121908', 'NSGA-II_crowding_distance: 0.4925467614375679', 'NSGA-II_rank: 1', 'change: 0.14125556891696645', 'is_elite: True']\n", + "Id: 23_40 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_83', '22_87'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_40', 'origin': '22_83~CUW~22_87#MGNP'} Metrics: ['ELUC: -11.888587265211441', 'NSGA-II_crowding_distance: 0.4126530980905194', 'NSGA-II_rank: 4', 'change: 0.26654321814026133', 'is_elite: False']\n", + "Id: 23_76 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_76', 'origin': '21_22~CUW~22_83#MGNP'} Metrics: ['ELUC: -12.728962384653878', 'NSGA-II_crowding_distance: 0.2499817728662272', 'NSGA-II_rank: 3', 'change: 0.2569498643273276', 'is_elite: False']\n", + "Id: 23_44 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '21_13'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_44', 'origin': '22_40~CUW~21_13#MGNP'} Metrics: ['ELUC: -13.469518723577258', 'NSGA-II_crowding_distance: 0.3651083662781006', 'NSGA-II_rank: 1', 'change: 0.21025515077304308', 'is_elite: True']\n", + "Id: 23_65 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_81', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_65', 'origin': '21_81~CUW~22_91#MGNP'} Metrics: ['ELUC: -13.811547737061456', 'NSGA-II_crowding_distance: 0.2458412218605673', 'NSGA-II_rank: 4', 'change: 0.2718064805691188', 'is_elite: False']\n", + "Id: 23_84 Identity: {'ancestor_count': 19, 'ancestor_ids': ['1_1', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_84', 'origin': '1_1~CUW~22_83#MGNP'} Metrics: ['ELUC: -13.940651732096914', 'NSGA-II_crowding_distance: 0.11358109491252656', 'NSGA-II_rank: 3', 'change: 0.2608666363078806', 'is_elite: False']\n", + "Id: 23_14 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_37', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_14', 'origin': '22_37~CUW~22_49#MGNP'} Metrics: ['ELUC: -14.048914922639296', 'NSGA-II_crowding_distance: 0.05367874123997071', 'NSGA-II_rank: 1', 'change: 0.21170908598903213', 'is_elite: False']\n", + "Id: 23_87 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_49', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_87', 'origin': '22_49~CUW~22_83#MGNP'} Metrics: ['ELUC: -14.161246811174555', 'NSGA-II_crowding_distance: 0.07130426625819522', 'NSGA-II_rank: 3', 'change: 0.2652172478450397', 'is_elite: False']\n", + "Id: 23_48 Identity: {'ancestor_count': 20, 'ancestor_ids': ['2_49', '22_76'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_48', 'origin': '2_49~CUW~22_76#MGNP'} Metrics: ['ELUC: -14.171947403679619', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28786533792304597', 'is_elite: False']\n", + "Id: 22_49 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_13', '21_13'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_49', 'origin': '21_13~CUW~21_13#MGNP'} Metrics: ['ELUC: -14.252417370508274', 'NSGA-II_crowding_distance: 0.06028109002471251', 'NSGA-II_rank: 1', 'change: 0.21298565959202997', 'is_elite: False']\n", + "Id: 23_85 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_85', 'origin': '2_49~CUW~22_86#MGNP'} Metrics: ['ELUC: -14.324798328005052', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28508489218763305', 'is_elite: False']\n", + "Id: 23_99 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_99', 'origin': '22_40~CUW~22_49#MGNP'} Metrics: ['ELUC: -14.373107405878066', 'NSGA-II_crowding_distance: 0.30673492308740946', 'NSGA-II_rank: 2', 'change: 0.22438096511366243', 'is_elite: False']\n", + "Id: 23_69 Identity: {'ancestor_count': 19, 'ancestor_ids': ['1_1', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_69', 'origin': '1_1~CUW~22_83#MGNP'} Metrics: ['ELUC: -14.432161775222509', 'NSGA-II_crowding_distance: 0.33814290499800626', 'NSGA-II_rank: 3', 'change: 0.2719192286821482', 'is_elite: False']\n", + "Id: 23_55 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_33', '20_81'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_55', 'origin': '22_33~CUW~20_81#MGNP'} Metrics: ['ELUC: -14.551854220333716', 'NSGA-II_crowding_distance: 0.46783552283896457', 'NSGA-II_rank: 2', 'change: 0.23110580285382484', 'is_elite: False']\n", + "Id: 23_80 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_13', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_80', 'origin': '21_13~CUW~22_49#MGNP'} Metrics: ['ELUC: -14.610480714494422', 'NSGA-II_crowding_distance: 0.2420701986439166', 'NSGA-II_rank: 1', 'change: 0.2201656753062077', 'is_elite: True']\n", + "Id: 23_79 Identity: {'ancestor_count': 20, 'ancestor_ids': ['20_81', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_79', 'origin': '20_81~CUW~22_91#MGNP'} Metrics: ['ELUC: -14.755829079760806', 'NSGA-II_crowding_distance: 0.28503952324215676', 'NSGA-II_rank: 1', 'change: 0.27667096033985283', 'is_elite: True']\n", + "Id: 23_64 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_81', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_64', 'origin': '21_81~CUW~22_83#MGNP'} Metrics: ['ELUC: -15.788094475922291', 'NSGA-II_crowding_distance: 0.11021248566254918', 'NSGA-II_rank: 1', 'change: 0.28523064832299067', 'is_elite: False']\n", + "Id: 22_83 Identity: {'ancestor_count': 18, 'ancestor_ids': ['20_81', '21_93'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_83', 'origin': '20_81~CUW~21_93#MGNP'} Metrics: ['ELUC: -16.08729769975913', 'NSGA-II_crowding_distance: 0.1086178670077367', 'NSGA-II_rank: 1', 'change: 0.2869604771100083', 'is_elite: False']\n", + "Id: 23_60 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_57', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_60', 'origin': '22_57~CUW~22_91#MGNP'} Metrics: ['ELUC: -16.967526060693974', 'NSGA-II_crowding_distance: 0.11894292221149788', 'NSGA-II_rank: 1', 'change: 0.2976244817643477', 'is_elite: False']\n", + "Id: 23_34 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_83', '2_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_34', 'origin': '22_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.348693082309435', 'NSGA-II_crowding_distance: 0.045501665538809535', 'NSGA-II_rank: 1', 'change: 0.30104412601692676', 'is_elite: False']\n", + "Id: 23_20 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_20', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.495148039508496', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3032067710505784', 'is_elite: False']\n", + "Id: 23_43 Identity: {'ancestor_count': 20, 'ancestor_ids': ['1_1', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_43', 'origin': '1_1~CUW~22_91#MGNP'} Metrics: ['ELUC: -17.541872640490492', 'NSGA-II_crowding_distance: 0.019989709796564035', 'NSGA-II_rank: 1', 'change: 0.3014543262736812', 'is_elite: False']\n", + "Id: 23_24 Identity: {'ancestor_count': 18, 'ancestor_ids': ['22_57', '2_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_24', 'origin': '22_57~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.586449057531734', 'NSGA-II_crowding_distance: 0.008334490496421883', 'NSGA-II_rank: 1', 'change: 0.3029738177687332', 'is_elite: False']\n", + "Id: 23_17 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_91', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_17', 'origin': '22_91~CUW~22_91#MGNP'} Metrics: ['ELUC: -17.596361692776995', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302437957274864', 'is_elite: False']\n", + "Id: 23_77 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_77', 'origin': '2_49~CUW~22_86#MGNP'} Metrics: ['ELUC: -17.59691421462941', 'NSGA-II_crowding_distance: 0.0007784156188782618', 'NSGA-II_rank: 1', 'change: 0.3030070800232848', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 22_91 Identity: {'ancestor_count': 19, 'ancestor_ids': ['21_22', '2_49'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_91', 'origin': '21_22~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 23_26 Identity: {'ancestor_count': 20, 'ancestor_ids': ['22_91', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_26', 'origin': '22_91~CUW~22_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 23_62 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_62', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 23_75 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_75', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 23_97 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_97', 'origin': '2_49~CUW~22_83#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 23.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 24...:\n", + "PopulationResponse:\n", + " Generation: 24\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/24/20240219-223316\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 24 and asking ESP for generation 25...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 24 data persisted.\n", + "Evaluated candidates:\n", + "Id: 24_96 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_96', 'origin': '23_59~CUW~2_49#MGNP'} Metrics: ['ELUC: 17.617344660399436', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2787769276559083', 'is_elite: False']\n", + "Id: 24_81 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '23_80'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_81', 'origin': '2_49~CUW~23_80#MGNP'} Metrics: ['ELUC: 10.988833677534917', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2910780369179037', 'is_elite: False']\n", + "Id: 24_38 Identity: {'ancestor_count': 19, 'ancestor_ids': ['23_31', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_38', 'origin': '23_31~CUW~2_49#MGNP'} Metrics: ['ELUC: 10.823084960238917', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25611055065214217', 'is_elite: False']\n", + "Id: 24_31 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_31', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 9.777188593244727', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2906301432072212', 'is_elite: False']\n", + "Id: 24_76 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_41', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_76', 'origin': '23_41~CUW~2_49#MGNP'} Metrics: ['ELUC: 7.669628362693144', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26262665233374033', 'is_elite: False']\n", + "Id: 24_67 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_67', 'origin': '22_86~CUW~2_49#MGNP'} Metrics: ['ELUC: 5.875113696321654', 'NSGA-II_crowding_distance: 1.184874836581646', 'NSGA-II_rank: 9', 'change: 0.2590199838877239', 'is_elite: False']\n", + "Id: 24_73 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_73', 'origin': '23_80~CUW~1_1#MGNP'} Metrics: ['ELUC: 4.248376296141709', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.1339750708161836', 'is_elite: False']\n", + "Id: 24_47 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_44', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_47', 'origin': '23_44~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.139302170702498', 'NSGA-II_crowding_distance: 1.4306328316412533', 'NSGA-II_rank: 9', 'change: 0.2653268122342036', 'is_elite: False']\n", + "Id: 24_56 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_41', '23_80'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_56', 'origin': '23_41~CUW~23_80#MGNP'} Metrics: ['ELUC: 2.106520211698987', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09165364068272051', 'is_elite: False']\n", + "Id: 24_80 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_31', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_80', 'origin': '23_31~CUW~23_79#MGNP'} Metrics: ['ELUC: 1.4856843816075713', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.28473544350838115', 'is_elite: False']\n", + "Id: 24_84 Identity: {'ancestor_count': 19, 'ancestor_ids': ['1_1', '22_86'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_84', 'origin': '1_1~CUW~22_86#MGNP'} Metrics: ['ELUC: 1.2303543473436183', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04597013137335759', 'is_elite: False']\n", + "Id: 24_51 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_41', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_51', 'origin': '23_41~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.6971994310560451', 'NSGA-II_crowding_distance: 0.1757721564923841', 'NSGA-II_rank: 3', 'change: 0.05181552285408409', 'is_elite: False']\n", + "Id: 24_100 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_100', 'origin': '22_86~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.28389225406708324', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06281273728278602', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 24_62 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_79', '23_63'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_62', 'origin': '23_79~CUW~23_63#MGNP'} Metrics: ['ELUC: -0.01878316997451174', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.302562827156292', 'is_elite: False']\n", + "Id: 24_21 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '23_63'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_21', 'origin': '23_97~CUW~23_63#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 24_37 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_37', 'origin': '23_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 24_15 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '23_29'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_15', 'origin': '23_97~CUW~23_29#MGNP'} Metrics: ['ELUC: -0.5643344949159794', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23867870427048823', 'is_elite: False']\n", + "Id: 24_44 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_44', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6894781338386565', 'NSGA-II_crowding_distance: 0.23086448348867647', 'NSGA-II_rank: 1', 'change: 0.0396868065314051', 'is_elite: False']\n", + "Id: 24_92 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '23_41'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_92', 'origin': '1_1~CUW~23_41#MGNP'} Metrics: ['ELUC: -0.843832515490666', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04579952535850475', 'is_elite: False']\n", + "Id: 24_66 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_66', 'origin': '22_86~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.101870729472442', 'NSGA-II_crowding_distance: 0.5912200914797054', 'NSGA-II_rank: 3', 'change: 0.05801962667475899', 'is_elite: False']\n", + "Id: 24_27 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_41', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_27', 'origin': '23_41~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4653879452289085', 'NSGA-II_crowding_distance: 0.18190557699796395', 'NSGA-II_rank: 2', 'change: 0.04968116593353883', 'is_elite: False']\n", + "Id: 23_59 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_87', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_59', 'origin': '22_87~CUW~22_86#MGNP'} Metrics: ['ELUC: -1.883463714994084', 'NSGA-II_crowding_distance: 0.24283385485532777', 'NSGA-II_rank: 1', 'change: 0.04181996822749041', 'is_elite: True']\n", + "Id: 24_46 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_46', 'origin': '23_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.082663615256929', 'NSGA-II_crowding_distance: 0.24147353206431993', 'NSGA-II_rank: 2', 'change: 0.07346430982409465', 'is_elite: False']\n", + "Id: 24_79 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '23_82'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_79', 'origin': '23_80~CUW~23_82#MGNP'} Metrics: ['ELUC: -2.6127226797252234', 'NSGA-II_crowding_distance: 0.7483532704798791', 'NSGA-II_rank: 6', 'change: 0.16868991519774787', 'is_elite: False']\n", + "Id: 24_34 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '23_59'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_34', 'origin': '23_80~CUW~23_59#MGNP'} Metrics: ['ELUC: -2.7523721547109616', 'NSGA-II_crowding_distance: 0.15950825745338237', 'NSGA-II_rank: 6', 'change: 0.18339671394644583', 'is_elite: False']\n", + "Id: 24_86 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_41', '23_29'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_86', 'origin': '23_41~CUW~23_29#MGNP'} Metrics: ['ELUC: -3.22960230206823', 'NSGA-II_crowding_distance: 0.2810362352164212', 'NSGA-II_rank: 2', 'change: 0.08455627233443096', 'is_elite: False']\n", + "Id: 24_52 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '23_41'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_52', 'origin': '1_1~CUW~23_41#MGNP'} Metrics: ['ELUC: -3.3462378859549227', 'NSGA-II_crowding_distance: 0.19491423417003112', 'NSGA-II_rank: 1', 'change: 0.06705698539414495', 'is_elite: False']\n", + "Id: 24_17 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_86', '22_40'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_17', 'origin': '22_86~CUW~22_40#MGNP'} Metrics: ['ELUC: -3.3917844489269933', 'NSGA-II_crowding_distance: 0.298153029252143', 'NSGA-II_rank: 6', 'change: 0.186107571049449', 'is_elite: False']\n", + "Id: 24_71 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_79', '23_63'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_71', 'origin': '23_79~CUW~23_63#MGNP'} Metrics: ['ELUC: -3.7069135490723415', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26882481062809666', 'is_elite: False']\n", + "Id: 24_64 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_44', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_64', 'origin': '23_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.715584117147679', 'NSGA-II_crowding_distance: 0.5016971228530261', 'NSGA-II_rank: 3', 'change: 0.14361398985191642', 'is_elite: False']\n", + "Id: 23_41 Identity: {'ancestor_count': 20, 'ancestor_ids': ['20_78', '22_76'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_41', 'origin': '20_78~CUW~22_76#MGNP'} Metrics: ['ELUC: -3.7293255869377386', 'NSGA-II_crowding_distance: 0.05249564754671882', 'NSGA-II_rank: 1', 'change: 0.06865318711571738', 'is_elite: False']\n", + "Id: 24_41 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_41', '23_29'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_41', 'origin': '23_41~CUW~23_29#MGNP'} Metrics: ['ELUC: -3.7475855106965916', 'NSGA-II_crowding_distance: 0.11548254488705537', 'NSGA-II_rank: 1', 'change: 0.07590952384935769', 'is_elite: False']\n", + "Id: 24_60 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_29'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_60', 'origin': '22_40~CUW~23_29#MGNP'} Metrics: ['ELUC: -3.991583349963058', 'NSGA-II_crowding_distance: 0.7933464562064505', 'NSGA-II_rank: 5', 'change: 0.1491641224110264', 'is_elite: False']\n", + "Id: 24_11 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_11', 'origin': '23_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.232162287740156', 'NSGA-II_crowding_distance: 1.1990940597240096', 'NSGA-II_rank: 7', 'change: 0.24723101958765173', 'is_elite: False']\n", + "Id: 24_57 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_60', '23_82'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_57', 'origin': '23_60~CUW~23_82#MGNP'} Metrics: ['ELUC: -4.270150974986873', 'NSGA-II_crowding_distance: 0.7425807109197917', 'NSGA-II_rank: 6', 'change: 0.21535962772193462', 'is_elite: False']\n", + "Id: 24_30 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_36', '23_63'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_30', 'origin': '23_36~CUW~23_63#MGNP'} Metrics: ['ELUC: -4.289885214414285', 'NSGA-II_crowding_distance: 0.23969515098646563', 'NSGA-II_rank: 3', 'change: 0.14423296215445816', 'is_elite: False']\n", + "Id: 24_88 Identity: {'ancestor_count': 22, 'ancestor_ids': ['1_1', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_88', 'origin': '1_1~CUW~23_44#MGNP'} Metrics: ['ELUC: -5.02681240778635', 'NSGA-II_crowding_distance: 0.6515776514847178', 'NSGA-II_rank: 5', 'change: 0.15327633526000808', 'is_elite: False']\n", + "Id: 23_63 Identity: {'ancestor_count': 18, 'ancestor_ids': ['22_57', '22_57'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_63', 'origin': '22_57~CUW~22_57#MGNP'} Metrics: ['ELUC: -5.043030744265139', 'NSGA-II_crowding_distance: 0.15307566997558378', 'NSGA-II_rank: 1', 'change: 0.0808166235475437', 'is_elite: False']\n", + "Id: 24_94 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_29', '23_41'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_94', 'origin': '23_29~CUW~23_41#MGNP'} Metrics: ['ELUC: -5.123998735413668', 'NSGA-II_crowding_distance: 0.4012467051675227', 'NSGA-II_rank: 2', 'change: 0.09879186004413204', 'is_elite: False']\n", + "Id: 24_58 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_44', '23_29'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_58', 'origin': '23_44~CUW~23_29#MGNP'} Metrics: ['ELUC: -5.192017897306606', 'NSGA-II_crowding_distance: 0.8857451424015272', 'NSGA-II_rank: 4', 'change: 0.1485996449346321', 'is_elite: False']\n", + "Id: 24_83 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '23_63'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_83', 'origin': '23_80~CUW~23_63#MGNP'} Metrics: ['ELUC: -5.3748844801419065', 'NSGA-II_crowding_distance: 0.3535895212719374', 'NSGA-II_rank: 4', 'change: 0.1837101758061915', 'is_elite: False']\n", + "Id: 24_93 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_41', '23_29'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_93', 'origin': '23_41~CUW~23_29#MGNP'} Metrics: ['ELUC: -5.536182281583993', 'NSGA-II_crowding_distance: 0.08238633875920555', 'NSGA-II_rank: 1', 'change: 0.09123085399279365', 'is_elite: False']\n", + "Id: 24_65 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_29'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_65', 'origin': '23_59~CUW~23_29#MGNP'} Metrics: ['ELUC: -5.610076960679795', 'NSGA-II_crowding_distance: 0.22453944235792914', 'NSGA-II_rank: 1', 'change: 0.09577592196409329', 'is_elite: False']\n", + "Id: 24_97 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '23_63'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_97', 'origin': '23_97~CUW~23_63#MGNP'} Metrics: ['ELUC: -6.103985433105777', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.257103222260243', 'is_elite: False']\n", + "Id: 24_14 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_97', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_14', 'origin': '23_97~CUW~23_44#MGNP'} Metrics: ['ELUC: -6.642909624057585', 'NSGA-II_crowding_distance: 1.3018136856476727', 'NSGA-II_rank: 7', 'change: 0.2544358156315249', 'is_elite: False']\n", + "Id: 24_13 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_79', '23_31'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_13', 'origin': '23_79~CUW~23_31#MGNP'} Metrics: ['ELUC: -6.773329889181609', 'NSGA-II_crowding_distance: 0.8018763577563437', 'NSGA-II_rank: 5', 'change: 0.2397504374928177', 'is_elite: False']\n", + "Id: 24_91 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_29', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_91', 'origin': '23_29~CUW~23_44#MGNP'} Metrics: ['ELUC: -6.94374771306388', 'NSGA-II_crowding_distance: 0.5881545149336593', 'NSGA-II_rank: 4', 'change: 0.20494099472455224', 'is_elite: False']\n", + "Id: 24_68 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_36', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_68', 'origin': '23_36~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.791941071436817', 'NSGA-II_crowding_distance: 0.4291328921142906', 'NSGA-II_rank: 2', 'change: 0.11731780370941658', 'is_elite: False']\n", + "Id: 24_29 Identity: {'ancestor_count': 22, 'ancestor_ids': ['1_1', '23_36'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_29', 'origin': '1_1~CUW~23_36#MGNP'} Metrics: ['ELUC: -7.840499399675001', 'NSGA-II_crowding_distance: 0.23705501793867975', 'NSGA-II_rank: 3', 'change: 0.14593470675130565', 'is_elite: False']\n", + "Id: 24_40 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_86', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_40', 'origin': '22_86~CUW~23_44#MGNP'} Metrics: ['ELUC: -7.999692513748888', 'NSGA-II_crowding_distance: 0.22805760357620447', 'NSGA-II_rank: 3', 'change: 0.15205085942961186', 'is_elite: False']\n", + "Id: 24_63 Identity: {'ancestor_count': 19, 'ancestor_ids': ['23_82', '23_82'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_63', 'origin': '23_82~CUW~23_82#MGNP'} Metrics: ['ELUC: -8.012128328937315', 'NSGA-II_crowding_distance: 0.26905553330322796', 'NSGA-II_rank: 1', 'change: 0.11621085215956267', 'is_elite: True']\n", + "Id: 24_20 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_86', '23_36'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_20', 'origin': '22_86~CUW~23_36#MGNP'} Metrics: ['ELUC: -8.328743977837002', 'NSGA-II_crowding_distance: 0.29829360087004675', 'NSGA-II_rank: 1', 'change: 0.12991947994356276', 'is_elite: True']\n", + "Id: 24_42 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '23_41'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_42', 'origin': '2_49~CUW~23_41#MGNP'} Metrics: ['ELUC: -8.346650889883755', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2763734513917318', 'is_elite: False']\n", + "Id: 24_61 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_79', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_61', 'origin': '23_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.397751355064567', 'NSGA-II_crowding_distance: 0.7557160695158108', 'NSGA-II_rank: 6', 'change: 0.2538821341600152', 'is_elite: False']\n", + "Id: 24_99 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_63', '23_36'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_99', 'origin': '23_63~CUW~23_36#MGNP'} Metrics: ['ELUC: -9.493488138629354', 'NSGA-II_crowding_distance: 0.3337951045254743', 'NSGA-II_rank: 2', 'change: 0.1417064288988777', 'is_elite: False']\n", + "Id: 24_87 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_44', '23_31'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_87', 'origin': '23_44~CUW~23_31#MGNP'} Metrics: ['ELUC: -9.623612064872734', 'NSGA-II_crowding_distance: 0.2995198026369334', 'NSGA-II_rank: 3', 'change: 0.1801361581437716', 'is_elite: False']\n", + "Id: 24_36 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_86', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_36', 'origin': '22_86~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.004082136920285', 'NSGA-II_crowding_distance: 0.45224807987251325', 'NSGA-II_rank: 6', 'change: 0.27816083887394255', 'is_elite: False']\n", + "Id: 24_24 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_44', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_24', 'origin': '23_44~CUW~23_79#MGNP'} Metrics: ['ELUC: -10.112526216956455', 'NSGA-II_crowding_distance: 0.39594188122322105', 'NSGA-II_rank: 5', 'change: 0.2431611042329365', 'is_elite: False']\n", + "Id: 24_53 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_53', 'origin': '22_40~CUW~23_79#MGNP'} Metrics: ['ELUC: -10.117012285943778', 'NSGA-II_crowding_distance: 0.1878925686529549', 'NSGA-II_rank: 5', 'change: 0.2733165939390267', 'is_elite: False']\n", + "Id: 24_89 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_41', '23_97'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_89', 'origin': '23_41~CUW~23_97#MGNP'} Metrics: ['ELUC: -10.44182755803123', 'NSGA-II_crowding_distance: 0.2494308854116432', 'NSGA-II_rank: 5', 'change: 0.2754265522501417', 'is_elite: False']\n", + "Id: 24_85 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_31', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_85', 'origin': '23_31~CUW~23_44#MGNP'} Metrics: ['ELUC: -10.529261110790838', 'NSGA-II_crowding_distance: 0.29437728346237263', 'NSGA-II_rank: 3', 'change: 0.1941650227066823', 'is_elite: False']\n", + "Id: 24_32 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '22_40'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_32', 'origin': '22_40~CUW~22_40#MGNP'} Metrics: ['ELUC: -11.701567444886253', 'NSGA-II_crowding_distance: 0.47696667349171973', 'NSGA-II_rank: 2', 'change: 0.14280744770940906', 'is_elite: False']\n", + "Id: 22_40 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_63', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_40', 'origin': '21_63~CUW~21_63#MGNP'} Metrics: ['ELUC: -11.78103137121908', 'NSGA-II_crowding_distance: 0.29229190534909294', 'NSGA-II_rank: 1', 'change: 0.14125556891696645', 'is_elite: True']\n", + "Id: 24_95 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '23_60'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_95', 'origin': '2_49~CUW~23_60#MGNP'} Metrics: ['ELUC: -11.948021161725244', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2903171727408024', 'is_elite: False']\n", + "Id: 24_25 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_80'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_25', 'origin': '22_40~CUW~23_80#MGNP'} Metrics: ['ELUC: -12.30144775386429', 'NSGA-II_crowding_distance: 0.19557805730666478', 'NSGA-II_rank: 1', 'change: 0.14971486325256977', 'is_elite: False']\n", + "Id: 24_82 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_36', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_82', 'origin': '23_36~CUW~23_44#MGNP'} Metrics: ['ELUC: -12.46910693900906', 'NSGA-II_crowding_distance: 0.7384858799274066', 'NSGA-II_rank: 4', 'change: 0.21084534771827732', 'is_elite: False']\n", + "Id: 24_18 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_36', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_18', 'origin': '23_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.863467431620423', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28614667642684527', 'is_elite: False']\n", + "Id: 24_72 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_80', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_72', 'origin': '23_80~CUW~23_44#MGNP'} Metrics: ['ELUC: -13.075581913126474', 'NSGA-II_crowding_distance: 0.47456048581911586', 'NSGA-II_rank: 3', 'change: 0.20709821180966553', 'is_elite: False']\n", + "Id: 24_90 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_80', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_90', 'origin': '23_80~CUW~23_44#MGNP'} Metrics: ['ELUC: -13.27119173260037', 'NSGA-II_crowding_distance: 0.3624615996206228', 'NSGA-II_rank: 2', 'change: 0.206067838371366', 'is_elite: False']\n", + "Id: 24_28 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_44', '23_63'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_28', 'origin': '23_44~CUW~23_63#MGNP'} Metrics: ['ELUC: -13.373688646679582', 'NSGA-II_crowding_distance: 0.09160735702459073', 'NSGA-II_rank: 2', 'change: 0.210231916442169', 'is_elite: False']\n", + "Id: 24_98 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_80', '23_36'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_98', 'origin': '23_80~CUW~23_36#MGNP'} Metrics: ['ELUC: -13.406851610670017', 'NSGA-II_crowding_distance: 0.26933248686933386', 'NSGA-II_rank: 1', 'change: 0.17202103214860573', 'is_elite: True']\n", + "Id: 23_44 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '21_13'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_44', 'origin': '22_40~CUW~21_13#MGNP'} Metrics: ['ELUC: -13.469518723577258', 'NSGA-II_crowding_distance: 0.17525202112840743', 'NSGA-II_rank: 1', 'change: 0.21025515077304308', 'is_elite: False']\n", + "Id: 24_35 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_80', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_35', 'origin': '23_80~CUW~23_44#MGNP'} Metrics: ['ELUC: -13.58815101078526', 'NSGA-II_crowding_distance: 0.3292141860359413', 'NSGA-II_rank: 2', 'change: 0.22474026652021326', 'is_elite: False']\n", + "Id: 24_26 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '22_86'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_26', 'origin': '23_97~CUW~22_86#MGNP'} Metrics: ['ELUC: -13.680011205530782', 'NSGA-II_crowding_distance: 0.5261003426648134', 'NSGA-II_rank: 4', 'change: 0.2735932660687457', 'is_elite: False']\n", + "Id: 24_55 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_97', '23_80'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_55', 'origin': '23_97~CUW~23_80#MGNP'} Metrics: ['ELUC: -13.737237613907102', 'NSGA-II_crowding_distance: 0.33380300095156934', 'NSGA-II_rank: 3', 'change: 0.27284073689426747', 'is_elite: False']\n", + "Id: 24_54 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_44', '23_80'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_54', 'origin': '23_44~CUW~23_80#MGNP'} Metrics: ['ELUC: -14.157726148812115', 'NSGA-II_crowding_distance: 0.06222739248162408', 'NSGA-II_rank: 1', 'change: 0.2115697573444551', 'is_elite: False']\n", + "Id: 24_77 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_77', 'origin': '23_80~CUW~1_1#MGNP'} Metrics: ['ELUC: -14.29008184547873', 'NSGA-II_crowding_distance: 0.054559377867740955', 'NSGA-II_rank: 1', 'change: 0.21489720886325606', 'is_elite: False']\n", + "Id: 24_39 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_79', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_39', 'origin': '23_79~CUW~23_79#MGNP'} Metrics: ['ELUC: -14.530409746579744', 'NSGA-II_crowding_distance: 0.0713987723349078', 'NSGA-II_rank: 3', 'change: 0.2744143890264361', 'is_elite: False']\n", + "Id: 23_80 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_13', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_80', 'origin': '21_13~CUW~22_49#MGNP'} Metrics: ['ELUC: -14.610480714494422', 'NSGA-II_crowding_distance: 0.25147610786002783', 'NSGA-II_rank: 1', 'change: 0.2201656753062077', 'is_elite: True']\n", + "Id: 24_49 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_49', 'origin': '2_49~CUW~23_79#MGNP'} Metrics: ['ELUC: -14.674650201777126', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.30105879247068806', 'is_elite: False']\n", + "Id: 23_79 Identity: {'ancestor_count': 20, 'ancestor_ids': ['20_81', '22_91'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_79', 'origin': '20_81~CUW~22_91#MGNP'} Metrics: ['ELUC: -14.755829079760806', 'NSGA-II_crowding_distance: 0.07325792447015995', 'NSGA-II_rank: 3', 'change: 0.27667096033985283', 'is_elite: False']\n", + "Id: 24_12 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_64', '23_41'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_12', 'origin': '23_64~CUW~23_41#MGNP'} Metrics: ['ELUC: -14.814682798637824', 'NSGA-II_crowding_distance: 0.33567116136535835', 'NSGA-II_rank: 2', 'change: 0.2726726413547709', 'is_elite: False']\n", + "Id: 24_22 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '22_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_22', 'origin': '23_97~CUW~22_49#MGNP'} Metrics: ['ELUC: -14.837479993550488', 'NSGA-II_crowding_distance: 0.239996641924953', 'NSGA-II_rank: 3', 'change: 0.28937035772473657', 'is_elite: False']\n", + "Id: 24_48 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '22_83'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_48', 'origin': '23_97~CUW~22_83#MGNP'} Metrics: ['ELUC: -15.35537933017492', 'NSGA-II_crowding_distance: 0.09758020183479102', 'NSGA-II_rank: 2', 'change: 0.2838032964049983', 'is_elite: False']\n", + "Id: 24_43 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_97', '23_44'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_43', 'origin': '23_97~CUW~23_44#MGNP'} Metrics: ['ELUC: -15.645829593967512', 'NSGA-II_crowding_distance: 0.20368010378965523', 'NSGA-II_rank: 2', 'change: 0.28493975950993733', 'is_elite: False']\n", + "Id: 24_50 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_50', 'origin': '22_40~CUW~23_79#MGNP'} Metrics: ['ELUC: -15.75657546098187', 'NSGA-II_crowding_distance: 0.2906967709703919', 'NSGA-II_rank: 1', 'change: 0.26504522656463747', 'is_elite: True']\n", + "Id: 24_16 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_81', '23_97'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_16', 'origin': '21_81~CUW~23_97#MGNP'} Metrics: ['ELUC: -16.110715053868358', 'NSGA-II_crowding_distance: 0.12158888498256767', 'NSGA-II_rank: 1', 'change: 0.281443674340751', 'is_elite: False']\n", + "Id: 24_33 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_97'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_33', 'origin': '23_59~CUW~23_97#MGNP'} Metrics: ['ELUC: -16.535189899800525', 'NSGA-II_crowding_distance: 0.15455259718486505', 'NSGA-II_rank: 1', 'change: 0.2881113131881894', 'is_elite: False']\n", + "Id: 24_59 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '22_83'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_59', 'origin': '22_40~CUW~22_83#MGNP'} Metrics: ['ELUC: -16.6267291543721', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.31274595891610024', 'is_elite: False']\n", + "Id: 24_19 Identity: {'ancestor_count': 20, 'ancestor_ids': ['2_49', '23_97'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_19', 'origin': '2_49~CUW~23_97#MGNP'} Metrics: ['ELUC: -17.50047673906931', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030722005889741', 'is_elite: False']\n", + "Id: 24_70 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_70', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.568417179009817', 'NSGA-II_crowding_distance: 0.11038008696193582', 'NSGA-II_rank: 1', 'change: 0.30282107075858383', 'is_elite: False']\n", + "Id: 24_23 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_97', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_23', 'origin': '23_97~CUW~23_79#MGNP'} Metrics: ['ELUC: -17.59738818401554', 'NSGA-II_crowding_distance: 0.0023159082780592755', 'NSGA-II_rank: 1', 'change: 0.303020439029682', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 23_97 Identity: {'ancestor_count': 19, 'ancestor_ids': ['2_49', '22_83'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_97', 'origin': '2_49~CUW~22_83#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 24_45 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '2_49'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_45', 'origin': '22_40~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 24_69 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_97'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_69', 'origin': '22_40~CUW~23_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 24_74 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_74', 'origin': '2_49~CUW~23_79#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 24_75 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '23_97'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_75', 'origin': '23_97~CUW~23_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 24_78 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '23_97'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_78', 'origin': '23_97~CUW~23_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 24.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 25...:\n", + "PopulationResponse:\n", + " Generation: 25\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/25/20240219-224029\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 25 and asking ESP for generation 26...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 25 data persisted.\n", + "Evaluated candidates:\n", + "Id: 25_38 Identity: {'ancestor_count': 23, 'ancestor_ids': ['2_49', '24_20'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_38', 'origin': '2_49~CUW~24_20#MGNP'} Metrics: ['ELUC: 22.778540980711785', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.29941332970748863', 'is_elite: False']\n", + "Id: 25_48 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_63', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_48', 'origin': '24_63~CUW~24_78#MGNP'} Metrics: ['ELUC: 17.081795795497367', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.28150831302231816', 'is_elite: False']\n", + "Id: 25_77 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_65', '2_49'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_77', 'origin': '24_65~CUW~2_49#MGNP'} Metrics: ['ELUC: 14.246307723429979', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2711893321591665', 'is_elite: False']\n", + "Id: 25_65 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_50', '2_49'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_65', 'origin': '24_50~CUW~2_49#MGNP'} Metrics: ['ELUC: 7.612084920639522', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.25921538077114814', 'is_elite: False']\n", + "Id: 25_49 Identity: {'ancestor_count': 20, 'ancestor_ids': ['2_49', '23_59'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_49', 'origin': '2_49~CUW~23_59#MGNP'} Metrics: ['ELUC: 2.5213176540056748', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3499211695661923', 'is_elite: False']\n", + "Id: 25_93 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_20', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_93', 'origin': '24_20~CUW~24_78#MGNP'} Metrics: ['ELUC: 0.8022920569056199', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.21709676654887922', 'is_elite: False']\n", + "Id: 25_41 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_41', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.3696059839180058', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04331325213321688', 'is_elite: False']\n", + "Id: 25_85 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_85', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.2621256521799968', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03571766285241984', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 25_12 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_44', '24_52'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_12', 'origin': '24_44~CUW~24_52#MGNP'} Metrics: ['ELUC: -0.031088350504065207', 'NSGA-II_crowding_distance: 0.4146478745120614', 'NSGA-II_rank: 2', 'change: 0.054588180607115226', 'is_elite: False']\n", + "Id: 25_82 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_63', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_82', 'origin': '24_63~CUW~22_40#MGNP'} Metrics: ['ELUC: -0.07159760233639752', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.10135920689601126', 'is_elite: False']\n", + "Id: 25_18 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_78', '24_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_18', 'origin': '24_78~CUW~24_63#MGNP'} Metrics: ['ELUC: -0.44125044923973455', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.26384777665825515', 'is_elite: False']\n", + "Id: 25_99 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_52', '24_25'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_99', 'origin': '24_52~CUW~24_25#MGNP'} Metrics: ['ELUC: -0.5037858623617409', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.13859872004701718', 'is_elite: False']\n", + "Id: 25_91 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_91', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6767632511629323', 'NSGA-II_crowding_distance: 0.23086448348867647', 'NSGA-II_rank: 1', 'change: 0.027591555327354134', 'is_elite: True']\n", + "Id: 25_100 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_98', '24_44'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_100', 'origin': '24_98~CUW~24_44#MGNP'} Metrics: ['ELUC: -0.8473588467596341', 'NSGA-II_crowding_distance: 0.29295443977807256', 'NSGA-II_rank: 5', 'change: 0.1302360409299079', 'is_elite: False']\n", + "Id: 25_81 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_81', 'origin': '24_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9383442560348314', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09228363911614221', 'is_elite: False']\n", + "Id: 25_68 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_65', '24_25'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_68', 'origin': '24_65~CUW~24_25#MGNP'} Metrics: ['ELUC: -1.0273026113378625', 'NSGA-II_crowding_distance: 0.6433645443360508', 'NSGA-II_rank: 5', 'change: 0.13089830182112638', 'is_elite: False']\n", + "Id: 25_45 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_44', '24_20'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_45', 'origin': '24_44~CUW~24_20#MGNP'} Metrics: ['ELUC: -1.0345013733867194', 'NSGA-II_crowding_distance: 0.7505298293128176', 'NSGA-II_rank: 4', 'change: 0.09383675570339867', 'is_elite: False']\n", + "Id: 25_55 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_78', '24_41'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_55', 'origin': '24_78~CUW~24_41#MGNP'} Metrics: ['ELUC: -1.1591353948289045', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.25632151693884053', 'is_elite: False']\n", + "Id: 25_76 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_41', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_76', 'origin': '24_41~CUW~22_40#MGNP'} Metrics: ['ELUC: -1.588637180301549', 'NSGA-II_crowding_distance: 0.8587920554162849', 'NSGA-II_rank: 3', 'change: 0.08354723202778776', 'is_elite: False']\n", + "Id: 25_83 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_63', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_83', 'origin': '24_63~CUW~22_40#MGNP'} Metrics: ['ELUC: -1.8507578344930593', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15127630325464256', 'is_elite: False']\n", + "Id: 23_59 Identity: {'ancestor_count': 19, 'ancestor_ids': ['22_87', '22_86'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_59', 'origin': '22_87~CUW~22_86#MGNP'} Metrics: ['ELUC: -1.883463714994084', 'NSGA-II_crowding_distance: 0.1483381047314788', 'NSGA-II_rank: 1', 'change: 0.04181996822749041', 'is_elite: False']\n", + "Id: 25_80 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_78', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_80', 'origin': '24_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8887784839489423', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.25417454587931976', 'is_elite: False']\n", + "Id: 25_32 Identity: {'ancestor_count': 19, 'ancestor_ids': ['24_44', '23_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_32', 'origin': '24_44~CUW~23_63#MGNP'} Metrics: ['ELUC: -2.2160301849299606', 'NSGA-II_crowding_distance: 0.06613881127770266', 'NSGA-II_rank: 1', 'change: 0.04573050575293195', 'is_elite: False']\n", + "Id: 25_70 Identity: {'ancestor_count': 23, 'ancestor_ids': ['23_59', '24_20'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_70', 'origin': '23_59~CUW~24_20#MGNP'} Metrics: ['ELUC: -2.2941463298912543', 'NSGA-II_crowding_distance: 0.5449959593921956', 'NSGA-II_rank: 7', 'change: 0.16048725470725309', 'is_elite: False']\n", + "Id: 25_88 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '23_80'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_88', 'origin': '1_1~CUW~23_80#MGNP'} Metrics: ['ELUC: -2.41900898765612', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.17123539170632393', 'is_elite: False']\n", + "Id: 25_19 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_59', '24_52'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_19', 'origin': '23_59~CUW~24_52#MGNP'} Metrics: ['ELUC: -2.5764743530781913', 'NSGA-II_crowding_distance: 0.1858622584549352', 'NSGA-II_rank: 1', 'change: 0.04979371147598602', 'is_elite: False']\n", + "Id: 25_40 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_98', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_40', 'origin': '24_98~CUW~24_78#MGNP'} Metrics: ['ELUC: -2.768611149140589', 'NSGA-II_crowding_distance: 0.7917646222900743', 'NSGA-II_rank: 8', 'change: 0.2550694313063208', 'is_elite: False']\n", + "Id: 25_21 Identity: {'ancestor_count': 2, 'ancestor_ids': ['24_44', '2_49'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_21', 'origin': '24_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.1850821108869134', 'NSGA-II_crowding_distance: 0.7883488950162432', 'NSGA-II_rank: 8', 'change: 0.2608714353930467', 'is_elite: False']\n", + "Id: 25_73 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_44', '24_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_73', 'origin': '24_44~CUW~24_63#MGNP'} Metrics: ['ELUC: -4.013557327728033', 'NSGA-II_crowding_distance: 0.45292609413542684', 'NSGA-II_rank: 2', 'change: 0.08081311108747395', 'is_elite: False']\n", + "Id: 25_23 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_23', 'origin': '24_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.159026014020856', 'NSGA-II_crowding_distance: 0.2535145973920721', 'NSGA-II_rank: 1', 'change: 0.06821442363038034', 'is_elite: True']\n", + "Id: 25_58 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_20', '24_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_58', 'origin': '24_20~CUW~24_63#MGNP'} Metrics: ['ELUC: -4.619074220272259', 'NSGA-II_crowding_distance: 0.16189897177429344', 'NSGA-II_rank: 2', 'change: 0.10511906896006518', 'is_elite: False']\n", + "Id: 25_66 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_63', '24_65'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_66', 'origin': '24_63~CUW~24_65#MGNP'} Metrics: ['ELUC: -4.766108682992675', 'NSGA-II_crowding_distance: 0.12484791161393309', 'NSGA-II_rank: 1', 'change: 0.08827804825243991', 'is_elite: False']\n", + "Id: 25_25 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '23_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_25', 'origin': '24_63~CUW~23_63#MGNP'} Metrics: ['ELUC: -5.098317430482428', 'NSGA-II_crowding_distance: 0.06765761278715551', 'NSGA-II_rank: 1', 'change: 0.08952619334520183', 'is_elite: False']\n", + "Id: 25_72 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_44', '24_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_72', 'origin': '24_44~CUW~24_63#MGNP'} Metrics: ['ELUC: -5.133887273558544', 'NSGA-II_crowding_distance: 0.23690074461871435', 'NSGA-II_rank: 2', 'change: 0.10689943479977118', 'is_elite: False']\n", + "Id: 25_51 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_65', '23_44'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_51', 'origin': '24_65~CUW~23_44#MGNP'} Metrics: ['ELUC: -5.152658494203841', 'NSGA-II_crowding_distance: 0.6407564216383494', 'NSGA-II_rank: 7', 'change: 0.16634386489910427', 'is_elite: False']\n", + "Id: 25_75 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_65', '24_20'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_75', 'origin': '24_65~CUW~24_20#MGNP'} Metrics: ['ELUC: -5.175118877055654', 'NSGA-II_crowding_distance: 0.8735251899758971', 'NSGA-II_rank: 6', 'change: 0.14753639771434718', 'is_elite: False']\n", + "Id: 25_56 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '24_44'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_56', 'origin': '24_63~CUW~24_44#MGNP'} Metrics: ['ELUC: -5.510281396922506', 'NSGA-II_crowding_distance: 0.08896269418729061', 'NSGA-II_rank: 1', 'change: 0.09583673183030371', 'is_elite: False']\n", + "Id: 25_27 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_52', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_27', 'origin': '24_52~CUW~22_40#MGNP'} Metrics: ['ELUC: -5.839199272330659', 'NSGA-II_crowding_distance: 0.20992862641403898', 'NSGA-II_rank: 1', 'change: 0.10349768552912968', 'is_elite: False']\n", + "Id: 25_34 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_34', 'origin': '23_80~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.897215038035894', 'NSGA-II_crowding_distance: 0.7367508257551447', 'NSGA-II_rank: 7', 'change: 0.1825761923375022', 'is_elite: False']\n", + "Id: 25_13 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '24_33'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_13', 'origin': '1_1~CUW~24_33#MGNP'} Metrics: ['ELUC: -6.266578735392844', 'NSGA-II_crowding_distance: 0.8149742286282448', 'NSGA-II_rank: 7', 'change: 0.23922593100370226', 'is_elite: False']\n", + "Id: 25_98 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_78', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_98', 'origin': '24_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.307257091750467', 'NSGA-II_crowding_distance: 1.137170568824684', 'NSGA-II_rank: 8', 'change: 0.28851713944162477', 'is_elite: False']\n", + "Id: 25_16 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_20', '23_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_16', 'origin': '24_20~CUW~23_63#MGNP'} Metrics: ['ELUC: -7.282395581610069', 'NSGA-II_crowding_distance: 0.9175548991092055', 'NSGA-II_rank: 5', 'change: 0.1431587715856075', 'is_elite: False']\n", + "Id: 25_26 Identity: {'ancestor_count': 23, 'ancestor_ids': ['23_59', '24_20'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_26', 'origin': '23_59~CUW~24_20#MGNP'} Metrics: ['ELUC: -7.669311938691262', 'NSGA-II_crowding_distance: 0.9851060262954969', 'NSGA-II_rank: 4', 'change: 0.139428655613303', 'is_elite: False']\n", + "Id: 25_20 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_63', '24_65'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_20', 'origin': '24_63~CUW~24_65#MGNP'} Metrics: ['ELUC: -7.766990782325144', 'NSGA-II_crowding_distance: 0.7956164107666128', 'NSGA-II_rank: 3', 'change: 0.12347396587108149', 'is_elite: False']\n", + "Id: 25_59 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '23_59'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_59', 'origin': '23_80~CUW~23_59#MGNP'} Metrics: ['ELUC: -7.821129428977017', 'NSGA-II_crowding_distance: 0.5242007828244877', 'NSGA-II_rank: 6', 'change: 0.17037197005180676', 'is_elite: False']\n", + "Id: 24_63 Identity: {'ancestor_count': 19, 'ancestor_ids': ['23_82', '23_82'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_63', 'origin': '23_82~CUW~23_82#MGNP'} Metrics: ['ELUC: -8.012128328937315', 'NSGA-II_crowding_distance: 0.26999244264312344', 'NSGA-II_rank: 2', 'change: 0.11621085215956267', 'is_elite: False']\n", + "Id: 25_64 Identity: {'ancestor_count': 22, 'ancestor_ids': ['1_1', '24_50'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_64', 'origin': '1_1~CUW~24_50#MGNP'} Metrics: ['ELUC: -8.060561086063005', 'NSGA-II_crowding_distance: 0.2296315762705719', 'NSGA-II_rank: 6', 'change: 0.18615488845998346', 'is_elite: False']\n", + "Id: 25_24 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '24_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_24', 'origin': '24_63~CUW~24_63#MGNP'} Metrics: ['ELUC: -8.062977090717059', 'NSGA-II_crowding_distance: 0.27557812540557775', 'NSGA-II_rank: 1', 'change: 0.11515472297873304', 'is_elite: True']\n", + "Id: 24_20 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_86', '23_36'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_20', 'origin': '22_86~CUW~23_36#MGNP'} Metrics: ['ELUC: -8.328743977837002', 'NSGA-II_crowding_distance: 0.18523490238252888', 'NSGA-II_rank: 2', 'change: 0.12991947994356276', 'is_elite: False']\n", + "Id: 25_35 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_20', '24_16'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_35', 'origin': '24_20~CUW~24_16#MGNP'} Metrics: ['ELUC: -8.54246667242968', 'NSGA-II_crowding_distance: 0.6571101526293275', 'NSGA-II_rank: 7', 'change: 0.2410441871294593', 'is_elite: False']\n", + "Id: 25_29 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_50', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_29', 'origin': '24_50~CUW~22_40#MGNP'} Metrics: ['ELUC: -8.766477919520726', 'NSGA-II_crowding_distance: 0.3801371565745061', 'NSGA-II_rank: 5', 'change: 0.16656041468281266', 'is_elite: False']\n", + "Id: 25_47 Identity: {'ancestor_count': 22, 'ancestor_ids': ['1_1', '24_50'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_47', 'origin': '1_1~CUW~24_50#MGNP'} Metrics: ['ELUC: -8.824064580804707', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2985970277374418', 'is_elite: False']\n", + "Id: 25_43 Identity: {'ancestor_count': 22, 'ancestor_ids': ['1_1', '24_25'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_43', 'origin': '1_1~CUW~24_25#MGNP'} Metrics: ['ELUC: -8.836622241356073', 'NSGA-II_crowding_distance: 0.6558255311107629', 'NSGA-II_rank: 6', 'change: 0.19051606157971607', 'is_elite: False']\n", + "Id: 25_28 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_70', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_28', 'origin': '24_70~CUW~22_40#MGNP'} Metrics: ['ELUC: -8.875741835506103', 'NSGA-II_crowding_distance: 0.5267309699140673', 'NSGA-II_rank: 8', 'change: 0.29733349399381115', 'is_elite: False']\n", + "Id: 25_96 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_65', '24_25'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_96', 'origin': '24_65~CUW~24_25#MGNP'} Metrics: ['ELUC: -8.952076534369397', 'NSGA-II_crowding_distance: 0.39333008249888046', 'NSGA-II_rank: 5', 'change: 0.1763423959640014', 'is_elite: False']\n", + "Id: 25_50 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_50', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 25_86 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_98', '24_50'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_86', 'origin': '24_98~CUW~24_50#MGNP'} Metrics: ['ELUC: -9.307847513858947', 'NSGA-II_crowding_distance: 0.4124713961327417', 'NSGA-II_rank: 7', 'change: 0.2721274501147436', 'is_elite: False']\n", + "Id: 25_11 Identity: {'ancestor_count': 23, 'ancestor_ids': ['22_40', '24_98'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_11', 'origin': '22_40~CUW~24_98#MGNP'} Metrics: ['ELUC: -9.565411678261201', 'NSGA-II_crowding_distance: 0.4538230899740622', 'NSGA-II_rank: 4', 'change: 0.1603458651581945', 'is_elite: False']\n", + "Id: 25_67 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '24_65'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_67', 'origin': '22_40~CUW~24_65#MGNP'} Metrics: ['ELUC: -9.61215153131204', 'NSGA-II_crowding_distance: 0.219516985639923', 'NSGA-II_rank: 2', 'change: 0.14114370479353697', 'is_elite: False']\n", + "Id: 25_78 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_78', 'origin': '23_80~CUW~22_40#MGNP'} Metrics: ['ELUC: -9.622093632736611', 'NSGA-II_crowding_distance: 0.4870619154599813', 'NSGA-II_rank: 3', 'change: 0.1501896089574427', 'is_elite: False']\n", + "Id: 25_97 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_20', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_97', 'origin': '24_20~CUW~22_40#MGNP'} Metrics: ['ELUC: -9.632442613188546', 'NSGA-II_crowding_distance: 0.2989411359042248', 'NSGA-II_rank: 1', 'change: 0.12135154826882022', 'is_elite: True']\n", + "Id: 25_36 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '24_44'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_36', 'origin': '2_49~CUW~24_44#MGNP'} Metrics: ['ELUC: -9.672911149089895', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2739021631840793', 'is_elite: False']\n", + "Id: 25_53 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_53', 'origin': '2_49~CUW~22_40#MGNP'} Metrics: ['ELUC: -9.837866397279793', 'NSGA-II_crowding_distance: 0.896843233753531', 'NSGA-II_rank: 6', 'change: 0.25826760269807963', 'is_elite: False']\n", + "Id: 25_62 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_50', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_62', 'origin': '24_50~CUW~22_40#MGNP'} Metrics: ['ELUC: -10.877634296418902', 'NSGA-II_crowding_distance: 0.20590581799278318', 'NSGA-II_rank: 2', 'change: 0.14938762490624685', 'is_elite: False']\n", + "Id: 25_84 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_44', '23_80'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_84', 'origin': '24_44~CUW~23_80#MGNP'} Metrics: ['ELUC: -10.955197185419072', 'NSGA-II_crowding_distance: 0.7036849431919109', 'NSGA-II_rank: 5', 'change: 0.19537169677862634', 'is_elite: False']\n", + "Id: 25_74 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_20', '24_25'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_74', 'origin': '24_20~CUW~24_25#MGNP'} Metrics: ['ELUC: -11.491892912799004', 'NSGA-II_crowding_distance: 0.25861097667030747', 'NSGA-II_rank: 4', 'change: 0.17170599369722592', 'is_elite: False']\n", + "Id: 25_92 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_92', 'origin': '1_1~CUW~24_78#MGNP'} Metrics: ['ELUC: -11.68176273209535', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.28374586018857023', 'is_elite: False']\n", + "Id: 25_33 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_50', '24_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_33', 'origin': '24_50~CUW~24_63#MGNP'} Metrics: ['ELUC: -11.750361317015635', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.24127420499242744', 'is_elite: False']\n", + "Id: 22_40 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_63', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_40', 'origin': '21_63~CUW~21_63#MGNP'} Metrics: ['ELUC: -11.78103137121908', 'NSGA-II_crowding_distance: 0.256448761063439', 'NSGA-II_rank: 1', 'change: 0.14125556891696645', 'is_elite: True']\n", + "Id: 25_44 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_50', '23_80'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_44', 'origin': '24_50~CUW~23_80#MGNP'} Metrics: ['ELUC: -11.781521612509033', 'NSGA-II_crowding_distance: 0.7956470807131201', 'NSGA-II_rank: 4', 'change: 0.17816294363997173', 'is_elite: False']\n", + "Id: 25_37 Identity: {'ancestor_count': 23, 'ancestor_ids': ['23_80', '24_98'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_37', 'origin': '23_80~CUW~24_98#MGNP'} Metrics: ['ELUC: -12.31210632304362', 'NSGA-II_crowding_distance: 0.6044544135422114', 'NSGA-II_rank: 3', 'change: 0.1700066723723403', 'is_elite: False']\n", + "Id: 25_30 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_50', '23_80'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_30', 'origin': '24_50~CUW~23_80#MGNP'} Metrics: ['ELUC: -12.334929933706162', 'NSGA-II_crowding_distance: 0.373118529165117', 'NSGA-II_rank: 3', 'change: 0.25297808445462033', 'is_elite: False']\n", + "Id: 25_14 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_25', '24_25'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_14', 'origin': '24_25~CUW~24_25#MGNP'} Metrics: ['ELUC: -12.434368652611273', 'NSGA-II_crowding_distance: 0.36560692544482765', 'NSGA-II_rank: 2', 'change: 0.1527438729287705', 'is_elite: False']\n", + "Id: 25_15 Identity: {'ancestor_count': 23, 'ancestor_ids': ['22_40', '24_20'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_15', 'origin': '22_40~CUW~24_20#MGNP'} Metrics: ['ELUC: -12.455041381052169', 'NSGA-II_crowding_distance: 0.08771307646491705', 'NSGA-II_rank: 1', 'change: 0.14996977252385235', 'is_elite: False']\n", + "Id: 25_60 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_63', '24_20'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_60', 'origin': '24_63~CUW~24_20#MGNP'} Metrics: ['ELUC: -12.478780659492097', 'NSGA-II_crowding_distance: 0.12803829072482134', 'NSGA-II_rank: 1', 'change: 0.15558617574728997', 'is_elite: False']\n", + "Id: 25_46 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_50', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_46', 'origin': '24_50~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.535916517587108', 'NSGA-II_crowding_distance: 0.2603941574956996', 'NSGA-II_rank: 3', 'change: 0.25577472598403694', 'is_elite: False']\n", + "Id: 25_22 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_80', '23_44'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_22', 'origin': '23_80~CUW~23_44#MGNP'} Metrics: ['ELUC: -13.388053089470105', 'NSGA-II_crowding_distance: 0.6104961113365214', 'NSGA-II_rank: 2', 'change: 0.2085988086817181', 'is_elite: False']\n", + "Id: 24_98 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_80', '23_36'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_98', 'origin': '23_80~CUW~23_36#MGNP'} Metrics: ['ELUC: -13.406851610670017', 'NSGA-II_crowding_distance: 0.11799609263189698', 'NSGA-II_rank: 1', 'change: 0.17202103214860573', 'is_elite: False']\n", + "Id: 25_52 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_98', '24_98'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_52', 'origin': '24_98~CUW~24_98#MGNP'} Metrics: ['ELUC: -13.487569263179255', 'NSGA-II_crowding_distance: 0.07558334086860427', 'NSGA-II_rank: 1', 'change: 0.1736741266909393', 'is_elite: False']\n", + "Id: 25_63 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_98', '23_80'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_63', 'origin': '24_98~CUW~23_80#MGNP'} Metrics: ['ELUC: -13.625325501599855', 'NSGA-II_crowding_distance: 0.12961517698397784', 'NSGA-II_rank: 1', 'change: 0.19086584738593249', 'is_elite: False']\n", + "Id: 25_42 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_20', '24_98'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_42', 'origin': '24_20~CUW~24_98#MGNP'} Metrics: ['ELUC: -14.00597081660518', 'NSGA-II_crowding_distance: 0.13716080282010273', 'NSGA-II_rank: 1', 'change: 0.2035509728311177', 'is_elite: False']\n", + "Id: 25_61 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_78', '24_65'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_61', 'origin': '24_78~CUW~24_65#MGNP'} Metrics: ['ELUC: -14.029230594913576', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2917482552297347', 'is_elite: False']\n", + "Id: 25_39 Identity: {'ancestor_count': 22, 'ancestor_ids': ['23_80', '23_44'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_39', 'origin': '23_80~CUW~23_44#MGNP'} Metrics: ['ELUC: -14.535518336508328', 'NSGA-II_crowding_distance: 0.09006511022202132', 'NSGA-II_rank: 1', 'change: 0.21634532133237466', 'is_elite: False']\n", + "Id: 23_80 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_13', '22_49'], 'birth_generation': 23, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '23_80', 'origin': '21_13~CUW~22_49#MGNP'} Metrics: ['ELUC: -14.610480714494422', 'NSGA-II_crowding_distance: 0.19857676682345188', 'NSGA-II_rank: 1', 'change: 0.2201656753062077', 'is_elite: False']\n", + "Id: 25_54 Identity: {'ancestor_count': 22, 'ancestor_ids': ['2_49', '24_50'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_54', 'origin': '2_49~CUW~24_50#MGNP'} Metrics: ['ELUC: -14.884656591043454', 'NSGA-II_crowding_distance: 0.28102749995861687', 'NSGA-II_rank: 3', 'change: 0.2760124081691003', 'is_elite: False']\n", + "Id: 25_71 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_71', 'origin': '22_40~CUW~24_78#MGNP'} Metrics: ['ELUC: -15.172303025320746', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.28240922790506556', 'is_elite: False']\n", + "Id: 24_50 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_79'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_50', 'origin': '22_40~CUW~23_79#MGNP'} Metrics: ['ELUC: -15.75657546098187', 'NSGA-II_crowding_distance: 0.5683367999857711', 'NSGA-II_rank: 2', 'change: 0.26504522656463747', 'is_elite: False']\n", + "Id: 25_90 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_25', '23_44'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_90', 'origin': '24_25~CUW~23_44#MGNP'} Metrics: ['ELUC: -15.931057853488165', 'NSGA-II_crowding_distance: 0.323184082528302', 'NSGA-II_rank: 1', 'change: 0.25191346748114796', 'is_elite: True']\n", + "Id: 25_79 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_78', '24_65'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_79', 'origin': '24_78~CUW~24_65#MGNP'} Metrics: ['ELUC: -16.342405763783766', 'NSGA-II_crowding_distance: 0.21048742619816724', 'NSGA-II_rank: 1', 'change: 0.2872053013626268', 'is_elite: True']\n", + "Id: 25_95 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_63', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_95', 'origin': '24_63~CUW~24_78#MGNP'} Metrics: ['ELUC: -17.092743709479887', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30369638336416444', 'is_elite: False']\n", + "Id: 25_89 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_33', '2_49'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_89', 'origin': '24_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.10641142896241', 'NSGA-II_crowding_distance: 0.09721721221428295', 'NSGA-II_rank: 1', 'change: 0.2947721122323972', 'is_elite: False']\n", + "Id: 25_94 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '24_33'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_94', 'origin': '1_1~CUW~24_33#MGNP'} Metrics: ['ELUC: -17.374180050874863', 'NSGA-II_crowding_distance: 0.054676398412894275', 'NSGA-II_rank: 1', 'change: 0.2987032233292299', 'is_elite: False']\n", + "Id: 25_57 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_57', 'origin': '2_49~CUW~24_78#MGNP'} Metrics: ['ELUC: -17.587246848626638', 'NSGA-II_crowding_distance: 0.027163981690731313', 'NSGA-II_rank: 1', 'change: 0.302926405771258', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 24_78 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_97', '23_97'], 'birth_generation': 24, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '24_78', 'origin': '23_97~CUW~23_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 25_17 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_17', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 25_31 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_59', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_31', 'origin': '23_59~CUW~24_78#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 25_69 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_50', '2_49'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_69', 'origin': '24_50~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 25_87 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_98', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_87', 'origin': '24_98~CUW~24_78#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 25.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 26...:\n", + "PopulationResponse:\n", + " Generation: 26\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/26/20240219-224741\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 26 and asking ESP for generation 27...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 26 data persisted.\n", + "Evaluated candidates:\n", + "Id: 26_71 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_79', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_71', 'origin': '25_79~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.831838971468095', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037910757013925', 'is_elite: False']\n", + "Id: 26_13 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_27', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_13', 'origin': '25_27~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.494727890340172', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.30096071648536893', 'is_elite: False']\n", + "Id: 26_11 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_11', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 22.643081648296317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3042292903147794', 'is_elite: False']\n", + "Id: 26_42 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_42', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 19.4334099700507', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2747032183256976', 'is_elite: False']\n", + "Id: 26_94 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_79', '23_80'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_94', 'origin': '25_79~CUW~23_80#MGNP'} Metrics: ['ELUC: 15.5235255029356', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24136428848986294', 'is_elite: False']\n", + "Id: 26_36 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_36', 'origin': '25_23~CUW~2_49#MGNP'} Metrics: ['ELUC: 6.34982706711586', 'NSGA-II_crowding_distance: 1.2651668465746317', 'NSGA-II_rank: 8', 'change: 0.26136576718460613', 'is_elite: False']\n", + "Id: 26_14 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_79', '22_40'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_14', 'origin': '25_79~CUW~22_40#MGNP'} Metrics: ['ELUC: 5.725360860961902', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.237343267284073', 'is_elite: False']\n", + "Id: 26_73 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '23_80'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_73', 'origin': '1_1~CUW~23_80#MGNP'} Metrics: ['ELUC: 2.675104075433428', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09627638067972297', 'is_elite: False']\n", + "Id: 26_91 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_91', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.5274550702704044', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.351627749496774', 'is_elite: False']\n", + "Id: 26_63 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_97', '25_91'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_63', 'origin': '25_97~CUW~25_91#MGNP'} Metrics: ['ELUC: 1.1438183517301332', 'NSGA-II_crowding_distance: 0.34727691852142273', 'NSGA-II_rank: 5', 'change: 0.10212684108787197', 'is_elite: False']\n", + "Id: 26_21 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_21', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.8126279567284359', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.021369793221530695', 'is_elite: False']\n", + "Id: 26_43 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_60', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_43', 'origin': '25_60~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.616042740160847', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11717800783917764', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 26_26 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_60', '25_19'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_26', 'origin': '25_60~CUW~25_19#MGNP'} Metrics: ['ELUC: -0.5230245239372341', 'NSGA-II_crowding_distance: 0.7173682824301388', 'NSGA-II_rank: 5', 'change: 0.11646973141534943', 'is_elite: False']\n", + "Id: 25_91 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_91', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6767632511629323', 'NSGA-II_crowding_distance: 0.2604517177260295', 'NSGA-II_rank: 1', 'change: 0.027591555327354134', 'is_elite: True']\n", + "Id: 26_72 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_23', '25_19'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_72', 'origin': '25_23~CUW~25_19#MGNP'} Metrics: ['ELUC: -0.9481791616600572', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04756983008201606', 'is_elite: False']\n", + "Id: 26_16 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_16', 'origin': '23_80~CUW~23_59#MGNP'} Metrics: ['ELUC: -1.2341561360709834', 'NSGA-II_crowding_distance: 0.22317911984078626', 'NSGA-II_rank: 2', 'change: 0.04621491564797238', 'is_elite: False']\n", + "Id: 26_30 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_27', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_30', 'origin': '25_27~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.3442959856602785', 'NSGA-II_crowding_distance: 0.12752316559949892', 'NSGA-II_rank: 3', 'change: 0.0635716646989717', 'is_elite: False']\n", + "Id: 26_55 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_24', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_55', 'origin': '25_24~CUW~23_59#MGNP'} Metrics: ['ELUC: -1.4239559625132456', 'NSGA-II_crowding_distance: 0.09798375585845501', 'NSGA-II_rank: 2', 'change: 0.04999749820053015', 'is_elite: False']\n", + "Id: 26_66 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '25_27'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_66', 'origin': '25_87~CUW~25_27#MGNP'} Metrics: ['ELUC: -1.8333825068042473', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2688642445656915', 'is_elite: False']\n", + "Id: 26_41 Identity: {'ancestor_count': 23, 'ancestor_ids': ['2_49', '25_90'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_41', 'origin': '2_49~CUW~25_90#MGNP'} Metrics: ['ELUC: -1.8811413711034508', 'NSGA-II_crowding_distance: 0.9129103854788518', 'NSGA-II_rank: 8', 'change: 0.2680467812921823', 'is_elite: False']\n", + "Id: 26_57 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_91', '25_23'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_57', 'origin': '25_91~CUW~25_23#MGNP'} Metrics: ['ELUC: -1.8985279747154438', 'NSGA-II_crowding_distance: 0.21174128675959164', 'NSGA-II_rank: 3', 'change: 0.06532441629834244', 'is_elite: False']\n", + "Id: 26_64 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '25_27'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_64', 'origin': '25_87~CUW~25_27#MGNP'} Metrics: ['ELUC: -1.9492962177118554', 'NSGA-II_crowding_distance: 0.7348331534253683', 'NSGA-II_rank: 8', 'change: 0.2985161477991596', 'is_elite: False']\n", + "Id: 26_22 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_22', 'origin': '25_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0240404004516916', 'NSGA-II_crowding_distance: 0.13532071992600161', 'NSGA-II_rank: 2', 'change: 0.06172681001759504', 'is_elite: False']\n", + "Id: 26_69 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_69', 'origin': '23_59~CUW~23_59#MGNP'} Metrics: ['ELUC: -2.3593292124774066', 'NSGA-II_crowding_distance: 0.334200363186414', 'NSGA-II_rank: 1', 'change: 0.04257255541510991', 'is_elite: True']\n", + "Id: 26_65 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '25_23'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_65', 'origin': '1_1~CUW~25_23#MGNP'} Metrics: ['ELUC: -2.555783525658449', 'NSGA-II_crowding_distance: 0.1239063816006028', 'NSGA-II_rank: 2', 'change: 0.07079258969397648', 'is_elite: False']\n", + "Id: 26_54 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_19', '25_27'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_54', 'origin': '25_19~CUW~25_27#MGNP'} Metrics: ['ELUC: -3.084115962493461', 'NSGA-II_crowding_distance: 0.13526141583856938', 'NSGA-II_rank: 2', 'change: 0.08040435132230506', 'is_elite: False']\n", + "Id: 26_19 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_97', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_19', 'origin': '25_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.1309103146030246', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09106522066540908', 'is_elite: False']\n", + "Id: 26_99 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_97', '25_19'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_99', 'origin': '25_97~CUW~25_19#MGNP'} Metrics: ['ELUC: -3.1915425236094985', 'NSGA-II_crowding_distance: 0.2381337210034576', 'NSGA-II_rank: 3', 'change: 0.08877116866464957', 'is_elite: False']\n", + "Id: 26_18 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_18', 'origin': '25_23~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.1932422233250004', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.26454565127179763', 'is_elite: False']\n", + "Id: 26_88 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_97', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_88', 'origin': '25_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.231247928873975', 'NSGA-II_crowding_distance: 0.5254724255817149', 'NSGA-II_rank: 4', 'change: 0.10289354421831859', 'is_elite: False']\n", + "Id: 26_82 Identity: {'ancestor_count': 23, 'ancestor_ids': ['23_80', '25_27'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_82', 'origin': '23_80~CUW~25_27#MGNP'} Metrics: ['ELUC: -3.2433454531178625', 'NSGA-II_crowding_distance: 0.6667321139988249', 'NSGA-II_rank: 5', 'change: 0.1698160187923045', 'is_elite: False']\n", + "Id: 26_20 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '25_24'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_20', 'origin': '25_87~CUW~25_24#MGNP'} Metrics: ['ELUC: -3.2528839243846983', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.32025439798477207', 'is_elite: False']\n", + "Id: 26_60 Identity: {'ancestor_count': 24, 'ancestor_ids': ['23_59', '25_60'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_60', 'origin': '23_59~CUW~25_60#MGNP'} Metrics: ['ELUC: -3.874029787260818', 'NSGA-II_crowding_distance: 0.27337314645188804', 'NSGA-II_rank: 3', 'change: 0.09528623981518161', 'is_elite: False']\n", + "Id: 26_78 Identity: {'ancestor_count': 2, 'ancestor_ids': ['25_91', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_78', 'origin': '25_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.150288385372614', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2682010091723355', 'is_elite: False']\n", + "Id: 25_23 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_23', 'origin': '24_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.159026014020856', 'NSGA-II_crowding_distance: 0.24118043945377307', 'NSGA-II_rank: 1', 'change: 0.06821442363038034', 'is_elite: True']\n", + "Id: 26_87 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_24', '25_91'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_87', 'origin': '25_24~CUW~25_91#MGNP'} Metrics: ['ELUC: -4.232497431615291', 'NSGA-II_crowding_distance: 0.2684282540982436', 'NSGA-II_rank: 2', 'change: 0.08322055677231592', 'is_elite: False']\n", + "Id: 26_75 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '25_91'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_75', 'origin': '23_80~CUW~25_91#MGNP'} Metrics: ['ELUC: -4.417624503285777', 'NSGA-II_crowding_distance: 0.8182460628669443', 'NSGA-II_rank: 5', 'change: 0.18152175933217712', 'is_elite: False']\n", + "Id: 26_31 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_27', '25_23'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_31', 'origin': '25_27~CUW~25_23#MGNP'} Metrics: ['ELUC: -4.425170325880148', 'NSGA-II_crowding_distance: 0.9215423431787048', 'NSGA-II_rank: 4', 'change: 0.14137187018500808', 'is_elite: False']\n", + "Id: 26_77 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '25_24'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_77', 'origin': '1_1~CUW~25_24#MGNP'} Metrics: ['ELUC: -4.442261740165848', 'NSGA-II_crowding_distance: 0.15724747556045512', 'NSGA-II_rank: 1', 'change: 0.07918741680306099', 'is_elite: False']\n", + "Id: 26_38 Identity: {'ancestor_count': 24, 'ancestor_ids': ['1_1', '25_42'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_38', 'origin': '1_1~CUW~25_42#MGNP'} Metrics: ['ELUC: -4.448850250678063', 'NSGA-II_crowding_distance: 0.3478063249649861', 'NSGA-II_rank: 3', 'change: 0.1392305443750694', 'is_elite: False']\n", + "Id: 26_46 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_27', '22_40'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_46', 'origin': '25_27~CUW~22_40#MGNP'} Metrics: ['ELUC: -4.789207097246928', 'NSGA-II_crowding_distance: 0.2675007282178697', 'NSGA-II_rank: 2', 'change: 0.12993076374697846', 'is_elite: False']\n", + "Id: 26_39 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_91', '25_97'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_39', 'origin': '25_91~CUW~25_97#MGNP'} Metrics: ['ELUC: -5.20295933260606', 'NSGA-II_crowding_distance: 0.23102345039442257', 'NSGA-II_rank: 3', 'change: 0.1637878935877329', 'is_elite: False']\n", + "Id: 26_48 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_91', '25_24'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_48', 'origin': '25_91~CUW~25_24#MGNP'} Metrics: ['ELUC: -5.543657369634319', 'NSGA-II_crowding_distance: 0.16257385743785746', 'NSGA-II_rank: 1', 'change: 0.09163594517538559', 'is_elite: False']\n", + "Id: 26_47 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_27', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_47', 'origin': '25_27~CUW~23_59#MGNP'} Metrics: ['ELUC: -5.950059518747733', 'NSGA-II_crowding_distance: 0.21136730264026943', 'NSGA-II_rank: 2', 'change: 0.13229442631001123', 'is_elite: False']\n", + "Id: 26_89 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_24', '25_27'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_89', 'origin': '25_24~CUW~25_27#MGNP'} Metrics: ['ELUC: -6.078096490311447', 'NSGA-II_crowding_distance: 0.2221091142237171', 'NSGA-II_rank: 1', 'change: 0.09993521298050458', 'is_elite: False']\n", + "Id: 26_74 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_74', 'origin': '25_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.281989219112598', 'NSGA-II_crowding_distance: 1.6868753011417157', 'NSGA-II_rank: 6', 'change: 0.22835663788594812', 'is_elite: False']\n", + "Id: 26_17 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_90', '25_91'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_17', 'origin': '25_90~CUW~25_91#MGNP'} Metrics: ['ELUC: -6.483852767879916', 'NSGA-II_crowding_distance: 1.0148928028348927', 'NSGA-II_rank: 4', 'change: 0.17735877232686856', 'is_elite: False']\n", + "Id: 26_81 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '25_24'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_81', 'origin': '23_80~CUW~25_24#MGNP'} Metrics: ['ELUC: -6.520761431746426', 'NSGA-II_crowding_distance: 0.18425790181296703', 'NSGA-II_rank: 3', 'change: 0.1658275560924567', 'is_elite: False']\n", + "Id: 26_96 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_24', '23_80'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_96', 'origin': '25_24~CUW~23_80#MGNP'} Metrics: ['ELUC: -7.178344279805768', 'NSGA-II_crowding_distance: 0.14556339725826337', 'NSGA-II_rank: 3', 'change: 0.17986823081465037', 'is_elite: False']\n", + "Id: 26_28 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_91', '25_42'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_28', 'origin': '25_91~CUW~25_42#MGNP'} Metrics: ['ELUC: -7.8422173262211015', 'NSGA-II_crowding_distance: 0.20052584729832731', 'NSGA-II_rank: 3', 'change: 0.18233171746498836', 'is_elite: False']\n", + "Id: 25_24 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '24_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_24', 'origin': '24_63~CUW~24_63#MGNP'} Metrics: ['ELUC: -8.062977090717059', 'NSGA-II_crowding_distance: 0.2739302581646149', 'NSGA-II_rank: 1', 'change: 0.11515472297873304', 'is_elite: True']\n", + "Id: 26_53 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '25_91'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_53', 'origin': '22_40~CUW~25_91#MGNP'} Metrics: ['ELUC: -8.4995072014584', 'NSGA-II_crowding_distance: 0.27088588131427593', 'NSGA-II_rank: 2', 'change: 0.1326445139772083', 'is_elite: False']\n", + "Id: 26_80 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '25_27'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_80', 'origin': '25_87~CUW~25_27#MGNP'} Metrics: ['ELUC: -8.627085666468597', 'NSGA-II_crowding_distance: 0.6532163877762658', 'NSGA-II_rank: 6', 'change: 0.2592623199295439', 'is_elite: False']\n", + "Id: 26_32 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_90', '25_24'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_32', 'origin': '25_90~CUW~25_24#MGNP'} Metrics: ['ELUC: -9.63199117378707', 'NSGA-II_crowding_distance: 0.4244444038102845', 'NSGA-II_rank: 3', 'change: 0.19253807099242726', 'is_elite: False']\n", + "Id: 25_97 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_20', '22_40'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_97', 'origin': '24_20~CUW~22_40#MGNP'} Metrics: ['ELUC: -9.632442613188546', 'NSGA-II_crowding_distance: 0.1545313686458902', 'NSGA-II_rank: 1', 'change: 0.12135154826882022', 'is_elite: False']\n", + "Id: 26_40 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_23', '25_90'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_40', 'origin': '25_23~CUW~25_90#MGNP'} Metrics: ['ELUC: -9.71264139888586', 'NSGA-II_crowding_distance: 0.8507309713002713', 'NSGA-II_rank: 4', 'change: 0.19950444501850434', 'is_elite: False']\n", + "Id: 26_29 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_90', '25_97'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_29', 'origin': '25_90~CUW~25_97#MGNP'} Metrics: ['ELUC: -9.807673478873408', 'NSGA-II_crowding_distance: 0.10808238408301406', 'NSGA-II_rank: 1', 'change: 0.13165540418786256', 'is_elite: False']\n", + "Id: 26_86 Identity: {'ancestor_count': 24, 'ancestor_ids': ['22_40', '25_97'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_86', 'origin': '22_40~CUW~25_97#MGNP'} Metrics: ['ELUC: -10.241009914647039', 'NSGA-II_crowding_distance: 0.5166472430948316', 'NSGA-II_rank: 2', 'change: 0.14288510795068388', 'is_elite: False']\n", + "Id: 26_51 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_91', '25_97'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_51', 'origin': '25_91~CUW~25_97#MGNP'} Metrics: ['ELUC: -10.82090187254217', 'NSGA-II_crowding_distance: 0.10197785749755665', 'NSGA-II_rank: 1', 'change: 0.13343240311931837', 'is_elite: False']\n", + "Id: 26_35 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_79', '25_27'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_35', 'origin': '25_79~CUW~25_27#MGNP'} Metrics: ['ELUC: -10.934068639334802', 'NSGA-II_crowding_distance: 0.8315654948682798', 'NSGA-II_rank: 5', 'change: 0.21557658253360312', 'is_elite: False']\n", + "Id: 26_23 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_27', '25_87'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_23', 'origin': '25_27~CUW~25_87#MGNP'} Metrics: ['ELUC: -11.04234613736293', 'NSGA-II_crowding_distance: 0.31312469885828415', 'NSGA-II_rank: 6', 'change: 0.2682263736248188', 'is_elite: False']\n", + "Id: 26_84 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_23', '25_87'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_84', 'origin': '25_23~CUW~25_87#MGNP'} Metrics: ['ELUC: -11.142511912868878', 'NSGA-II_crowding_distance: 0.32111671295294253', 'NSGA-II_rank: 5', 'change: 0.24079776181908047', 'is_elite: False']\n", + "Id: 26_44 Identity: {'ancestor_count': 23, 'ancestor_ids': ['22_40', '25_90'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_44', 'origin': '22_40~CUW~25_90#MGNP'} Metrics: ['ELUC: -11.393064624112087', 'NSGA-II_crowding_distance: 0.06415986624509579', 'NSGA-II_rank: 1', 'change: 0.13517874792335316', 'is_elite: False']\n", + "Id: 26_56 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_27', '25_87'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_56', 'origin': '25_27~CUW~25_87#MGNP'} Metrics: ['ELUC: -11.429840157709089', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2716933022043966', 'is_elite: False']\n", + "Id: 26_93 Identity: {'ancestor_count': 21, 'ancestor_ids': ['23_80', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_93', 'origin': '23_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.501784683519384', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2622180668598204', 'is_elite: False']\n", + "Id: 26_25 Identity: {'ancestor_count': 24, 'ancestor_ids': ['22_40', '25_97'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_25', 'origin': '22_40~CUW~25_97#MGNP'} Metrics: ['ELUC: -11.695719552715424', 'NSGA-II_crowding_distance: 0.04243190976077793', 'NSGA-II_rank: 1', 'change: 0.13773035174077927', 'is_elite: False']\n", + "Id: 22_40 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_63', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_40', 'origin': '21_63~CUW~21_63#MGNP'} Metrics: ['ELUC: -11.78103137121908', 'NSGA-II_crowding_distance: 0.25381339185428414', 'NSGA-II_rank: 1', 'change: 0.14125556891696645', 'is_elite: True']\n", + "Id: 26_97 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_90', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_97', 'origin': '25_90~CUW~23_59#MGNP'} Metrics: ['ELUC: -12.299446383773669', 'NSGA-II_crowding_distance: 0.4596347715833926', 'NSGA-II_rank: 4', 'change: 0.20672045096685504', 'is_elite: False']\n", + "Id: 26_100 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_27', '25_90'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_100', 'origin': '25_27~CUW~25_90#MGNP'} Metrics: ['ELUC: -12.432106234143362', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2212845053224902', 'is_elite: False']\n", + "Id: 26_45 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_80'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_45', 'origin': '22_40~CUW~23_80#MGNP'} Metrics: ['ELUC: -13.557119758977821', 'NSGA-II_crowding_distance: 0.28557117952806127', 'NSGA-II_rank: 1', 'change: 0.1818740763555117', 'is_elite: True']\n", + "Id: 26_92 Identity: {'ancestor_count': 24, 'ancestor_ids': ['24_98', '25_42'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_92', 'origin': '24_98~CUW~25_42#MGNP'} Metrics: ['ELUC: -13.695164000088054', 'NSGA-II_crowding_distance: 0.5570732296363838', 'NSGA-II_rank: 3', 'change: 0.19866709204665112', 'is_elite: False']\n", + "Id: 26_61 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_42', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_61', 'origin': '25_42~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.695358088542475', 'NSGA-II_crowding_distance: 0.5009605016853624', 'NSGA-II_rank: 2', 'change: 0.1986358612926689', 'is_elite: False']\n", + "Id: 26_62 Identity: {'ancestor_count': 24, 'ancestor_ids': ['23_80', '25_97'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_62', 'origin': '23_80~CUW~25_97#MGNP'} Metrics: ['ELUC: -13.774420637846633', 'NSGA-II_crowding_distance: 0.18049308163482763', 'NSGA-II_rank: 1', 'change: 0.19263521460215638', 'is_elite: False']\n", + "Id: 26_15 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '23_80'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_15', 'origin': '25_87~CUW~23_80#MGNP'} Metrics: ['ELUC: -13.850507590937378', 'NSGA-II_crowding_distance: 0.5068836348585251', 'NSGA-II_rank: 3', 'change: 0.26903221628619295', 'is_elite: False']\n", + "Id: 26_98 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_90', '25_63'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_98', 'origin': '25_90~CUW~25_63#MGNP'} Metrics: ['ELUC: -14.28628359358847', 'NSGA-II_crowding_distance: 0.32496779290029976', 'NSGA-II_rank: 2', 'change: 0.22208776835988023', 'is_elite: False']\n", + "Id: 26_37 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_63', '23_80'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_37', 'origin': '25_63~CUW~23_80#MGNP'} Metrics: ['ELUC: -14.540806070025095', 'NSGA-II_crowding_distance: 0.20176140221352482', 'NSGA-II_rank: 1', 'change: 0.2190357296748544', 'is_elite: False']\n", + "Id: 26_85 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_42', '25_87'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_85', 'origin': '25_42~CUW~25_87#MGNP'} Metrics: ['ELUC: -14.873642114477311', 'NSGA-II_crowding_distance: 0.3540812494102219', 'NSGA-II_rank: 2', 'change: 0.27217139504601273', 'is_elite: False']\n", + "Id: 26_90 Identity: {'ancestor_count': 23, 'ancestor_ids': ['22_40', '25_90'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_90', 'origin': '22_40~CUW~25_90#MGNP'} Metrics: ['ELUC: -15.269085257140635', 'NSGA-II_crowding_distance: 0.17031365524531983', 'NSGA-II_rank: 1', 'change: 0.22747140144629036', 'is_elite: False']\n", + "Id: 26_33 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_90', '25_90'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_33', 'origin': '25_90~CUW~25_90#MGNP'} Metrics: ['ELUC: -15.80124299417619', 'NSGA-II_crowding_distance: 0.10923857942838172', 'NSGA-II_rank: 1', 'change: 0.24846352582445957', 'is_elite: False']\n", + "Id: 26_12 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_63', '22_40'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_12', 'origin': '25_63~CUW~22_40#MGNP'} Metrics: ['ELUC: -15.878120556258393', 'NSGA-II_crowding_distance: 0.011681024826923667', 'NSGA-II_rank: 1', 'change: 0.24973024238634003', 'is_elite: False']\n", + "Id: 26_70 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_90', '25_42'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_70', 'origin': '25_90~CUW~25_42#MGNP'} Metrics: ['ELUC: -15.912733825725958', 'NSGA-II_crowding_distance: 0.010327806648855895', 'NSGA-II_rank: 1', 'change: 0.2500568495445606', 'is_elite: False']\n", + "Id: 25_90 Identity: {'ancestor_count': 22, 'ancestor_ids': ['24_25', '23_44'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_90', 'origin': '24_25~CUW~23_44#MGNP'} Metrics: ['ELUC: -15.931057853488165', 'NSGA-II_crowding_distance: 0.012934438230297642', 'NSGA-II_rank: 1', 'change: 0.25191346748114796', 'is_elite: False']\n", + "Id: 26_50 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_90', '25_90'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_50', 'origin': '25_90~CUW~25_90#MGNP'} Metrics: ['ELUC: -15.966076404418539', 'NSGA-II_crowding_distance: 0.16792970967304233', 'NSGA-II_rank: 1', 'change: 0.2530109576615324', 'is_elite: False']\n", + "Id: 25_79 Identity: {'ancestor_count': 21, 'ancestor_ids': ['24_78', '24_65'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_79', 'origin': '24_78~CUW~24_65#MGNP'} Metrics: ['ELUC: -16.342405763783766', 'NSGA-II_crowding_distance: 0.3446798096843793', 'NSGA-II_rank: 3', 'change: 0.2872053013626268', 'is_elite: False']\n", + "Id: 26_79 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '25_90'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_79', 'origin': '25_87~CUW~25_90#MGNP'} Metrics: ['ELUC: -16.6211482181936', 'NSGA-II_crowding_distance: 0.2537159709738719', 'NSGA-II_rank: 2', 'change: 0.2861043320698609', 'is_elite: False']\n", + "Id: 26_95 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_40', '25_79'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_95', 'origin': '22_40~CUW~25_79#MGNP'} Metrics: ['ELUC: -16.983833167237655', 'NSGA-II_crowding_distance: 0.2583955391312587', 'NSGA-II_rank: 1', 'change: 0.2841540289228528', 'is_elite: True']\n", + "Id: 26_83 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '25_24'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_83', 'origin': '2_49~CUW~25_24#MGNP'} Metrics: ['ELUC: -17.158938232281727', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3052613924290803', 'is_elite: False']\n", + "Id: 26_59 Identity: {'ancestor_count': 24, 'ancestor_ids': ['2_49', '25_87'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_59', 'origin': '2_49~CUW~25_87#MGNP'} Metrics: ['ELUC: -17.544154180851592', 'NSGA-II_crowding_distance: 0.11281038376691288', 'NSGA-II_rank: 2', 'change: 0.3027560000972615', 'is_elite: False']\n", + "Id: 26_58 Identity: {'ancestor_count': 24, 'ancestor_ids': ['22_40', '25_87'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_58', 'origin': '22_40~CUW~25_87#MGNP'} Metrics: ['ELUC: -17.578956025035435', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30322170346266747', 'is_elite: False']\n", + "Id: 26_52 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_90', '25_87'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_52', 'origin': '25_90~CUW~25_87#MGNP'} Metrics: ['ELUC: -17.58292082782616', 'NSGA-II_crowding_distance: 0.09774041836124622', 'NSGA-II_rank: 1', 'change: 0.3026720799069606', 'is_elite: False']\n", + "Id: 26_67 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_67', 'origin': '25_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59190569641081', 'NSGA-II_crowding_distance: 0.00198935999148819', 'NSGA-II_rank: 1', 'change: 0.3029984133468552', 'is_elite: False']\n", + "Id: 26_68 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_68', 'origin': '25_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59737144331564', 'NSGA-II_crowding_distance: 0.00038563688301716716', 'NSGA-II_rank: 1', 'change: 0.3030204291962141', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 25_87 Identity: {'ancestor_count': 23, 'ancestor_ids': ['24_98', '24_78'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_87', 'origin': '24_98~CUW~24_78#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 26_24 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_24', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 26_27 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_27', 'origin': '25_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 26_34 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_79', '25_87'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_34', 'origin': '25_79~CUW~25_87#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 26_49 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '25_24'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_49', 'origin': '25_87~CUW~25_24#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 26_76 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_76', 'origin': '25_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 26.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 27...:\n", + "PopulationResponse:\n", + " Generation: 27\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/27/20240219-225453\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 27 and asking ESP for generation 28...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 27 data persisted.\n", + "Evaluated candidates:\n", + "Id: 27_87 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_87', 'origin': '1_1~CUW~26_76#MGNP'} Metrics: ['ELUC: 23.273575835314823', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2955057384924476', 'is_elite: False']\n", + "Id: 27_86 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_76', '26_62'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_86', 'origin': '26_76~CUW~26_62#MGNP'} Metrics: ['ELUC: 21.104044531554038', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.280251112668576', 'is_elite: False']\n", + "Id: 27_26 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_26', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 16.198723252515677', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2861016708577955', 'is_elite: False']\n", + "Id: 27_99 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_95', '25_24'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_99', 'origin': '26_95~CUW~25_24#MGNP'} Metrics: ['ELUC: 11.623423430459752', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.22755104643203466', 'is_elite: False']\n", + "Id: 27_28 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_95', '26_69'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_28', 'origin': '26_95~CUW~26_69#MGNP'} Metrics: ['ELUC: 8.929627300794614', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.22603944594627454', 'is_elite: False']\n", + "Id: 27_17 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_89', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_17', 'origin': '26_89~CUW~26_95#MGNP'} Metrics: ['ELUC: 5.849617920654493', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.17956024380490584', 'is_elite: False']\n", + "Id: 27_24 Identity: {'ancestor_count': 25, 'ancestor_ids': ['25_24', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_24', 'origin': '25_24~CUW~26_76#MGNP'} Metrics: ['ELUC: 4.142693367611824', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27426206757377325', 'is_elite: False']\n", + "Id: 27_78 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_69', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_78', 'origin': '26_69~CUW~26_76#MGNP'} Metrics: ['ELUC: 3.522813652206422', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.17222083883183398', 'is_elite: False']\n", + "Id: 27_60 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_95', '26_62'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_60', 'origin': '26_95~CUW~26_62#MGNP'} Metrics: ['ELUC: 2.2374605396262246', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1318642197069625', 'is_elite: False']\n", + "Id: 27_47 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '22_40'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_47', 'origin': '1_1~CUW~22_40#MGNP'} Metrics: ['ELUC: 0.8455825963784962', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11102549116087569', 'is_elite: False']\n", + "Id: 27_72 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_89', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_72', 'origin': '26_89~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.7611618863382773', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07026823066186051', 'is_elite: False']\n", + "Id: 27_98 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '25_91'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_98', 'origin': '1_1~CUW~25_91#MGNP'} Metrics: ['ELUC: 0.7217550688270822', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.046306543001048646', 'is_elite: False']\n", + "Id: 27_92 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_92', 'origin': '26_69~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.39757203408814434', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.02722734529038689', 'is_elite: False']\n", + "Id: 27_53 Identity: {'ancestor_count': 2, 'ancestor_ids': ['25_91', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_53', 'origin': '25_91~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.35665014214819596', 'NSGA-II_crowding_distance: 0.22227845897090442', 'NSGA-II_rank: 2', 'change: 0.031106097113004966', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 27_20 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_20', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6197336238352086', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06859427587079388', 'is_elite: False']\n", + "Id: 27_51 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_76', '26_45'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_51', 'origin': '26_76~CUW~26_45#MGNP'} Metrics: ['ELUC: -0.6468605566068099', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.23657619834429358', 'is_elite: False']\n", + "Id: 25_91 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_91', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6767632511629323', 'NSGA-II_crowding_distance: 0.2604517177260295', 'NSGA-II_rank: 1', 'change: 0.027591555327354134', 'is_elite: True']\n", + "Id: 27_70 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '26_48'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_70', 'origin': '26_45~CUW~26_48#MGNP'} Metrics: ['ELUC: -0.7029953164279429', 'NSGA-II_crowding_distance: 0.675479737350662', 'NSGA-II_rank: 5', 'change: 0.1290244781377089', 'is_elite: False']\n", + "Id: 27_96 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_96', 'origin': '25_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.0001024908412515', 'NSGA-II_crowding_distance: 0.2976764438147077', 'NSGA-II_rank: 4', 'change: 0.0692171055128367', 'is_elite: False']\n", + "Id: 27_43 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_89', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_43', 'origin': '26_89~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.0085586483364481', 'NSGA-II_crowding_distance: 0.5585557538829158', 'NSGA-II_rank: 4', 'change: 0.13259870210324537', 'is_elite: False']\n", + "Id: 27_85 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '26_69'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_85', 'origin': '1_1~CUW~26_69#MGNP'} Metrics: ['ELUC: -1.0955356298494767', 'NSGA-II_crowding_distance: 0.19615366841351312', 'NSGA-II_rank: 3', 'change: 0.05417636611076712', 'is_elite: False']\n", + "Id: 27_65 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '26_69'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_65', 'origin': '1_1~CUW~26_69#MGNP'} Metrics: ['ELUC: -1.2090212251856167', 'NSGA-II_crowding_distance: 0.12562640664266686', 'NSGA-II_rank: 3', 'change: 0.0690806376402626', 'is_elite: False']\n", + "Id: 27_79 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_40', '26_48'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_79', 'origin': '22_40~CUW~26_48#MGNP'} Metrics: ['ELUC: -1.6184123963313122', 'NSGA-II_crowding_distance: 0.2145364943672501', 'NSGA-II_rank: 3', 'change: 0.07888456208764436', 'is_elite: False']\n", + "Id: 27_90 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_90', 'origin': '26_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.808837535519142', 'NSGA-II_crowding_distance: 0.30948529144205494', 'NSGA-II_rank: 2', 'change: 0.053567525804032505', 'is_elite: False']\n", + "Id: 27_30 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_69', '26_89'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_30', 'origin': '26_69~CUW~26_89#MGNP'} Metrics: ['ELUC: -2.239776247621933', 'NSGA-II_crowding_distance: 0.40576011279253094', 'NSGA-II_rank: 2', 'change: 0.07500134478918194', 'is_elite: False']\n", + "Id: 27_76 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '26_29'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_76', 'origin': '1_1~CUW~26_29#MGNP'} Metrics: ['ELUC: -2.24220614518374', 'NSGA-II_crowding_distance: 0.25208101482162604', 'NSGA-II_rank: 3', 'change: 0.10928642842671117', 'is_elite: False']\n", + "Id: 27_68 Identity: {'ancestor_count': 25, 'ancestor_ids': ['25_91', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_68', 'origin': '25_91~CUW~26_76#MGNP'} Metrics: ['ELUC: -2.2939665468219013', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.238796538628087', 'is_elite: False']\n", + "Id: 26_69 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_69', 'origin': '23_59~CUW~23_59#MGNP'} Metrics: ['ELUC: -2.3593292124774066', 'NSGA-II_crowding_distance: 0.2173054158529014', 'NSGA-II_rank: 1', 'change: 0.04257255541510991', 'is_elite: True']\n", + "Id: 27_54 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_76', '26_48'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_54', 'origin': '26_76~CUW~26_48#MGNP'} Metrics: ['ELUC: -2.57736211621491', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23558698996926383', 'is_elite: False']\n", + "Id: 27_13 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '25_91'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_13', 'origin': '26_69~CUW~25_91#MGNP'} Metrics: ['ELUC: -2.9155823373431122', 'NSGA-II_crowding_distance: 0.18829582384944404', 'NSGA-II_rank: 1', 'change: 0.054437198805852266', 'is_elite: False']\n", + "Id: 27_91 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_50', '26_48'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_91', 'origin': '26_50~CUW~26_48#MGNP'} Metrics: ['ELUC: -3.48268686531651', 'NSGA-II_crowding_distance: 0.43027873042582737', 'NSGA-II_rank: 5', 'change: 0.16992631436592462', 'is_elite: False']\n", + "Id: 27_37 Identity: {'ancestor_count': 25, 'ancestor_ids': ['25_91', '26_37'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_37', 'origin': '25_91~CUW~26_37#MGNP'} Metrics: ['ELUC: -3.7930870695350136', 'NSGA-II_crowding_distance: 1.427178361025677', 'NSGA-II_rank: 6', 'change: 0.1862922507994343', 'is_elite: False']\n", + "Id: 27_22 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '25_91'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_22', 'origin': '22_40~CUW~25_91#MGNP'} Metrics: ['ELUC: -3.936467468232695', 'NSGA-II_crowding_distance: 0.2192919315945991', 'NSGA-II_rank: 3', 'change: 0.11046709373185477', 'is_elite: False']\n", + "Id: 25_23 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_23', 'origin': '24_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.159026014020856', 'NSGA-II_crowding_distance: 0.22086978582386152', 'NSGA-II_rank: 1', 'change: 0.06821442363038034', 'is_elite: True']\n", + "Id: 27_56 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_77', '25_24'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_56', 'origin': '26_77~CUW~25_24#MGNP'} Metrics: ['ELUC: -4.769255329050038', 'NSGA-II_crowding_distance: 0.1281567576096938', 'NSGA-II_rank: 1', 'change: 0.08888241876231519', 'is_elite: False']\n", + "Id: 27_49 Identity: {'ancestor_count': 25, 'ancestor_ids': ['25_24', '26_37'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_49', 'origin': '25_24~CUW~26_37#MGNP'} Metrics: ['ELUC: -4.788221206842954', 'NSGA-II_crowding_distance: 0.15022379715256556', 'NSGA-II_rank: 5', 'change: 0.17086591424915915', 'is_elite: False']\n", + "Id: 27_18 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '25_24'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_18', 'origin': '25_23~CUW~25_24#MGNP'} Metrics: ['ELUC: -4.953486052090962', 'NSGA-II_crowding_distance: 0.198203671700016', 'NSGA-II_rank: 1', 'change: 0.09297131237430452', 'is_elite: True']\n", + "Id: 27_80 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_95', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_80', 'origin': '26_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.160706836147839', 'NSGA-II_crowding_distance: 0.6564421051548234', 'NSGA-II_rank: 6', 'change: 0.25191431545463605', 'is_elite: False']\n", + "Id: 27_97 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_37', '1_1'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_97', 'origin': '26_37~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.223082461932263', 'NSGA-II_crowding_distance: 0.4513612611542056', 'NSGA-II_rank: 4', 'change: 0.13991100363031556', 'is_elite: False']\n", + "Id: 27_34 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_37', '25_23'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_34', 'origin': '26_37~CUW~25_23#MGNP'} Metrics: ['ELUC: -5.227308970610697', 'NSGA-II_crowding_distance: 0.2149480508651332', 'NSGA-II_rank: 3', 'change: 0.12302329293556379', 'is_elite: False']\n", + "Id: 27_45 Identity: {'ancestor_count': 24, 'ancestor_ids': ['1_1', '26_90'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_45', 'origin': '1_1~CUW~26_90#MGNP'} Metrics: ['ELUC: -5.330427142536014', 'NSGA-II_crowding_distance: 0.1815808978444608', 'NSGA-II_rank: 3', 'change: 0.14566108950343568', 'is_elite: False']\n", + "Id: 27_14 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_50', '26_69'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_14', 'origin': '26_50~CUW~26_69#MGNP'} Metrics: ['ELUC: -5.611206066174296', 'NSGA-II_crowding_distance: 0.3813350790717448', 'NSGA-II_rank: 5', 'change: 0.17353749360388226', 'is_elite: False']\n", + "Id: 27_88 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_24', '26_48'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_88', 'origin': '25_24~CUW~26_48#MGNP'} Metrics: ['ELUC: -5.8030483354963645', 'NSGA-II_crowding_distance: 0.6287390670427473', 'NSGA-II_rank: 2', 'change: 0.1021590073736135', 'is_elite: False']\n", + "Id: 27_62 Identity: {'ancestor_count': 2, 'ancestor_ids': ['25_91', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_62', 'origin': '25_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.015732519446699', 'NSGA-II_crowding_distance: 0.1580095312642794', 'NSGA-II_rank: 6', 'change: 0.26260240565964693', 'is_elite: False']\n", + "Id: 27_83 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_95', '26_62'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_83', 'origin': '26_95~CUW~26_62#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.4193800810908742', 'NSGA-II_rank: 6', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 27_63 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_37', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_63', 'origin': '26_37~CUW~26_95#MGNP'} Metrics: ['ELUC: -6.573143569842469', 'NSGA-II_crowding_distance: 0.35154186416198774', 'NSGA-II_rank: 4', 'change: 0.1592914573841655', 'is_elite: False']\n", + "Id: 27_74 Identity: {'ancestor_count': 25, 'ancestor_ids': ['25_91', '26_37'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_74', 'origin': '25_91~CUW~26_37#MGNP'} Metrics: ['ELUC: -6.806026295820278', 'NSGA-II_crowding_distance: 0.20191587101868574', 'NSGA-II_rank: 3', 'change: 0.1470643453921874', 'is_elite: False']\n", + "Id: 27_27 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_91', '26_50'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_27', 'origin': '25_91~CUW~26_50#MGNP'} Metrics: ['ELUC: -6.816506966029561', 'NSGA-II_crowding_distance: 0.3541311385355831', 'NSGA-II_rank: 4', 'change: 0.19945695297604496', 'is_elite: False']\n", + "Id: 27_95 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_23', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_95', 'origin': '25_23~CUW~26_95#MGNP'} Metrics: ['ELUC: -7.335341894573604', 'NSGA-II_crowding_distance: 0.6714223389535857', 'NSGA-II_rank: 5', 'change: 0.22475751265132082', 'is_elite: False']\n", + "Id: 27_59 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_37', '26_89'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_59', 'origin': '26_37~CUW~26_89#MGNP'} Metrics: ['ELUC: -7.341491154117885', 'NSGA-II_crowding_distance: 0.20472365190204994', 'NSGA-II_rank: 3', 'change: 0.1687699006485848', 'is_elite: False']\n", + "Id: 27_19 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_24', '26_77'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_19', 'origin': '25_24~CUW~26_77#MGNP'} Metrics: ['ELUC: -7.5593755506690865', 'NSGA-II_crowding_distance: 0.2511998321744784', 'NSGA-II_rank: 1', 'change: 0.10067277731826463', 'is_elite: True']\n", + "Id: 27_32 Identity: {'ancestor_count': 2, 'ancestor_ids': ['25_91', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_32', 'origin': '25_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.9954537494271065', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29942650877005206', 'is_elite: False']\n", + "Id: 25_24 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '24_63'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_24', 'origin': '24_63~CUW~24_63#MGNP'} Metrics: ['ELUC: -8.062977090717059', 'NSGA-II_crowding_distance: 0.09547643714982727', 'NSGA-II_rank: 1', 'change: 0.11515472297873304', 'is_elite: False']\n", + "Id: 27_52 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_52', 'origin': '26_45~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.063357012966831', 'NSGA-II_crowding_distance: 0.34634090692666486', 'NSGA-II_rank: 4', 'change: 0.2209015606406891', 'is_elite: False']\n", + "Id: 27_46 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '25_91'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_46', 'origin': '26_45~CUW~25_91#MGNP'} Metrics: ['ELUC: -8.075761946419172', 'NSGA-II_crowding_distance: 0.27705932028193003', 'NSGA-II_rank: 3', 'change: 0.181405748697283', 'is_elite: False']\n", + "Id: 27_100 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_89', '26_69'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_100', 'origin': '26_89~CUW~26_69#MGNP'} Metrics: ['ELUC: -8.277430050740575', 'NSGA-II_crowding_distance: 0.1431163381843938', 'NSGA-II_rank: 1', 'change: 0.11697521226396985', 'is_elite: False']\n", + "Id: 27_12 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_37', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_12', 'origin': '26_37~CUW~26_76#MGNP'} Metrics: ['ELUC: -8.894842792879846', 'NSGA-II_crowding_distance: 0.3385049973408966', 'NSGA-II_rank: 4', 'change: 0.25093100846752714', 'is_elite: False']\n", + "Id: 27_23 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '25_23'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_23', 'origin': '22_40~CUW~25_23#MGNP'} Metrics: ['ELUC: -9.177032043009326', 'NSGA-II_crowding_distance: 0.4998710856720961', 'NSGA-II_rank: 2', 'change: 0.13893795904509268', 'is_elite: False']\n", + "Id: 27_77 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '26_37'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_77', 'origin': '2_49~CUW~26_37#MGNP'} Metrics: ['ELUC: -9.426497516645998', 'NSGA-II_crowding_distance: 0.8562307961264339', 'NSGA-II_rank: 5', 'change: 0.2789089263135161', 'is_elite: False']\n", + "Id: 27_55 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_24', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_55', 'origin': '25_24~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.749560959203697', 'NSGA-II_crowding_distance: 0.7178555913592489', 'NSGA-II_rank: 4', 'change: 0.27609151716832425', 'is_elite: False']\n", + "Id: 27_44 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '22_40'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_44', 'origin': '26_45~CUW~22_40#MGNP'} Metrics: ['ELUC: -9.75501714433374', 'NSGA-II_crowding_distance: 0.1957417025265836', 'NSGA-II_rank: 1', 'change: 0.12914300771339257', 'is_elite: False']\n", + "Id: 27_69 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_33', '26_69'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_69', 'origin': '26_33~CUW~26_69#MGNP'} Metrics: ['ELUC: -10.023568818210675', 'NSGA-II_crowding_distance: 0.9045618318838649', 'NSGA-II_rank: 3', 'change: 0.20157662721451775', 'is_elite: False']\n", + "Id: 27_11 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '25_24'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_11', 'origin': '22_40~CUW~25_24#MGNP'} Metrics: ['ELUC: -10.604936445535264', 'NSGA-II_crowding_distance: 0.39396059424781377', 'NSGA-II_rank: 2', 'change: 0.16382323420805844', 'is_elite: False']\n", + "Id: 27_48 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_40', '26_45'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_48', 'origin': '22_40~CUW~26_45#MGNP'} Metrics: ['ELUC: -10.737707240178278', 'NSGA-II_crowding_distance: 0.15582479771983102', 'NSGA-II_rank: 1', 'change: 0.13362851198822615', 'is_elite: False']\n", + "Id: 22_40 Identity: {'ancestor_count': 20, 'ancestor_ids': ['21_63', '21_63'], 'birth_generation': 22, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '22_40', 'origin': '21_63~CUW~21_63#MGNP'} Metrics: ['ELUC: -11.78103137121908', 'NSGA-II_crowding_distance: 0.15656561183516018', 'NSGA-II_rank: 1', 'change: 0.14125556891696645', 'is_elite: False']\n", + "Id: 27_39 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_90', '25_97'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_39', 'origin': '26_90~CUW~25_97#MGNP'} Metrics: ['ELUC: -12.42857652205627', 'NSGA-II_crowding_distance: 0.1395406011019682', 'NSGA-II_rank: 1', 'change: 0.15164962861197517', 'is_elite: False']\n", + "Id: 27_42 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_90', '25_97'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_42', 'origin': '26_90~CUW~25_97#MGNP'} Metrics: ['ELUC: -12.560362047336332', 'NSGA-II_crowding_distance: 0.4041190664590478', 'NSGA-II_rank: 2', 'change: 0.1936273904550863', 'is_elite: False']\n", + "Id: 27_94 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_97', '26_45'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_94', 'origin': '25_97~CUW~26_45#MGNP'} Metrics: ['ELUC: -12.59567720722389', 'NSGA-II_crowding_distance: 0.16548211168725951', 'NSGA-II_rank: 1', 'change: 0.16906658365132726', 'is_elite: False']\n", + "Id: 26_45 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_80'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_45', 'origin': '22_40~CUW~23_80#MGNP'} Metrics: ['ELUC: -13.557119758977821', 'NSGA-II_crowding_distance: 0.20620099394252867', 'NSGA-II_rank: 1', 'change: 0.1818740763555117', 'is_elite: True']\n", + "Id: 27_36 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_95', '26_45'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_36', 'origin': '26_95~CUW~26_45#MGNP'} Metrics: ['ELUC: -14.271375889292715', 'NSGA-II_crowding_distance: 0.47095359767641487', 'NSGA-II_rank: 2', 'change: 0.21694917708150885', 'is_elite: False']\n", + "Id: 27_16 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_40', '26_48'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_16', 'origin': '22_40~CUW~26_48#MGNP'} Metrics: ['ELUC: -14.275480644948987', 'NSGA-II_crowding_distance: 0.2514309325631591', 'NSGA-II_rank: 1', 'change: 0.20208558292570444', 'is_elite: True']\n", + "Id: 27_71 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_95', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_71', 'origin': '26_95~CUW~26_76#MGNP'} Metrics: ['ELUC: -14.94287345385946', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.31619162291303715', 'is_elite: False']\n", + "Id: 27_25 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_37', '26_33'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_25', 'origin': '26_37~CUW~26_33#MGNP'} Metrics: ['ELUC: -15.211600651448999', 'NSGA-II_crowding_distance: 0.17740254759222424', 'NSGA-II_rank: 1', 'change: 0.22881841273328682', 'is_elite: False']\n", + "Id: 27_73 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_90', '26_62'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_73', 'origin': '26_90~CUW~26_62#MGNP'} Metrics: ['ELUC: -15.437391393200768', 'NSGA-II_crowding_distance: 0.04742670054153465', 'NSGA-II_rank: 1', 'change: 0.23530056613882372', 'is_elite: False']\n", + "Id: 27_82 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_50', '26_77'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_82', 'origin': '26_50~CUW~26_77#MGNP'} Metrics: ['ELUC: -15.484985624513408', 'NSGA-II_crowding_distance: 0.09139668625459847', 'NSGA-II_rank: 1', 'change: 0.23833005599975288', 'is_elite: False']\n", + "Id: 27_66 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_37', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_66', 'origin': '26_37~CUW~26_95#MGNP'} Metrics: ['ELUC: -15.537553512412991', 'NSGA-II_crowding_distance: 0.1345029436488015', 'NSGA-II_rank: 1', 'change: 0.2608715184549417', 'is_elite: False']\n", + "Id: 27_75 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_76', '26_45'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_75', 'origin': '26_76~CUW~26_45#MGNP'} Metrics: ['ELUC: -15.829354719703097', 'NSGA-II_crowding_distance: 0.33194889489970025', 'NSGA-II_rank: 2', 'change: 0.27077941979693276', 'is_elite: False']\n", + "Id: 27_35 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_35', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.949795282042574', 'NSGA-II_crowding_distance: 0.10190969811703143', 'NSGA-II_rank: 2', 'change: 0.2808288997438954', 'is_elite: False']\n", + "Id: 27_84 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_45', '26_50'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_84', 'origin': '26_45~CUW~26_50#MGNP'} Metrics: ['ELUC: -16.33028108950212', 'NSGA-II_crowding_distance: 0.10431752442172793', 'NSGA-II_rank: 1', 'change: 0.2641178123683581', 'is_elite: False']\n", + "Id: 27_50 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_95', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_50', 'origin': '26_95~CUW~26_95#MGNP'} Metrics: ['ELUC: -16.52731508685774', 'NSGA-II_crowding_distance: 0.08991223482317852', 'NSGA-II_rank: 1', 'change: 0.2752009840299108', 'is_elite: False']\n", + "Id: 27_40 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_48', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_40', 'origin': '26_48~CUW~26_76#MGNP'} Metrics: ['ELUC: -16.591413814731172', 'NSGA-II_crowding_distance: 0.7967952625126369', 'NSGA-II_rank: 3', 'change: 0.29193320768382724', 'is_elite: False']\n", + "Id: 27_58 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_62', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_58', 'origin': '26_62~CUW~26_95#MGNP'} Metrics: ['ELUC: -16.856687634456065', 'NSGA-II_crowding_distance: 0.13602238120572038', 'NSGA-II_rank: 2', 'change: 0.2826167844433906', 'is_elite: False']\n", + "Id: 27_33 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_91', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_33', 'origin': '25_91~CUW~26_95#MGNP'} Metrics: ['ELUC: -16.86007531848705', 'NSGA-II_crowding_distance: 0.05047058216437693', 'NSGA-II_rank: 1', 'change: 0.28195484815762994', 'is_elite: False']\n", + "Id: 27_57 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_95', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_57', 'origin': '26_95~CUW~26_95#MGNP'} Metrics: ['ELUC: -16.93976734361479', 'NSGA-II_crowding_distance: 0.014409218214393772', 'NSGA-II_rank: 1', 'change: 0.28326083907749344', 'is_elite: False']\n", + "Id: 26_95 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_40', '25_79'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_95', 'origin': '22_40~CUW~25_79#MGNP'} Metrics: ['ELUC: -16.983833167237655', 'NSGA-II_crowding_distance: 0.03938112091928325', 'NSGA-II_rank: 1', 'change: 0.2841540289228528', 'is_elite: False']\n", + "Id: 27_93 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_95', '26_89'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_93', 'origin': '26_95~CUW~26_89#MGNP'} Metrics: ['ELUC: -16.99733661853694', 'NSGA-II_crowding_distance: 0.05925037423252355', 'NSGA-II_rank: 1', 'change: 0.29403431959039933', 'is_elite: False']\n", + "Id: 27_29 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_29', 'origin': '2_49~CUW~26_76#MGNP'} Metrics: ['ELUC: -17.12997897661792', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.3020797763307517', 'is_elite: False']\n", + "Id: 27_89 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_89', 'origin': '2_49~CUW~26_76#MGNP'} Metrics: ['ELUC: -17.307250714199842', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30202029402747005', 'is_elite: False']\n", + "Id: 27_21 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_37', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_21', 'origin': '26_37~CUW~26_76#MGNP'} Metrics: ['ELUC: -17.334092266599537', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2964300508246803', 'is_elite: False']\n", + "Id: 27_15 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_90', '26_95'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_15', 'origin': '26_90~CUW~26_95#MGNP'} Metrics: ['ELUC: -17.350037044317958', 'NSGA-II_crowding_distance: 0.045872403414648294', 'NSGA-II_rank: 1', 'change: 0.29561842751577494', 'is_elite: False']\n", + "Id: 27_38 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_76', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_38', 'origin': '26_76~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.35837877439332', 'NSGA-II_crowding_distance: 0.024838676659013213', 'NSGA-II_rank: 1', 'change: 0.30159462582758456', 'is_elite: False']\n", + "Id: 27_64 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_64', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.38266210956475', 'NSGA-II_crowding_distance: 0.017452257472369337', 'NSGA-II_rank: 1', 'change: 0.3024760776741019', 'is_elite: False']\n", + "Id: 27_61 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_61', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.582590586653673', 'NSGA-II_crowding_distance: 0.014037004352726626', 'NSGA-II_rank: 1', 'change: 0.30299704697390756', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 26_76 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_87', '1_1'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_76', 'origin': '25_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 27_31 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_31', 'origin': '2_49~CUW~26_76#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 27_41 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '2_49'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_41', 'origin': '26_45~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 27_67 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_95', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_67', 'origin': '26_95~CUW~26_76#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 27_81 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_76', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_81', 'origin': '26_76~CUW~26_76#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 27.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 28...:\n", + "PopulationResponse:\n", + " Generation: 28\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/28/20240219-230208\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 28 and asking ESP for generation 29...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 28 data persisted.\n", + "Evaluated candidates:\n", + "Id: 28_20 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '27_19'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_20', 'origin': '27_81~CUW~27_19#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 28_78 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '2_49'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_78', 'origin': '27_81~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 28_89 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_89', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 23.66451927786999', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.30137460940657446', 'is_elite: False']\n", + "Id: 28_19 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_19', 'origin': '27_81~CUW~1_1#MGNP'} Metrics: ['ELUC: 20.415685783882225', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2656363314277401', 'is_elite: False']\n", + "Id: 28_43 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '25_91'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_43', 'origin': '27_81~CUW~25_91#MGNP'} Metrics: ['ELUC: 7.019813877472541', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.25524546131678594', 'is_elite: False']\n", + "Id: 28_64 Identity: {'ancestor_count': 25, 'ancestor_ids': ['27_94', '26_69'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_64', 'origin': '27_94~CUW~26_69#MGNP'} Metrics: ['ELUC: 5.9245783306805215', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.12440145812254524', 'is_elite: False']\n", + "Id: 28_87 Identity: {'ancestor_count': 25, 'ancestor_ids': ['27_39', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_87', 'origin': '27_39~CUW~1_1#MGNP'} Metrics: ['ELUC: 3.950111572918723', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11664530988220262', 'is_elite: False']\n", + "Id: 28_66 Identity: {'ancestor_count': 22, 'ancestor_ids': ['1_1', '27_13'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_66', 'origin': '1_1~CUW~27_13#MGNP'} Metrics: ['ELUC: 1.0695656333897907', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.057237323289726', 'is_elite: False']\n", + "Id: 28_26 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_69', '27_44'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_26', 'origin': '26_69~CUW~27_44#MGNP'} Metrics: ['ELUC: 0.9738235418088801', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09900726097668046', 'is_elite: False']\n", + "Id: 28_85 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_85', 'origin': '27_81~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.36184829478125113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23062292671330464', 'is_elite: False']\n", + "Id: 28_21 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_21', 'origin': '1_1~CUW~25_23#MGNP'} Metrics: ['ELUC: 0.35412368823823775', 'NSGA-II_crowding_distance: 0.492012061829542', 'NSGA-II_rank: 4', 'change: 0.07153169196598946', 'is_elite: False']\n", + "Id: 28_28 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_91', '27_44'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_28', 'origin': '25_91~CUW~27_44#MGNP'} Metrics: ['ELUC: 0.27660116083722686', 'NSGA-II_crowding_distance: 0.6491501593120417', 'NSGA-II_rank: 5', 'change: 0.11345186091216897', 'is_elite: False']\n", + "Id: 28_63 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_63', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.2310210063956336', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03108425908738607', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 28_27 Identity: {'ancestor_count': 25, 'ancestor_ids': ['27_39', '26_69'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_27', 'origin': '27_39~CUW~26_69#MGNP'} Metrics: ['ELUC: -0.11321978989218569', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.24327344701841416', 'is_elite: False']\n", + "Id: 28_60 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '22_40'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_60', 'origin': '1_1~CUW~22_40#MGNP'} Metrics: ['ELUC: -0.13948936624530403', 'NSGA-II_crowding_distance: 0.39225665569322177', 'NSGA-II_rank: 6', 'change: 0.1173405738078519', 'is_elite: False']\n", + "Id: 28_56 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_56', '27_81'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_56', 'origin': '27_56~CUW~27_81#MGNP'} Metrics: ['ELUC: -0.2952191517566449', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30318190835585457', 'is_elite: False']\n", + "Id: 28_36 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_16', '27_81'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_36', 'origin': '27_16~CUW~27_81#MGNP'} Metrics: ['ELUC: -0.6542389698211273', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.21059753206219783', 'is_elite: False']\n", + "Id: 25_91 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_91', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6767632511629323', 'NSGA-II_crowding_distance: 0.2604517177260295', 'NSGA-II_rank: 1', 'change: 0.027591555327354134', 'is_elite: True']\n", + "Id: 28_80 Identity: {'ancestor_count': 25, 'ancestor_ids': ['27_39', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_80', 'origin': '27_39~CUW~25_23#MGNP'} Metrics: ['ELUC: -0.7872337054979832', 'NSGA-II_crowding_distance: 0.3902978126446309', 'NSGA-II_rank: 6', 'change: 0.12311076757692643', 'is_elite: False']\n", + "Id: 28_97 Identity: {'ancestor_count': 22, 'ancestor_ids': ['2_49', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_97', 'origin': '2_49~CUW~26_45#MGNP'} Metrics: ['ELUC: -1.1823508153850915', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25714637684328234', 'is_elite: False']\n", + "Id: 28_18 Identity: {'ancestor_count': 2, 'ancestor_ids': ['25_91', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_18', 'origin': '25_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5558471205164908', 'NSGA-II_crowding_distance: 0.20739087590874278', 'NSGA-II_rank: 2', 'change: 0.04292531926710206', 'is_elite: False']\n", + "Id: 28_98 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_98', 'origin': '26_45~CUW~25_23#MGNP'} Metrics: ['ELUC: -1.6481433063947482', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.18720430029129062', 'is_elite: False']\n", + "Id: 28_59 Identity: {'ancestor_count': 22, 'ancestor_ids': ['27_18', '26_69'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_59', 'origin': '27_18~CUW~26_69#MGNP'} Metrics: ['ELUC: -2.0885476007867703', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.056339461843420174', 'is_elite: False']\n", + "Id: 28_57 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_57', 'origin': '26_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2351248586471186', 'NSGA-II_crowding_distance: 0.11699181949829865', 'NSGA-II_rank: 2', 'change: 0.04499943332442937', 'is_elite: False']\n", + "Id: 26_69 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_69', 'origin': '23_59~CUW~23_59#MGNP'} Metrics: ['ELUC: -2.3593292124774066', 'NSGA-II_crowding_distance: 0.22762320948365566', 'NSGA-II_rank: 1', 'change: 0.04257255541510991', 'is_elite: True']\n", + "Id: 28_73 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '27_39'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_73', 'origin': '1_1~CUW~27_39#MGNP'} Metrics: ['ELUC: -2.59033640156758', 'NSGA-II_crowding_distance: 0.774776632202275', 'NSGA-II_rank: 4', 'change: 0.08697379566332523', 'is_elite: False']\n", + "Id: 28_51 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_69', '27_13'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_51', 'origin': '26_69~CUW~27_13#MGNP'} Metrics: ['ELUC: -2.615007036834891', 'NSGA-II_crowding_distance: 0.07893432748292768', 'NSGA-II_rank: 2', 'change: 0.05602991703493984', 'is_elite: False']\n", + "Id: 28_44 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_69', '27_13'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_44', 'origin': '26_69~CUW~27_13#MGNP'} Metrics: ['ELUC: -2.6195976226871083', 'NSGA-II_crowding_distance: 0.0854724213340527', 'NSGA-II_rank: 2', 'change: 0.059066181349724356', 'is_elite: False']\n", + "Id: 28_48 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_66', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_48', 'origin': '27_66~CUW~25_23#MGNP'} Metrics: ['ELUC: -2.646909354285471', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.22829137722051554', 'is_elite: False']\n", + "Id: 28_22 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_16', '26_69'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_22', 'origin': '27_16~CUW~26_69#MGNP'} Metrics: ['ELUC: -2.727013814320092', 'NSGA-II_crowding_distance: 1.716806624875614', 'NSGA-II_rank: 7', 'change: 0.14417999226402528', 'is_elite: False']\n", + "Id: 28_53 Identity: {'ancestor_count': 23, 'ancestor_ids': ['1_1', '27_19'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_53', 'origin': '1_1~CUW~27_19#MGNP'} Metrics: ['ELUC: -2.886723439415458', 'NSGA-II_crowding_distance: 0.30284849459817814', 'NSGA-II_rank: 3', 'change: 0.07445511509559057', 'is_elite: False']\n", + "Id: 28_25 Identity: {'ancestor_count': 25, 'ancestor_ids': ['25_91', '27_100'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_25', 'origin': '25_91~CUW~27_100#MGNP'} Metrics: ['ELUC: -2.91627394528567', 'NSGA-II_crowding_distance: 0.21640356493842344', 'NSGA-II_rank: 2', 'change: 0.07308270222358595', 'is_elite: False']\n", + "Id: 28_12 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '25_91'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_12', 'origin': '25_23~CUW~25_91#MGNP'} Metrics: ['ELUC: -3.1680812977452164', 'NSGA-II_crowding_distance: 0.12448216288587338', 'NSGA-II_rank: 1', 'change: 0.05323081331668409', 'is_elite: False']\n", + "Id: 28_35 Identity: {'ancestor_count': 22, 'ancestor_ids': ['27_18', '25_91'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_35', 'origin': '27_18~CUW~25_91#MGNP'} Metrics: ['ELUC: -3.225445443678665', 'NSGA-II_crowding_distance: 0.10657715370275836', 'NSGA-II_rank: 1', 'change: 0.06501699930452441', 'is_elite: False']\n", + "Id: 28_71 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_91', '27_18'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_71', 'origin': '25_91~CUW~27_18#MGNP'} Metrics: ['ELUC: -3.9816844131070126', 'NSGA-II_crowding_distance: 0.2314085247863835', 'NSGA-II_rank: 3', 'change: 0.09384962070867262', 'is_elite: False']\n", + "Id: 25_23 Identity: {'ancestor_count': 20, 'ancestor_ids': ['24_63', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_23', 'origin': '24_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.159026014020856', 'NSGA-II_crowding_distance: 0.20085108330496132', 'NSGA-II_rank: 1', 'change: 0.06821442363038034', 'is_elite: False']\n", + "Id: 28_96 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_96', 'origin': '26_45~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.3491451522303475', 'NSGA-II_crowding_distance: 0.39656126391076', 'NSGA-II_rank: 6', 'change: 0.1286284998024444', 'is_elite: False']\n", + "Id: 28_32 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_13', '27_56'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_32', 'origin': '27_13~CUW~27_56#MGNP'} Metrics: ['ELUC: -4.604377693608269', 'NSGA-II_crowding_distance: 0.20419772859323676', 'NSGA-II_rank: 2', 'change: 0.08290073707738688', 'is_elite: False']\n", + "Id: 28_14 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_14', 'origin': '26_45~CUW~25_23#MGNP'} Metrics: ['ELUC: -4.722322178286348', 'NSGA-II_crowding_distance: 1.0815921881326132', 'NSGA-II_rank: 6', 'change: 0.13787511650375442', 'is_elite: False']\n", + "Id: 28_86 Identity: {'ancestor_count': 22, 'ancestor_ids': ['27_18', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_86', 'origin': '27_18~CUW~26_45#MGNP'} Metrics: ['ELUC: -4.728901342283887', 'NSGA-II_crowding_distance: 0.2851202046912594', 'NSGA-II_rank: 3', 'change: 0.09559920160434679', 'is_elite: False']\n", + "Id: 27_18 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '25_24'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_18', 'origin': '25_23~CUW~25_24#MGNP'} Metrics: ['ELUC: -4.953486052090962', 'NSGA-II_crowding_distance: 0.1815648195440979', 'NSGA-II_rank: 2', 'change: 0.09297131237430452', 'is_elite: False']\n", + "Id: 28_93 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_91', '27_44'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_93', 'origin': '25_91~CUW~27_44#MGNP'} Metrics: ['ELUC: -5.230930021242247', 'NSGA-II_crowding_distance: 0.6821386327275771', 'NSGA-II_rank: 5', 'change: 0.11481166734706347', 'is_elite: False']\n", + "Id: 28_42 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_23', '27_16'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_42', 'origin': '25_23~CUW~27_16#MGNP'} Metrics: ['ELUC: -5.665444956656715', 'NSGA-II_crowding_distance: 0.7720211472394666', 'NSGA-II_rank: 5', 'change: 0.13675180557720273', 'is_elite: False']\n", + "Id: 28_83 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '25_91'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_83', 'origin': '27_19~CUW~25_91#MGNP'} Metrics: ['ELUC: -5.7752944116200995', 'NSGA-II_crowding_distance: 0.2476772060971253', 'NSGA-II_rank: 1', 'change: 0.08167476370294353', 'is_elite: True']\n", + "Id: 28_38 Identity: {'ancestor_count': 22, 'ancestor_ids': ['2_49', '27_13'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_38', 'origin': '2_49~CUW~27_13#MGNP'} Metrics: ['ELUC: -5.807594495851381', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26000283363127596', 'is_elite: False']\n", + "Id: 28_17 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_23', '27_13'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_17', 'origin': '25_23~CUW~27_13#MGNP'} Metrics: ['ELUC: -6.093544056319395', 'NSGA-II_crowding_distance: 1.0799015625905928', 'NSGA-II_rank: 4', 'change: 0.11097422032845386', 'is_elite: False']\n", + "Id: 28_61 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_45', '27_100'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_61', 'origin': '26_45~CUW~27_100#MGNP'} Metrics: ['ELUC: -6.185354812633853', 'NSGA-II_crowding_distance: 0.9540480108162253', 'NSGA-II_rank: 5', 'change: 0.20799424203297665', 'is_elite: False']\n", + "Id: 28_46 Identity: {'ancestor_count': 25, 'ancestor_ids': ['27_100', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_46', 'origin': '27_100~CUW~25_23#MGNP'} Metrics: ['ELUC: -6.640660093857897', 'NSGA-II_crowding_distance: 0.1445187728142783', 'NSGA-II_rank: 2', 'change: 0.09702594358319643', 'is_elite: False']\n", + "Id: 28_33 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '27_19'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_33', 'origin': '27_19~CUW~27_19#MGNP'} Metrics: ['ELUC: -6.844603020662543', 'NSGA-II_crowding_distance: 0.43190152470908416', 'NSGA-II_rank: 3', 'change: 0.10863007534554213', 'is_elite: False']\n", + "Id: 28_47 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_47', 'origin': '27_19~CUW~25_23#MGNP'} Metrics: ['ELUC: -6.904560845235359', 'NSGA-II_crowding_distance: 0.2254300424092394', 'NSGA-II_rank: 2', 'change: 0.09898732904248646', 'is_elite: False']\n", + "Id: 28_75 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_75', 'origin': '27_19~CUW~25_23#MGNP'} Metrics: ['ELUC: -6.995214831712791', 'NSGA-II_crowding_distance: 0.16514108784897422', 'NSGA-II_rank: 1', 'change: 0.09398478402946583', 'is_elite: False']\n", + "Id: 28_67 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '2_49'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_67', 'origin': '26_45~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.3542194629415265', 'NSGA-II_crowding_distance: 1.2088537312186542', 'NSGA-II_rank: 7', 'change: 0.25465914413118024', 'is_elite: False']\n", + "Id: 27_19 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_24', '26_77'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_19', 'origin': '25_24~CUW~26_77#MGNP'} Metrics: ['ELUC: -7.5593755506690865', 'NSGA-II_crowding_distance: 0.29728242693580226', 'NSGA-II_rank: 1', 'change: 0.10067277731826463', 'is_elite: True']\n", + "Id: 28_88 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_16', '27_19'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_88', 'origin': '27_16~CUW~27_19#MGNP'} Metrics: ['ELUC: -7.861782657576073', 'NSGA-II_crowding_distance: 0.2536951796622044', 'NSGA-II_rank: 3', 'change: 0.14086520857447266', 'is_elite: False']\n", + "Id: 28_30 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_23', '27_48'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_30', 'origin': '25_23~CUW~27_48#MGNP'} Metrics: ['ELUC: -8.14737020083266', 'NSGA-II_crowding_distance: 0.1377925532943895', 'NSGA-II_rank: 3', 'change: 0.1454318924730619', 'is_elite: False']\n", + "Id: 28_90 Identity: {'ancestor_count': 23, 'ancestor_ids': ['22_40', '27_19'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_90', 'origin': '22_40~CUW~27_19#MGNP'} Metrics: ['ELUC: -8.266777749447684', 'NSGA-II_crowding_distance: 0.2698460401084123', 'NSGA-II_rank: 2', 'change: 0.128841402371622', 'is_elite: False']\n", + "Id: 28_100 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_45', '27_19'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_100', 'origin': '26_45~CUW~27_19#MGNP'} Metrics: ['ELUC: -8.389533233327167', 'NSGA-II_crowding_distance: 0.7794068183282619', 'NSGA-II_rank: 4', 'change: 0.1763420333512482', 'is_elite: False']\n", + "Id: 28_11 Identity: {'ancestor_count': 25, 'ancestor_ids': ['25_23', '27_39'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_11', 'origin': '25_23~CUW~27_39#MGNP'} Metrics: ['ELUC: -8.621270384844172', 'NSGA-II_crowding_distance: 1.2111820803960183', 'NSGA-II_rank: 6', 'change: 0.23112409046403876', 'is_elite: False']\n", + "Id: 28_77 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '25_91'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_77', 'origin': '26_45~CUW~25_91#MGNP'} Metrics: ['ELUC: -8.91118614080032', 'NSGA-II_crowding_distance: 0.18587875260829012', 'NSGA-II_rank: 2', 'change: 0.13611985865656145', 'is_elite: False']\n", + "Id: 28_58 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '27_13'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_58', 'origin': '26_45~CUW~27_13#MGNP'} Metrics: ['ELUC: -9.211997899816154', 'NSGA-II_crowding_distance: 0.46254540402586186', 'NSGA-II_rank: 3', 'change: 0.14864244545129737', 'is_elite: False']\n", + "Id: 28_39 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_39', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.218333482883082', 'NSGA-II_crowding_distance: 0.283193375124386', 'NSGA-II_rank: 7', 'change: 0.26509995989316637', 'is_elite: False']\n", + "Id: 28_76 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_25', '27_81'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_76', 'origin': '27_25~CUW~27_81#MGNP'} Metrics: ['ELUC: -9.237425311081866', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.27928349342554587', 'is_elite: False']\n", + "Id: 28_45 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '26_69'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_45', 'origin': '26_45~CUW~26_69#MGNP'} Metrics: ['ELUC: -9.54340293016833', 'NSGA-II_crowding_distance: 0.2073459950062026', 'NSGA-II_rank: 4', 'change: 0.18341165537764426', 'is_elite: False']\n", + "Id: 28_55 Identity: {'ancestor_count': 2, 'ancestor_ids': ['25_91', '2_49'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_55', 'origin': '25_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.838321025283062', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.24945321824641847', 'is_elite: False']\n", + "Id: 28_50 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_18', '27_25'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_50', 'origin': '27_18~CUW~27_25#MGNP'} Metrics: ['ELUC: -10.08075330701382', 'NSGA-II_crowding_distance: 0.2893546346025454', 'NSGA-II_rank: 4', 'change: 0.18726779651521575', 'is_elite: False']\n", + "Id: 28_65 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_91', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_65', 'origin': '25_91~CUW~26_45#MGNP'} Metrics: ['ELUC: -10.23981399180186', 'NSGA-II_crowding_distance: 0.33132522155965494', 'NSGA-II_rank: 1', 'change: 0.1276253874739408', 'is_elite: True']\n", + "Id: 28_99 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_44', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_99', 'origin': '27_44~CUW~25_23#MGNP'} Metrics: ['ELUC: -10.257159103153004', 'NSGA-II_crowding_distance: 0.5788286934484919', 'NSGA-II_rank: 5', 'change: 0.21239741146073035', 'is_elite: False']\n", + "Id: 28_49 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_44', '1_1'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_49', 'origin': '27_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.280634363572581', 'NSGA-II_crowding_distance: 0.25565497606813087', 'NSGA-II_rank: 2', 'change: 0.14442287166877915', 'is_elite: False']\n", + "Id: 28_68 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '27_44'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_68', 'origin': '27_19~CUW~27_44#MGNP'} Metrics: ['ELUC: -10.687232575208936', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2340204341760185', 'is_elite: False']\n", + "Id: 28_24 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_23', '27_16'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_24', 'origin': '25_23~CUW~27_16#MGNP'} Metrics: ['ELUC: -11.093883536875762', 'NSGA-II_crowding_distance: 0.12267533014637072', 'NSGA-II_rank: 1', 'change: 0.13955114989367454', 'is_elite: False']\n", + "Id: 28_70 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_16', '22_40'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_70', 'origin': '27_16~CUW~22_40#MGNP'} Metrics: ['ELUC: -11.559619289903889', 'NSGA-II_crowding_distance: 0.09578945333405003', 'NSGA-II_rank: 1', 'change: 0.14183146946260322', 'is_elite: False']\n", + "Id: 28_91 Identity: {'ancestor_count': 25, 'ancestor_ids': ['27_94', '26_69'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_91', 'origin': '27_94~CUW~26_69#MGNP'} Metrics: ['ELUC: -11.748904558028292', 'NSGA-II_crowding_distance: 0.14210821012570254', 'NSGA-II_rank: 2', 'change: 0.1564759270436463', 'is_elite: False']\n", + "Id: 28_74 Identity: {'ancestor_count': 25, 'ancestor_ids': ['22_40', '27_39'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_74', 'origin': '22_40~CUW~27_39#MGNP'} Metrics: ['ELUC: -11.79004676539094', 'NSGA-II_crowding_distance: 0.016834451570939647', 'NSGA-II_rank: 2', 'change: 0.15681356909300811', 'is_elite: False']\n", + "Id: 28_82 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_23', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_82', 'origin': '25_23~CUW~26_45#MGNP'} Metrics: ['ELUC: -11.840568218225066', 'NSGA-II_crowding_distance: 0.12206099952332633', 'NSGA-II_rank: 2', 'change: 0.1593229751043708', 'is_elite: False']\n", + "Id: 28_40 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_18', '27_25'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_40', 'origin': '27_18~CUW~27_25#MGNP'} Metrics: ['ELUC: -11.970922174312854', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.19793160759758244', 'is_elite: False']\n", + "Id: 28_41 Identity: {'ancestor_count': 23, 'ancestor_ids': ['22_40', '27_48'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_41', 'origin': '22_40~CUW~27_48#MGNP'} Metrics: ['ELUC: -12.090894994659767', 'NSGA-II_crowding_distance: 0.11472276736012667', 'NSGA-II_rank: 1', 'change: 0.15121299635504562', 'is_elite: False']\n", + "Id: 28_79 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_23', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_79', 'origin': '25_23~CUW~26_45#MGNP'} Metrics: ['ELUC: -12.091042692259448', 'NSGA-II_crowding_distance: 0.44061034125290155', 'NSGA-II_rank: 3', 'change: 0.18272654598116053', 'is_elite: False']\n", + "Id: 28_54 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '25_91'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_54', 'origin': '26_45~CUW~25_91#MGNP'} Metrics: ['ELUC: -12.482288559004298', 'NSGA-II_crowding_distance: 0.419549924403392', 'NSGA-II_rank: 3', 'change: 0.19341049570582625', 'is_elite: False']\n", + "Id: 28_34 Identity: {'ancestor_count': 23, 'ancestor_ids': ['22_40', '27_48'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_34', 'origin': '22_40~CUW~27_48#MGNP'} Metrics: ['ELUC: -12.601679477948101', 'NSGA-II_crowding_distance: 0.10870830338043327', 'NSGA-II_rank: 1', 'change: 0.1583781040534916', 'is_elite: False']\n", + "Id: 28_72 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_45', '27_39'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_72', 'origin': '26_45~CUW~27_39#MGNP'} Metrics: ['ELUC: -12.678259346753723', 'NSGA-II_crowding_distance: 0.22667565350461294', 'NSGA-II_rank: 2', 'change: 0.17391785898162926', 'is_elite: False']\n", + "Id: 28_62 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_16', '27_25'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_62', 'origin': '27_16~CUW~27_25#MGNP'} Metrics: ['ELUC: -12.786486763140921', 'NSGA-II_crowding_distance: 0.13308664284977045', 'NSGA-II_rank: 1', 'change: 0.17184472478090487', 'is_elite: False']\n", + "Id: 28_37 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_16', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_37', 'origin': '27_16~CUW~26_45#MGNP'} Metrics: ['ELUC: -13.176352795003186', 'NSGA-II_crowding_distance: 0.20935046442372296', 'NSGA-II_rank: 2', 'change: 0.19605147076424786', 'is_elite: False']\n", + "Id: 28_13 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_13', 'origin': '27_81~CUW~26_45#MGNP'} Metrics: ['ELUC: -13.322771026338463', 'NSGA-II_crowding_distance: 0.4750098982174499', 'NSGA-II_rank: 3', 'change: 0.2611217529848447', 'is_elite: False']\n", + "Id: 26_45 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '23_80'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_45', 'origin': '22_40~CUW~23_80#MGNP'} Metrics: ['ELUC: -13.557119758977821', 'NSGA-II_crowding_distance: 0.12765250338321704', 'NSGA-II_rank: 1', 'change: 0.1818740763555117', 'is_elite: False']\n", + "Id: 28_92 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_92', 'origin': '26_45~CUW~25_23#MGNP'} Metrics: ['ELUC: -13.643650535704205', 'NSGA-II_crowding_distance: 0.08277493901904825', 'NSGA-II_rank: 1', 'change: 0.1953870536036465', 'is_elite: False']\n", + "Id: 28_23 Identity: {'ancestor_count': 26, 'ancestor_ids': ['25_91', '27_81'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_23', 'origin': '25_91~CUW~27_81#MGNP'} Metrics: ['ELUC: -13.998739617418689', 'NSGA-II_crowding_distance: 0.27624079261910417', 'NSGA-II_rank: 3', 'change: 0.27985229716278104', 'is_elite: False']\n", + "Id: 28_95 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_16', '22_40'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_95', 'origin': '27_16~CUW~22_40#MGNP'} Metrics: ['ELUC: -14.189088166000793', 'NSGA-II_crowding_distance: 0.054365642035205296', 'NSGA-II_rank: 1', 'change: 0.19584757484784351', 'is_elite: False']\n", + "Id: 27_16 Identity: {'ancestor_count': 22, 'ancestor_ids': ['22_40', '26_48'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_16', 'origin': '22_40~CUW~26_48#MGNP'} Metrics: ['ELUC: -14.275480644948987', 'NSGA-II_crowding_distance: 0.5226523977151968', 'NSGA-II_rank: 2', 'change: 0.20208558292570444', 'is_elite: False']\n", + "Id: 28_31 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '27_13'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_31', 'origin': '26_45~CUW~27_13#MGNP'} Metrics: ['ELUC: -14.353222777762866', 'NSGA-II_crowding_distance: 0.048902699477703', 'NSGA-II_rank: 1', 'change: 0.19956688999943994', 'is_elite: False']\n", + "Id: 28_29 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_16', '27_44'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_29', 'origin': '27_16~CUW~27_44#MGNP'} Metrics: ['ELUC: -14.376989432259593', 'NSGA-II_crowding_distance: 0.11195460431033645', 'NSGA-II_rank: 1', 'change: 0.20725030815112053', 'is_elite: False']\n", + "Id: 28_81 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '22_40'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_81', 'origin': '2_49~CUW~22_40#MGNP'} Metrics: ['ELUC: -14.857702973476458', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29898244649758215', 'is_elite: False']\n", + "Id: 28_16 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_16', 'origin': '22_40~CUW~25_23#MGNP'} Metrics: ['ELUC: -15.048037241462824', 'NSGA-II_crowding_distance: 0.3298024387465267', 'NSGA-II_rank: 1', 'change: 0.22118043337860718', 'is_elite: True']\n", + "Id: 28_52 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_52', 'origin': '27_81~CUW~26_45#MGNP'} Metrics: ['ELUC: -15.899694610610458', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2863814410542885', 'is_elite: False']\n", + "Id: 28_94 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '27_16'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_94', 'origin': '27_81~CUW~27_16#MGNP'} Metrics: ['ELUC: -16.324831648431285', 'NSGA-II_crowding_distance: 0.4192782202312645', 'NSGA-II_rank: 1', 'change: 0.27260052334811824', 'is_elite: True']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 27_81 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_76', '26_76'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_81', 'origin': '26_76~CUW~26_76#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 28_15 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_15', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 28_69 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_69', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 28_84 Identity: {'ancestor_count': 22, 'ancestor_ids': ['2_49', '27_18'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_84', 'origin': '2_49~CUW~27_18#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 28.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 29...:\n", + "PopulationResponse:\n", + " Generation: 29\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/29/20240219-230920\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 29 and asking ESP for generation 30...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 29 data persisted.\n", + "Evaluated candidates:\n", + "Id: 29_36 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '2_49'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_36', 'origin': '26_45~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 29_32 Identity: {'ancestor_count': 24, 'ancestor_ids': ['2_49', '28_29'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_32', 'origin': '2_49~CUW~28_29#MGNP'} Metrics: ['ELUC: 23.720744048453657', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3025332613976281', 'is_elite: False']\n", + "Id: 29_12 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_24', '2_49'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_12', 'origin': '28_24~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.664401783399114', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.30366454568761975', 'is_elite: False']\n", + "Id: 29_31 Identity: {'ancestor_count': 22, 'ancestor_ids': ['28_16', '2_49'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_31', 'origin': '28_16~CUW~2_49#MGNP'} Metrics: ['ELUC: 16.60216557669733', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.28756425546738695', 'is_elite: False']\n", + "Id: 29_68 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_84', '28_62'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_68', 'origin': '28_84~CUW~28_62#MGNP'} Metrics: ['ELUC: 13.313482962223157', 'NSGA-II_crowding_distance: 1.0803393271317465', 'NSGA-II_rank: 13', 'change: 0.29598406209359346', 'is_elite: False']\n", + "Id: 29_55 Identity: {'ancestor_count': 24, 'ancestor_ids': ['2_49', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_55', 'origin': '2_49~CUW~28_83#MGNP'} Metrics: ['ELUC: 10.313087917305186', 'NSGA-II_crowding_distance: 1.5064810174814056', 'NSGA-II_rank: 13', 'change: 0.3098627200579147', 'is_elite: False']\n", + "Id: 29_85 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_85', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 5.923567759105598', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3329419482172613', 'is_elite: False']\n", + "Id: 29_88 Identity: {'ancestor_count': 23, 'ancestor_ids': ['2_49', '27_19'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_88', 'origin': '2_49~CUW~27_19#MGNP'} Metrics: ['ELUC: 4.12418605787198', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2637276325738685', 'is_elite: False']\n", + "Id: 29_47 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_84', '28_62'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_47', 'origin': '28_84~CUW~28_62#MGNP'} Metrics: ['ELUC: 3.0580415704734993', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.23495874084191612', 'is_elite: False']\n", + "Id: 29_80 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_65', '28_94'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_80', 'origin': '28_65~CUW~28_94#MGNP'} Metrics: ['ELUC: 2.98953407609502', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.19145550639767925', 'is_elite: False']\n", + "Id: 29_83 Identity: {'ancestor_count': 23, 'ancestor_ids': ['2_49', '27_19'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_83', 'origin': '2_49~CUW~27_19#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 29_46 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_94', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_46', 'origin': '28_94~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.017085585243342', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.1881539049036524', 'is_elite: False']\n", + "Id: 29_58 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '25_91'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_58', 'origin': '26_69~CUW~25_91#MGNP'} Metrics: ['ELUC: 0.1435255192363816', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0499585584886078', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 29_59 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_59', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.2601468813861334', 'NSGA-II_crowding_distance: 0.11454717838905949', 'NSGA-II_rank: 1', 'change: 0.02024492555765747', 'is_elite: False']\n", + "Id: 29_13 Identity: {'ancestor_count': 22, 'ancestor_ids': ['1_1', '28_12'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_13', 'origin': '1_1~CUW~28_12#MGNP'} Metrics: ['ELUC: -0.4144480758715513', 'NSGA-II_crowding_distance: 0.15439720125383705', 'NSGA-II_rank: 3', 'change: 0.05248123490576067', 'is_elite: False']\n", + "Id: 29_75 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_91', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_75', 'origin': '25_91~CUW~28_16#MGNP'} Metrics: ['ELUC: -0.45259389610635553', 'NSGA-II_crowding_distance: 0.3148488395928839', 'NSGA-II_rank: 3', 'change: 0.07751117012595916', 'is_elite: False']\n", + "Id: 29_48 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '25_23'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_48', 'origin': '2_49~CUW~25_23#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.3339436948066058', 'NSGA-II_rank: 11', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 29_77 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_84', '2_49'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_77', 'origin': '28_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 1.666056305193394', 'NSGA-II_rank: 11', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 29_62 Identity: {'ancestor_count': 27, 'ancestor_ids': ['27_19', '28_94'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_62', 'origin': '27_19~CUW~28_94#MGNP'} Metrics: ['ELUC: -0.6597904914955743', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.22887750393226505', 'is_elite: False']\n", + "Id: 25_91 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 25, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '25_91', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6767632511629323', 'NSGA-II_crowding_distance: 0.194221612825118', 'NSGA-II_rank: 1', 'change: 0.027591555327354134', 'is_elite: False']\n", + "Id: 29_28 Identity: {'ancestor_count': 24, 'ancestor_ids': ['1_1', '28_75'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_28', 'origin': '1_1~CUW~28_75#MGNP'} Metrics: ['ELUC: -1.0613540481402768', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04355257202604242', 'is_elite: False']\n", + "Id: 29_39 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_41', '28_84'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_39', 'origin': '28_41~CUW~28_84#MGNP'} Metrics: ['ELUC: -1.7163319931705072', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27573855788021945', 'is_elite: False']\n", + "Id: 29_89 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '25_91'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_89', 'origin': '1_1~CUW~25_91#MGNP'} Metrics: ['ELUC: -1.7718680275598429', 'NSGA-II_crowding_distance: 0.11050991014675289', 'NSGA-II_rank: 2', 'change: 0.04461743453143177', 'is_elite: False']\n", + "Id: 29_78 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_24', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_78', 'origin': '28_24~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.9505823823230903', 'NSGA-II_crowding_distance: 0.17374977961485535', 'NSGA-II_rank: 2', 'change: 0.057152636081241055', 'is_elite: False']\n", + "Id: 29_15 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_65', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_15', 'origin': '28_65~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2046141481515877', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09422016177881326', 'is_elite: False']\n", + "Id: 26_69 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_69', 'origin': '23_59~CUW~23_59#MGNP'} Metrics: ['ELUC: -2.3593292124774066', 'NSGA-II_crowding_distance: 0.2539128879818792', 'NSGA-II_rank: 1', 'change: 0.04257255541510991', 'is_elite: True']\n", + "Id: 29_92 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_84', '28_24'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_92', 'origin': '28_84~CUW~28_24#MGNP'} Metrics: ['ELUC: -2.63663332977383', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.21826131406371316', 'is_elite: False']\n", + "Id: 29_90 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_84', '28_75'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_90', 'origin': '28_84~CUW~28_75#MGNP'} Metrics: ['ELUC: -2.9250988156330315', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2523626330790948', 'is_elite: False']\n", + "Id: 29_70 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_16', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_70', 'origin': '28_16~CUW~28_83#MGNP'} Metrics: ['ELUC: -3.0109241788836845', 'NSGA-II_crowding_distance: 0.17505782449956542', 'NSGA-II_rank: 2', 'change: 0.06864017013004485', 'is_elite: False']\n", + "Id: 29_51 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_91', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_51', 'origin': '25_91~CUW~28_83#MGNP'} Metrics: ['ELUC: -3.398888447248926', 'NSGA-II_crowding_distance: 0.3980070275692683', 'NSGA-II_rank: 3', 'change: 0.08302222071137873', 'is_elite: False']\n", + "Id: 29_17 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_17', 'origin': '25_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.4725484198808614', 'NSGA-II_crowding_distance: 0.20800202958322156', 'NSGA-II_rank: 1', 'change: 0.05590816660896231', 'is_elite: True']\n", + "Id: 29_93 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_91', '25_23'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_93', 'origin': '25_91~CUW~25_23#MGNP'} Metrics: ['ELUC: -3.4760498285756882', 'NSGA-II_crowding_distance: 0.37174104796655055', 'NSGA-II_rank: 2', 'change: 0.07675674771129332', 'is_elite: False']\n", + "Id: 29_96 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_62', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_96', 'origin': '28_62~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.224633579153699', 'NSGA-II_crowding_distance: 0.43235274728678297', 'NSGA-II_rank: 4', 'change: 0.12704595329841947', 'is_elite: False']\n", + "Id: 29_24 Identity: {'ancestor_count': 23, 'ancestor_ids': ['1_1', '27_19'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_24', 'origin': '1_1~CUW~27_19#MGNP'} Metrics: ['ELUC: -4.289041153412917', 'NSGA-II_crowding_distance: 0.25135218882925', 'NSGA-II_rank: 3', 'change: 0.11519436425481483', 'is_elite: False']\n", + "Id: 29_87 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_69', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_87', 'origin': '26_69~CUW~28_83#MGNP'} Metrics: ['ELUC: -4.546166374002797', 'NSGA-II_crowding_distance: 0.2173248975459255', 'NSGA-II_rank: 1', 'change: 0.06752442504308302', 'is_elite: True']\n", + "Id: 29_41 Identity: {'ancestor_count': 24, 'ancestor_ids': ['27_19', '28_34'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_41', 'origin': '27_19~CUW~28_34#MGNP'} Metrics: ['ELUC: -4.766843560446575', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.13300451055990126', 'is_elite: False']\n", + "Id: 29_25 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_41', '26_69'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_25', 'origin': '28_41~CUW~26_69#MGNP'} Metrics: ['ELUC: -4.851194321957768', 'NSGA-II_crowding_distance: 0.07905282038028247', 'NSGA-II_rank: 3', 'change: 0.12089081891069647', 'is_elite: False']\n", + "Id: 29_40 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_84', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_40', 'origin': '28_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.882627150157583', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2505940611588899', 'is_elite: False']\n", + "Id: 29_11 Identity: {'ancestor_count': 22, 'ancestor_ids': ['28_16', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_11', 'origin': '28_16~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.970015654862337', 'NSGA-II_crowding_distance: 0.21640601463207992', 'NSGA-II_rank: 3', 'change: 0.12385380420703121', 'is_elite: False']\n", + "Id: 29_100 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_100', 'origin': '27_19~CUW~28_16#MGNP'} Metrics: ['ELUC: -5.422707605214539', 'NSGA-II_crowding_distance: 0.34384812820817223', 'NSGA-II_rank: 5', 'change: 0.13670617239997987', 'is_elite: False']\n", + "Id: 29_82 Identity: {'ancestor_count': 22, 'ancestor_ids': ['28_16', '26_69'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_82', 'origin': '28_16~CUW~26_69#MGNP'} Metrics: ['ELUC: -5.581559665893483', 'NSGA-II_crowding_distance: 0.4470882376526242', 'NSGA-II_rank: 4', 'change: 0.13237700140103667', 'is_elite: False']\n", + "Id: 29_60 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_65', '26_69'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_60', 'origin': '28_65~CUW~26_69#MGNP'} Metrics: ['ELUC: -5.675814198976561', 'NSGA-II_crowding_distance: 0.49924436074705114', 'NSGA-II_rank: 5', 'change: 0.15462258868683634', 'is_elite: False']\n", + "Id: 28_83 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '25_91'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_83', 'origin': '27_19~CUW~25_91#MGNP'} Metrics: ['ELUC: -5.7752944116200995', 'NSGA-II_crowding_distance: 0.19526071765356529', 'NSGA-II_rank: 1', 'change: 0.08167476370294353', 'is_elite: True']\n", + "Id: 29_50 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_75', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_50', 'origin': '28_75~CUW~28_83#MGNP'} Metrics: ['ELUC: -6.2541906245230425', 'NSGA-II_crowding_distance: 0.16514108784897422', 'NSGA-II_rank: 1', 'change: 0.09680017379387201', 'is_elite: False']\n", + "Id: 29_34 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '27_19'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_34', 'origin': '27_19~CUW~27_19#MGNP'} Metrics: ['ELUC: -6.504559959580751', 'NSGA-II_crowding_distance: 0.4291146471530811', 'NSGA-II_rank: 2', 'change: 0.10604960349134643', 'is_elite: False']\n", + "Id: 29_37 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_83', '28_94'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_37', 'origin': '28_83~CUW~28_94#MGNP'} Metrics: ['ELUC: -6.535495047019637', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.20754751559676438', 'is_elite: False']\n", + "Id: 29_29 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_23', '28_65'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_29', 'origin': '25_23~CUW~28_65#MGNP'} Metrics: ['ELUC: -7.33310029701847', 'NSGA-II_crowding_distance: 0.5333904417214814', 'NSGA-II_rank: 5', 'change: 0.15613712174700078', 'is_elite: False']\n", + "Id: 29_21 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_75', '28_12'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_21', 'origin': '28_75~CUW~28_12#MGNP'} Metrics: ['ELUC: -7.496081886816531', 'NSGA-II_crowding_distance: 0.271338588251677', 'NSGA-II_rank: 2', 'change: 0.1201523838257105', 'is_elite: False']\n", + "Id: 27_19 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_24', '26_77'], 'birth_generation': 27, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '27_19', 'origin': '25_24~CUW~26_77#MGNP'} Metrics: ['ELUC: -7.5593755506690865', 'NSGA-II_crowding_distance: 0.10515965375391924', 'NSGA-II_rank: 1', 'change: 0.10067277731826463', 'is_elite: False']\n", + "Id: 29_74 Identity: {'ancestor_count': 24, 'ancestor_ids': ['27_19', '28_75'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_74', 'origin': '27_19~CUW~28_75#MGNP'} Metrics: ['ELUC: -7.668035713129519', 'NSGA-II_crowding_distance: 0.09591628395714678', 'NSGA-II_rank: 1', 'change: 0.10418408406996199', 'is_elite: False']\n", + "Id: 29_95 Identity: {'ancestor_count': 23, 'ancestor_ids': ['25_91', '28_65'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_95', 'origin': '25_91~CUW~28_65#MGNP'} Metrics: ['ELUC: -7.8032537026689335', 'NSGA-II_crowding_distance: 0.44412485231734444', 'NSGA-II_rank: 3', 'change: 0.12882338480772432', 'is_elite: False']\n", + "Id: 29_44 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_65', '28_24'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_44', 'origin': '28_65~CUW~28_24#MGNP'} Metrics: ['ELUC: -8.193154052418166', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.16808991777370474', 'is_elite: False']\n", + "Id: 29_79 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_23', '28_41'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_79', 'origin': '25_23~CUW~28_41#MGNP'} Metrics: ['ELUC: -8.554266176845779', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.16219700736308354', 'is_elite: False']\n", + "Id: 29_42 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_94', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_42', 'origin': '28_94~CUW~28_83#MGNP'} Metrics: ['ELUC: -8.655028819025189', 'NSGA-II_crowding_distance: 0.5540885982327621', 'NSGA-II_rank: 5', 'change: 0.15638984639800602', 'is_elite: False']\n", + "Id: 29_14 Identity: {'ancestor_count': 24, 'ancestor_ids': ['27_19', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_14', 'origin': '27_19~CUW~28_83#MGNP'} Metrics: ['ELUC: -8.677398152468978', 'NSGA-II_crowding_distance: 0.19369255695043455', 'NSGA-II_rank: 1', 'change: 0.11031887080537546', 'is_elite: False']\n", + "Id: 29_16 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_84', '27_19'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_16', 'origin': '28_84~CUW~27_19#MGNP'} Metrics: ['ELUC: -8.710029194179226', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.25052939881256003', 'is_elite: False']\n", + "Id: 29_38 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_69', '28_24'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_38', 'origin': '26_69~CUW~28_24#MGNP'} Metrics: ['ELUC: -8.727677351462738', 'NSGA-II_crowding_distance: 0.5116937101539498', 'NSGA-II_rank: 4', 'change: 0.14924484987310274', 'is_elite: False']\n", + "Id: 29_64 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_65', '28_94'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_64', 'origin': '28_65~CUW~28_94#MGNP'} Metrics: ['ELUC: -9.287898514155984', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.2003552043848532', 'is_elite: False']\n", + "Id: 29_66 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_34', '25_91'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_66', 'origin': '28_34~CUW~25_91#MGNP'} Metrics: ['ELUC: -9.378945132771277', 'NSGA-II_crowding_distance: 1.1227614300703461', 'NSGA-II_rank: 5', 'change: 0.1792091125434809', 'is_elite: False']\n", + "Id: 29_69 Identity: {'ancestor_count': 24, 'ancestor_ids': ['27_19', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_69', 'origin': '27_19~CUW~28_83#MGNP'} Metrics: ['ELUC: -9.466385621343811', 'NSGA-II_crowding_distance: 0.24480766006806182', 'NSGA-II_rank: 2', 'change: 0.12651991275776944', 'is_elite: False']\n", + "Id: 29_86 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '25_91'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_86', 'origin': '2_49~CUW~25_91#MGNP'} Metrics: ['ELUC: -9.482097648354392', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2771296571449933', 'is_elite: False']\n", + "Id: 29_56 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_16', '27_19'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_56', 'origin': '28_16~CUW~27_19#MGNP'} Metrics: ['ELUC: -9.625282711484566', 'NSGA-II_crowding_distance: 0.5801664052653172', 'NSGA-II_rank: 4', 'change: 0.17673239935396948', 'is_elite: False']\n", + "Id: 29_19 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_19', 'origin': '27_19~CUW~28_16#MGNP'} Metrics: ['ELUC: -9.975019022178579', 'NSGA-II_crowding_distance: 0.1468648388854159', 'NSGA-II_rank: 1', 'change: 0.12282740881122894', 'is_elite: False']\n", + "Id: 29_72 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_83', '28_41'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_72', 'origin': '28_83~CUW~28_41#MGNP'} Metrics: ['ELUC: -10.020662071752787', 'NSGA-II_crowding_distance: 0.12569722464311395', 'NSGA-II_rank: 2', 'change: 0.1410719859649785', 'is_elite: False']\n", + "Id: 28_65 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_91', '26_45'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_65', 'origin': '25_91~CUW~26_45#MGNP'} Metrics: ['ELUC: -10.23981399180186', 'NSGA-II_crowding_distance: 0.13165699553180593', 'NSGA-II_rank: 1', 'change: 0.1276253874739408', 'is_elite: False']\n", + "Id: 29_45 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_62', '28_65'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_45', 'origin': '28_62~CUW~28_65#MGNP'} Metrics: ['ELUC: -10.466774900156114', 'NSGA-II_crowding_distance: 0.31175068188940847', 'NSGA-II_rank: 3', 'change: 0.14827694548075215', 'is_elite: False']\n", + "Id: 29_26 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_24', '28_65'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_26', 'origin': '28_24~CUW~28_65#MGNP'} Metrics: ['ELUC: -10.492926834231207', 'NSGA-II_crowding_distance: 0.1308571121902057', 'NSGA-II_rank: 2', 'change: 0.14173826004922985', 'is_elite: False']\n", + "Id: 29_18 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_83', '28_84'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_18', 'origin': '28_83~CUW~28_84#MGNP'} Metrics: ['ELUC: -10.51593385770711', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.24939263914743126', 'is_elite: False']\n", + "Id: 29_99 Identity: {'ancestor_count': 27, 'ancestor_ids': ['26_69', '28_94'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_99', 'origin': '26_69~CUW~28_94#MGNP'} Metrics: ['ELUC: -10.595526676512677', 'NSGA-II_crowding_distance: 0.6359867611899872', 'NSGA-II_rank: 4', 'change: 0.2459161729124149', 'is_elite: False']\n", + "Id: 29_84 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_91', '28_24'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_84', 'origin': '25_91~CUW~28_24#MGNP'} Metrics: ['ELUC: -11.067110614906602', 'NSGA-II_crowding_distance: 0.47117622027112466', 'NSGA-II_rank: 3', 'change: 0.15458705366416253', 'is_elite: False']\n", + "Id: 29_97 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_65', '26_45'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_97', 'origin': '28_65~CUW~26_45#MGNP'} Metrics: ['ELUC: -11.313364556640638', 'NSGA-II_crowding_distance: 0.16627888093056387', 'NSGA-II_rank: 2', 'change: 0.15319637638435707', 'is_elite: False']\n", + "Id: 29_33 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_35', '28_24'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_33', 'origin': '28_35~CUW~28_24#MGNP'} Metrics: ['ELUC: -11.400643054851683', 'NSGA-II_crowding_distance: 0.24517469482884968', 'NSGA-II_rank: 1', 'change: 0.13791764305325674', 'is_elite: True']\n", + "Id: 29_81 Identity: {'ancestor_count': 23, 'ancestor_ids': ['2_49', '27_19'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_81', 'origin': '2_49~CUW~27_19#MGNP'} Metrics: ['ELUC: -11.69300603482804', 'NSGA-II_crowding_distance: 0.6689863376817362', 'NSGA-II_rank: 4', 'change: 0.28236075204953354', 'is_elite: False']\n", + "Id: 29_61 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_94', '28_65'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_61', 'origin': '28_94~CUW~28_65#MGNP'} Metrics: ['ELUC: -11.794282392007592', 'NSGA-II_crowding_distance: 0.8603738259817543', 'NSGA-II_rank: 3', 'change: 0.23948808374456274', 'is_elite: False']\n", + "Id: 29_98 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_65', '28_41'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_98', 'origin': '28_65~CUW~28_41#MGNP'} Metrics: ['ELUC: -11.85060654645169', 'NSGA-II_crowding_distance: 0.11894638023903653', 'NSGA-II_rank: 2', 'change: 0.1618745830211499', 'is_elite: False']\n", + "Id: 29_30 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_16', '28_65'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_30', 'origin': '28_16~CUW~28_65#MGNP'} Metrics: ['ELUC: -12.4127492760465', 'NSGA-II_crowding_distance: 0.12227112809668961', 'NSGA-II_rank: 2', 'change: 0.16547303462264962', 'is_elite: False']\n", + "Id: 29_73 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_12', '28_65'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_73', 'origin': '28_12~CUW~28_65#MGNP'} Metrics: ['ELUC: -12.471296911657467', 'NSGA-II_crowding_distance: 0.6800577288976464', 'NSGA-II_rank: 2', 'change: 0.18295063453841176', 'is_elite: False']\n", + "Id: 29_67 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_16', '28_62'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_67', 'origin': '28_16~CUW~28_62#MGNP'} Metrics: ['ELUC: -12.562624525270907', 'NSGA-II_crowding_distance: 0.17552436848644842', 'NSGA-II_rank: 1', 'change: 0.1613612419705449', 'is_elite: False']\n", + "Id: 29_52 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_75', '26_45'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_52', 'origin': '28_75~CUW~26_45#MGNP'} Metrics: ['ELUC: -12.903570687453124', 'NSGA-II_crowding_distance: 0.09388718910317054', 'NSGA-II_rank: 1', 'change: 0.16478505785976189', 'is_elite: False']\n", + "Id: 29_22 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_45', '26_45'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_22', 'origin': '26_45~CUW~26_45#MGNP'} Metrics: ['ELUC: -13.309471713392991', 'NSGA-II_crowding_distance: 0.07506777861835229', 'NSGA-II_rank: 1', 'change: 0.17670085992731824', 'is_elite: False']\n", + "Id: 29_53 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_45', '28_75'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_53', 'origin': '26_45~CUW~28_75#MGNP'} Metrics: ['ELUC: -13.421566041690252', 'NSGA-II_crowding_distance: 0.14668914961777732', 'NSGA-II_rank: 1', 'change: 0.1783930692760348', 'is_elite: False']\n", + "Id: 29_76 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_34', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_76', 'origin': '28_34~CUW~28_16#MGNP'} Metrics: ['ELUC: -14.423803386977848', 'NSGA-II_crowding_distance: 0.1861933602164838', 'NSGA-II_rank: 1', 'change: 0.20155908121163876', 'is_elite: False']\n", + "Id: 29_91 Identity: {'ancestor_count': 22, 'ancestor_ids': ['25_23', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_91', 'origin': '25_23~CUW~28_16#MGNP'} Metrics: ['ELUC: -14.797654393606472', 'NSGA-II_crowding_distance: 0.07448284165009168', 'NSGA-II_rank: 1', 'change: 0.21059637513062524', 'is_elite: False']\n", + "Id: 29_43 Identity: {'ancestor_count': 22, 'ancestor_ids': ['28_16', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_43', 'origin': '28_16~CUW~28_16#MGNP'} Metrics: ['ELUC: -14.854006384500883', 'NSGA-II_crowding_distance: 0.04971260124847486', 'NSGA-II_rank: 1', 'change: 0.21648242382048893', 'is_elite: False']\n", + "Id: 28_16 Identity: {'ancestor_count': 21, 'ancestor_ids': ['22_40', '25_23'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_16', 'origin': '22_40~CUW~25_23#MGNP'} Metrics: ['ELUC: -15.048037241462824', 'NSGA-II_crowding_distance: 0.042576225015175134', 'NSGA-II_rank: 1', 'change: 0.22118043337860718', 'is_elite: False']\n", + "Id: 29_57 Identity: {'ancestor_count': 22, 'ancestor_ids': ['28_16', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_57', 'origin': '28_16~CUW~28_16#MGNP'} Metrics: ['ELUC: -15.149501618737311', 'NSGA-II_crowding_distance: 0.21243605145008781', 'NSGA-II_rank: 1', 'change: 0.22417157534001816', 'is_elite: True']\n", + "Id: 29_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_54', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.185193875933583', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.31580578985537905', 'is_elite: False']\n", + "Id: 29_20 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_94', '28_94'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_20', 'origin': '28_94~CUW~28_94#MGNP'} Metrics: ['ELUC: -15.970139583571491', 'NSGA-II_crowding_distance: 0.21156362482679908', 'NSGA-II_rank: 1', 'change: 0.26891825595279273', 'is_elite: True']\n", + "Id: 29_35 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_84', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_35', 'origin': '28_84~CUW~28_16#MGNP'} Metrics: ['ELUC: -16.026096077485164', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.28438787117372516', 'is_elite: False']\n", + "Id: 29_49 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_41', '28_84'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_49', 'origin': '28_41~CUW~28_84#MGNP'} Metrics: ['ELUC: -16.123733366531514', 'NSGA-II_crowding_distance: 0.0325141609891236', 'NSGA-II_rank: 1', 'change: 0.270764433173299', 'is_elite: False']\n", + "Id: 29_63 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_94', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_63', 'origin': '28_94~CUW~28_16#MGNP'} Metrics: ['ELUC: -16.249562726082644', 'NSGA-II_crowding_distance: 0.7188170559670618', 'NSGA-II_rank: 2', 'change: 0.2763112576831477', 'is_elite: False']\n", + "Id: 28_94 Identity: {'ancestor_count': 26, 'ancestor_ids': ['27_81', '27_16'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_94', 'origin': '27_81~CUW~27_16#MGNP'} Metrics: ['ELUC: -16.324831648431285', 'NSGA-II_crowding_distance: 0.07794496580337744', 'NSGA-II_rank: 1', 'change: 0.27260052334811824', 'is_elite: False']\n", + "Id: 29_94 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_84', '2_49'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_94', 'origin': '28_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.521763345985363', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3001893705296033', 'is_elite: False']\n", + "Id: 29_65 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_94', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_65', 'origin': '28_94~CUW~28_16#MGNP'} Metrics: ['ELUC: -16.672023500464125', 'NSGA-II_crowding_distance: 0.17224307266137587', 'NSGA-II_rank: 1', 'change: 0.28471682137835325', 'is_elite: False']\n", + "Id: 29_23 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_84', '28_12'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_23', 'origin': '28_84~CUW~28_12#MGNP'} Metrics: ['ELUC: -17.580102154220995', 'NSGA-II_crowding_distance: 0.11397413454635794', 'NSGA-II_rank: 1', 'change: 0.30269169036811394', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 28_84 Identity: {'ancestor_count': 22, 'ancestor_ids': ['2_49', '27_18'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_84', 'origin': '2_49~CUW~27_18#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 29_27 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_45', '28_84'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_27', 'origin': '26_45~CUW~28_84#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 29_71 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_84', '2_49'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_71', 'origin': '28_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 29.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 30...:\n", + "PopulationResponse:\n", + " Generation: 30\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/30/20240219-231632\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 30 and asking ESP for generation 31...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 30 data persisted.\n", + "Evaluated candidates:\n", + "Id: 30_27 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_27', 'origin': '2_49~CUW~29_33#MGNP'} Metrics: ['ELUC: 18.45721744838962', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.29272792428822914', 'is_elite: False']\n", + "Id: 30_64 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_87', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_64', 'origin': '29_87~CUW~29_20#MGNP'} Metrics: ['ELUC: 14.624570840399878', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23773710065875153', 'is_elite: False']\n", + "Id: 30_45 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_45', 'origin': '29_87~CUW~29_71#MGNP'} Metrics: ['ELUC: 13.64609385575444', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24741373139001585', 'is_elite: False']\n", + "Id: 30_41 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_41', 'origin': '2_49~CUW~29_33#MGNP'} Metrics: ['ELUC: 13.493696166670777', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30705179702603047', 'is_elite: False']\n", + "Id: 30_55 Identity: {'ancestor_count': 28, 'ancestor_ids': ['28_83', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_55', 'origin': '28_83~CUW~29_20#MGNP'} Metrics: ['ELUC: 8.049578567051253', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.14799947017838705', 'is_elite: False']\n", + "Id: 30_19 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_17', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_19', 'origin': '29_17~CUW~29_20#MGNP'} Metrics: ['ELUC: 2.207889181725323', 'NSGA-II_crowding_distance: 1.3014348205322879', 'NSGA-II_rank: 6', 'change: 0.1612385775432265', 'is_elite: False']\n", + "Id: 30_39 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_39', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.970165314198515', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.030430650544502506', 'is_elite: False']\n", + "Id: 30_99 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_99', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.07446147395988596', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.026783698376898927', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 30_94 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '25_91'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_94', 'origin': '29_87~CUW~25_91#MGNP'} Metrics: ['ELUC: -0.30711348617582057', 'NSGA-II_crowding_distance: 0.2895913333185616', 'NSGA-II_rank: 3', 'change: 0.055547111793036806', 'is_elite: False']\n", + "Id: 30_22 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '29_87'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_22', 'origin': '2_49~CUW~29_87#MGNP'} Metrics: ['ELUC: -0.7656766436060831', 'NSGA-II_crowding_distance: 1.2894409549861259', 'NSGA-II_rank: 8', 'change: 0.26620254386767095', 'is_elite: False']\n", + "Id: 30_77 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_69', '29_17'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_77', 'origin': '26_69~CUW~29_17#MGNP'} Metrics: ['ELUC: -1.235493316151649', 'NSGA-II_crowding_distance: 0.19471667791705993', 'NSGA-II_rank: 2', 'change: 0.044018699361912744', 'is_elite: False']\n", + "Id: 30_57 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_83', '26_69'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_57', 'origin': '28_83~CUW~26_69#MGNP'} Metrics: ['ELUC: -1.9062709095560815', 'NSGA-II_crowding_distance: 0.09654299613064027', 'NSGA-II_rank: 2', 'change: 0.049607026932955496', 'is_elite: False']\n", + "Id: 30_51 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_51', 'origin': '29_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0794331031229296', 'NSGA-II_crowding_distance: 0.22529433635127227', 'NSGA-II_rank: 3', 'change: 0.06092262245955501', 'is_elite: False']\n", + "Id: 30_54 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_54', 'origin': '29_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.1716069880474698', 'NSGA-II_crowding_distance: 0.04622848520816208', 'NSGA-II_rank: 2', 'change: 0.05605324439425048', 'is_elite: False']\n", + "Id: 30_86 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_50', '25_91'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_86', 'origin': '29_50~CUW~25_91#MGNP'} Metrics: ['ELUC: -2.209144010744184', 'NSGA-II_crowding_distance: 0.06369039386168227', 'NSGA-II_rank: 2', 'change: 0.05764219539457125', 'is_elite: False']\n", + "Id: 26_69 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_69', 'origin': '23_59~CUW~23_59#MGNP'} Metrics: ['ELUC: -2.3593292124774066', 'NSGA-II_crowding_distance: 0.3306750355215595', 'NSGA-II_rank: 1', 'change: 0.04257255541510991', 'is_elite: True']\n", + "Id: 30_13 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_67', '29_17'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_13', 'origin': '29_67~CUW~29_17#MGNP'} Metrics: ['ELUC: -2.4081846220483887', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11652646482009105', 'is_elite: False']\n", + "Id: 30_72 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_76', '26_69'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_72', 'origin': '29_76~CUW~26_69#MGNP'} Metrics: ['ELUC: -2.451178213035894', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09772940664650794', 'is_elite: False']\n", + "Id: 30_20 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '26_69'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_20', 'origin': '29_87~CUW~26_69#MGNP'} Metrics: ['ELUC: -2.8179924488777663', 'NSGA-II_crowding_distance: 0.10800834864490923', 'NSGA-II_rank: 1', 'change: 0.055741972007641125', 'is_elite: False']\n", + "Id: 30_92 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_83', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_92', 'origin': '28_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.850643756715517', 'NSGA-II_crowding_distance: 0.09680190970903704', 'NSGA-II_rank: 2', 'change: 0.06303157430985998', 'is_elite: False']\n", + "Id: 30_16 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '26_69'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_16', 'origin': '1_1~CUW~26_69#MGNP'} Metrics: ['ELUC: -3.4274399540177343', 'NSGA-II_crowding_distance: 0.44225534029257985', 'NSGA-II_rank: 3', 'change: 0.0675741677334265', 'is_elite: False']\n", + "Id: 29_17 Identity: {'ancestor_count': 21, 'ancestor_ids': ['25_23', '1_1'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_17', 'origin': '25_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.4725484198808614', 'NSGA-II_crowding_distance: 0.061951543021049923', 'NSGA-II_rank: 1', 'change: 0.05590816660896231', 'is_elite: False']\n", + "Id: 30_61 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '29_87'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_61', 'origin': '1_1~CUW~29_87#MGNP'} Metrics: ['ELUC: -3.5080763821342864', 'NSGA-II_crowding_distance: 0.11723525774625092', 'NSGA-II_rank: 2', 'change: 0.06407647678206813', 'is_elite: False']\n", + "Id: 30_46 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '26_69'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_46', 'origin': '1_1~CUW~26_69#MGNP'} Metrics: ['ELUC: -3.6607448300814522', 'NSGA-II_crowding_distance: 0.0451458158775125', 'NSGA-II_rank: 1', 'change: 0.05992516419792237', 'is_elite: False']\n", + "Id: 30_80 Identity: {'ancestor_count': 24, 'ancestor_ids': ['25_91', '28_83'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_80', 'origin': '25_91~CUW~28_83#MGNP'} Metrics: ['ELUC: -3.7140151973978455', 'NSGA-II_crowding_distance: 0.2648885820363752', 'NSGA-II_rank: 2', 'change: 0.08191915934940215', 'is_elite: False']\n", + "Id: 30_90 Identity: {'ancestor_count': 22, 'ancestor_ids': ['26_69', '29_17'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_90', 'origin': '26_69~CUW~29_17#MGNP'} Metrics: ['ELUC: -3.91813828122472', 'NSGA-II_crowding_distance: 0.04387350237023344', 'NSGA-II_rank: 1', 'change: 0.061816874700518984', 'is_elite: False']\n", + "Id: 30_88 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_19', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_88', 'origin': '29_19~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.171611711804795', 'NSGA-II_crowding_distance: 0.05484786506079984', 'NSGA-II_rank: 1', 'change: 0.06434647114109335', 'is_elite: False']\n", + "Id: 30_21 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_76', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_21', 'origin': '29_76~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.329372248255834', 'NSGA-II_crowding_distance: 1.1474889625484024', 'NSGA-II_rank: 5', 'change: 0.13178435975445535', 'is_elite: False']\n", + "Id: 29_87 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_69', '28_83'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_87', 'origin': '26_69~CUW~28_83#MGNP'} Metrics: ['ELUC: -4.546166374002797', 'NSGA-II_crowding_distance: 0.12380531295109387', 'NSGA-II_rank: 1', 'change: 0.06752442504308302', 'is_elite: False']\n", + "Id: 30_33 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '29_57'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_33', 'origin': '29_87~CUW~29_57#MGNP'} Metrics: ['ELUC: -5.023956756161473', 'NSGA-II_crowding_distance: 0.9710604982509274', 'NSGA-II_rank: 4', 'change: 0.1285544775617392', 'is_elite: False']\n", + "Id: 30_85 Identity: {'ancestor_count': 28, 'ancestor_ids': ['1_1', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_85', 'origin': '1_1~CUW~29_20#MGNP'} Metrics: ['ELUC: -5.271794729746102', 'NSGA-II_crowding_distance: 1.2076483638435058', 'NSGA-II_rank: 6', 'change: 0.2208869882169765', 'is_elite: False']\n", + "Id: 30_62 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_69', '28_83'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_62', 'origin': '26_69~CUW~28_83#MGNP'} Metrics: ['ELUC: -5.557735349736976', 'NSGA-II_crowding_distance: 0.11733121660761316', 'NSGA-II_rank: 1', 'change: 0.07776427215221245', 'is_elite: False']\n", + "Id: 30_15 Identity: {'ancestor_count': 24, 'ancestor_ids': ['26_69', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_15', 'origin': '26_69~CUW~29_71#MGNP'} Metrics: ['ELUC: -5.689981948509016', 'NSGA-II_crowding_distance: 1.519723616907036', 'NSGA-II_rank: 7', 'change: 0.2470476432565163', 'is_elite: False']\n", + "Id: 30_60 Identity: {'ancestor_count': 25, 'ancestor_ids': ['28_65', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_60', 'origin': '28_65~CUW~29_14#MGNP'} Metrics: ['ELUC: -5.7255775639300035', 'NSGA-II_crowding_distance: 0.31699370225371054', 'NSGA-II_rank: 2', 'change: 0.10258232410422856', 'is_elite: False']\n", + "Id: 28_83 Identity: {'ancestor_count': 23, 'ancestor_ids': ['27_19', '25_91'], 'birth_generation': 28, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '28_83', 'origin': '27_19~CUW~25_91#MGNP'} Metrics: ['ELUC: -5.7752944116200995', 'NSGA-II_crowding_distance: 0.09571516392270729', 'NSGA-II_rank: 1', 'change: 0.08167476370294353', 'is_elite: False']\n", + "Id: 30_11 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '29_53'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_11', 'origin': '1_1~CUW~29_53#MGNP'} Metrics: ['ELUC: -6.00078576526195', 'NSGA-II_crowding_distance: 0.5407694855513082', 'NSGA-II_rank: 3', 'change: 0.11899759547196048', 'is_elite: False']\n", + "Id: 30_71 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_17'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_71', 'origin': '29_14~CUW~29_17#MGNP'} Metrics: ['ELUC: -6.0227260600822', 'NSGA-II_crowding_distance: 0.12613869119073848', 'NSGA-II_rank: 1', 'change: 0.09843250834454512', 'is_elite: False']\n", + "Id: 30_84 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_84', 'origin': '1_1~CUW~29_14#MGNP'} Metrics: ['ELUC: -6.705433220844791', 'NSGA-II_crowding_distance: 0.18504100490893374', 'NSGA-II_rank: 1', 'change: 0.10352699584300033', 'is_elite: True']\n", + "Id: 30_58 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_83', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_58', 'origin': '28_83~CUW~29_71#MGNP'} Metrics: ['ELUC: -6.773641871528043', 'NSGA-II_crowding_distance: 0.9402608579125422', 'NSGA-II_rank: 8', 'change: 0.26946266375222716', 'is_elite: False']\n", + "Id: 30_28 Identity: {'ancestor_count': 25, 'ancestor_ids': ['25_91', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_28', 'origin': '25_91~CUW~29_33#MGNP'} Metrics: ['ELUC: -7.308786233511654', 'NSGA-II_crowding_distance: 0.3444828192811783', 'NSGA-II_rank: 3', 'change: 0.1528715164415855', 'is_elite: False']\n", + "Id: 30_48 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_33', '29_87'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_48', 'origin': '29_33~CUW~29_87#MGNP'} Metrics: ['ELUC: -7.36537189750733', 'NSGA-II_crowding_distance: 0.32312832928670093', 'NSGA-II_rank: 2', 'change: 0.11240334998913504', 'is_elite: False']\n", + "Id: 30_47 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_20', '29_17'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_47', 'origin': '29_20~CUW~29_17#MGNP'} Metrics: ['ELUC: -7.486868036339868', 'NSGA-II_crowding_distance: 1.127434997369083', 'NSGA-II_rank: 5', 'change: 0.21385639670718684', 'is_elite: False']\n", + "Id: 30_59 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '2_49'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_59', 'origin': '29_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.963828273409268', 'NSGA-II_crowding_distance: 0.7672563607479214', 'NSGA-II_rank: 7', 'change: 0.2634439924530155', 'is_elite: False']\n", + "Id: 30_89 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_89', 'origin': '29_14~CUW~29_14#MGNP'} Metrics: ['ELUC: -8.511797071769356', 'NSGA-II_crowding_distance: 0.30986657315727517', 'NSGA-II_rank: 1', 'change: 0.11140431833454958', 'is_elite: True']\n", + "Id: 30_67 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_57', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_67', 'origin': '29_57~CUW~29_71#MGNP'} Metrics: ['ELUC: -8.6843323076118', 'NSGA-II_crowding_distance: 0.7105590450138739', 'NSGA-II_rank: 8', 'change: 0.29971932911205157', 'is_elite: False']\n", + "Id: 30_76 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '2_49'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_76', 'origin': '29_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.025888537480181', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3041266496144325', 'is_elite: False']\n", + "Id: 30_42 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_76', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_42', 'origin': '29_76~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.318332917406657', 'NSGA-II_crowding_distance: 0.2869921596023529', 'NSGA-II_rank: 2', 'change: 0.13567719228859454', 'is_elite: False']\n", + "Id: 30_30 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_17', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_30', 'origin': '29_17~CUW~29_33#MGNP'} Metrics: ['ELUC: -9.428112403588232', 'NSGA-II_crowding_distance: 0.28061296743501135', 'NSGA-II_rank: 3', 'change: 0.15840195206047938', 'is_elite: False']\n", + "Id: 30_40 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_57', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_40', 'origin': '29_57~CUW~29_20#MGNP'} Metrics: ['ELUC: -9.530259961521931', 'NSGA-II_crowding_distance: 0.500974306697511', 'NSGA-II_rank: 5', 'change: 0.2233482098128919', 'is_elite: False']\n", + "Id: 30_83 Identity: {'ancestor_count': 23, 'ancestor_ids': ['29_57', '29_17'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_83', 'origin': '29_57~CUW~29_17#MGNP'} Metrics: ['ELUC: -9.655559327925541', 'NSGA-II_crowding_distance: 0.8044720463887545', 'NSGA-II_rank: 4', 'change: 0.17626505762576702', 'is_elite: False']\n", + "Id: 30_23 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_20', '29_67'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_23', 'origin': '29_20~CUW~29_67#MGNP'} Metrics: ['ELUC: -9.771131614446244', 'NSGA-II_crowding_distance: 0.42019356254938856', 'NSGA-II_rank: 6', 'change: 0.23131281477375387', 'is_elite: False']\n", + "Id: 30_25 Identity: {'ancestor_count': 24, 'ancestor_ids': ['2_49', '28_83'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_25', 'origin': '2_49~CUW~28_83#MGNP'} Metrics: ['ELUC: -10.04557771158969', 'NSGA-II_crowding_distance: 0.40556577502078023', 'NSGA-II_rank: 7', 'change: 0.27169438991709055', 'is_elite: False']\n", + "Id: 30_95 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_95', 'origin': '2_49~CUW~29_14#MGNP'} Metrics: ['ELUC: -10.338661090866001', 'NSGA-II_crowding_distance: 0.1985725376796884', 'NSGA-II_rank: 7', 'change: 0.2763520566929263', 'is_elite: False']\n", + "Id: 30_38 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_76', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_38', 'origin': '29_76~CUW~29_71#MGNP'} Metrics: ['ELUC: -10.457203064592347', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.279257861763978', 'is_elite: False']\n", + "Id: 30_70 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_33', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_70', 'origin': '29_33~CUW~29_33#MGNP'} Metrics: ['ELUC: -10.523748258410913', 'NSGA-II_crowding_distance: 0.2531621085033982', 'NSGA-II_rank: 1', 'change: 0.13118629283280353', 'is_elite: True']\n", + "Id: 30_97 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_87', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_97', 'origin': '29_87~CUW~29_20#MGNP'} Metrics: ['ELUC: -10.799801214724177', 'NSGA-II_crowding_distance: 0.3759967188300977', 'NSGA-II_rank: 6', 'change: 0.23659288049269245', 'is_elite: False']\n", + "Id: 30_56 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_50', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_56', 'origin': '29_50~CUW~29_33#MGNP'} Metrics: ['ELUC: -10.800436959388344', 'NSGA-II_crowding_distance: 0.2783340283435987', 'NSGA-II_rank: 2', 'change: 0.13798130527758284', 'is_elite: False']\n", + "Id: 30_44 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_44', 'origin': '29_14~CUW~29_71#MGNP'} Metrics: ['ELUC: -10.965330494797433', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2693048680692779', 'is_elite: False']\n", + "Id: 30_53 Identity: {'ancestor_count': 25, 'ancestor_ids': ['28_83', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_53', 'origin': '28_83~CUW~29_33#MGNP'} Metrics: ['ELUC: -11.11186415329148', 'NSGA-II_crowding_distance: 0.25603909947366754', 'NSGA-II_rank: 3', 'change: 0.16915613102620722', 'is_elite: False']\n", + "Id: 30_43 Identity: {'ancestor_count': 28, 'ancestor_ids': ['1_1', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_43', 'origin': '1_1~CUW~29_20#MGNP'} Metrics: ['ELUC: -11.167765893245432', 'NSGA-II_crowding_distance: 0.5652361185860324', 'NSGA-II_rank: 5', 'change: 0.22814567132132207', 'is_elite: False']\n", + "Id: 30_93 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_71', '25_91'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_93', 'origin': '29_71~CUW~25_91#MGNP'} Metrics: ['ELUC: -11.235881228254616', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2866311843344641', 'is_elite: False']\n", + "Id: 30_74 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_57', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_74', 'origin': '29_57~CUW~29_14#MGNP'} Metrics: ['ELUC: -11.282061965512076', 'NSGA-II_crowding_distance: 1.0289395017490726', 'NSGA-II_rank: 4', 'change: 0.1889487407892721', 'is_elite: False']\n", + "Id: 29_33 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_35', '28_24'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_33', 'origin': '28_35~CUW~28_24#MGNP'} Metrics: ['ELUC: -11.400643054851683', 'NSGA-II_crowding_distance: 0.08047394612957245', 'NSGA-II_rank: 1', 'change: 0.13791764305325674', 'is_elite: False']\n", + "Id: 30_98 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_33', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_98', 'origin': '29_33~CUW~29_33#MGNP'} Metrics: ['ELUC: -11.468117414545226', 'NSGA-II_crowding_distance: 0.13942066355021107', 'NSGA-II_rank: 1', 'change: 0.13917168934170235', 'is_elite: False']\n", + "Id: 30_18 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_18', 'origin': '29_14~CUW~29_33#MGNP'} Metrics: ['ELUC: -12.065109574429844', 'NSGA-II_crowding_distance: 0.3447251947165739', 'NSGA-II_rank: 3', 'change: 0.18628805137606638', 'is_elite: False']\n", + "Id: 30_32 Identity: {'ancestor_count': 28, 'ancestor_ids': ['1_1', '29_67'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_32', 'origin': '1_1~CUW~29_67#MGNP'} Metrics: ['ELUC: -12.249266138858049', 'NSGA-II_crowding_distance: 0.31380129064468665', 'NSGA-II_rank: 2', 'change: 0.1667443529390324', 'is_elite: False']\n", + "Id: 30_34 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_67', '29_76'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_34', 'origin': '29_67~CUW~29_76#MGNP'} Metrics: ['ELUC: -12.3040503172611', 'NSGA-II_crowding_distance: 0.17374231783813163', 'NSGA-II_rank: 1', 'change: 0.16418656233555365', 'is_elite: True']\n", + "Id: 30_17 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_57', '29_87'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_17', 'origin': '29_57~CUW~29_87#MGNP'} Metrics: ['ELUC: -12.493582305197675', 'NSGA-II_crowding_distance: 0.11986058264524024', 'NSGA-II_rank: 1', 'change: 0.17361006981840196', 'is_elite: False']\n", + "Id: 30_91 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_20', '29_53'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_91', 'origin': '29_20~CUW~29_53#MGNP'} Metrics: ['ELUC: -12.550848973877242', 'NSGA-II_crowding_distance: 0.45112612735344276', 'NSGA-II_rank: 3', 'change: 0.2397208704464115', 'is_elite: False']\n", + "Id: 30_82 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '29_57'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_82', 'origin': '29_87~CUW~29_57#MGNP'} Metrics: ['ELUC: -13.414714051385973', 'NSGA-II_crowding_distance: 0.6508160254258886', 'NSGA-II_rank: 2', 'change: 0.18379585203295912', 'is_elite: False']\n", + "Id: 30_14 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_57', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_14', 'origin': '29_57~CUW~29_33#MGNP'} Metrics: ['ELUC: -13.466775456623333', 'NSGA-II_crowding_distance: 0.15841106453742465', 'NSGA-II_rank: 1', 'change: 0.18021848509915964', 'is_elite: False']\n", + "Id: 30_69 Identity: {'ancestor_count': 23, 'ancestor_ids': ['2_49', '29_57'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_69', 'origin': '2_49~CUW~29_57#MGNP'} Metrics: ['ELUC: -13.675758602928699', 'NSGA-II_crowding_distance: 0.3317558323134687', 'NSGA-II_rank: 3', 'change: 0.28289419333611837', 'is_elite: False']\n", + "Id: 30_87 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_57', '29_67'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_87', 'origin': '29_57~CUW~29_67#MGNP'} Metrics: ['ELUC: -13.850975043766786', 'NSGA-II_crowding_distance: 0.11489373209998155', 'NSGA-II_rank: 1', 'change: 0.19784102810813314', 'is_elite: False']\n", + "Id: 30_37 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_33', '29_76'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_37', 'origin': '29_33~CUW~29_76#MGNP'} Metrics: ['ELUC: -14.244622105630075', 'NSGA-II_crowding_distance: 0.16209971805345888', 'NSGA-II_rank: 1', 'change: 0.20129991693794547', 'is_elite: False']\n", + "Id: 30_65 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_71', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_65', 'origin': '29_71~CUW~29_14#MGNP'} Metrics: ['ELUC: -14.888402228975929', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.29817725297982745', 'is_elite: False']\n", + "Id: 30_68 Identity: {'ancestor_count': 24, 'ancestor_ids': ['2_49', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_68', 'origin': '2_49~CUW~29_71#MGNP'} Metrics: ['ELUC: -14.934189448661835', 'NSGA-II_crowding_distance: 0.1560002925775325', 'NSGA-II_rank: 3', 'change: 0.29201572613576504', 'is_elite: False']\n", + "Id: 29_57 Identity: {'ancestor_count': 22, 'ancestor_ids': ['28_16', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_57', 'origin': '28_16~CUW~28_16#MGNP'} Metrics: ['ELUC: -15.149501618737311', 'NSGA-II_crowding_distance: 0.32475918172441437', 'NSGA-II_rank: 1', 'change: 0.22417157534001816', 'is_elite: True']\n", + "Id: 30_50 Identity: {'ancestor_count': 21, 'ancestor_ids': ['2_49', '26_69'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_50', 'origin': '2_49~CUW~26_69#MGNP'} Metrics: ['ELUC: -15.389595265886516', 'NSGA-II_crowding_distance: 0.10982405111484515', 'NSGA-II_rank: 3', 'change: 0.29820890349703183', 'is_elite: False']\n", + "Id: 29_20 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_94', '28_94'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_20', 'origin': '28_94~CUW~28_94#MGNP'} Metrics: ['ELUC: -15.970139583571491', 'NSGA-II_crowding_distance: 0.25593091784544725', 'NSGA-II_rank: 1', 'change: 0.26891825595279273', 'is_elite: True']\n", + "Id: 30_78 Identity: {'ancestor_count': 24, 'ancestor_ids': ['2_49', '28_83'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_78', 'origin': '2_49~CUW~28_83#MGNP'} Metrics: ['ELUC: -16.293415875479006', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30040944919813684', 'is_elite: False']\n", + "Id: 30_26 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_65', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_26', 'origin': '29_65~CUW~29_20#MGNP'} Metrics: ['ELUC: -16.556990018501025', 'NSGA-II_crowding_distance: 0.6682185278174791', 'NSGA-II_rank: 2', 'change: 0.27918070680640356', 'is_elite: False']\n", + "Id: 30_31 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_33', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_31', 'origin': '29_33~CUW~29_20#MGNP'} Metrics: ['ELUC: -16.642456084146737', 'NSGA-II_crowding_distance: 0.13621718992346155', 'NSGA-II_rank: 1', 'change: 0.27519976028552146', 'is_elite: False']\n", + "Id: 30_49 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_20', '29_76'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_49', 'origin': '29_20~CUW~29_76#MGNP'} Metrics: ['ELUC: -17.13808790245649', 'NSGA-II_crowding_distance: 0.14439055861898914', 'NSGA-II_rank: 1', 'change: 0.2897419868448503', 'is_elite: False']\n", + "Id: 30_63 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_71', '26_69'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_63', 'origin': '29_71~CUW~26_69#MGNP'} Metrics: ['ELUC: -17.560280444607503', 'NSGA-II_crowding_distance: 0.07048941387190391', 'NSGA-II_rank: 1', 'change: 0.30270692290229556', 'is_elite: False']\n", + "Id: 30_35 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_71', '29_20'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_35', 'origin': '29_71~CUW~29_20#MGNP'} Metrics: ['ELUC: -17.595694502059782', 'NSGA-II_crowding_distance: 0.003135805295259418', 'NSGA-II_rank: 1', 'change: 0.30300873202852124', 'is_elite: False']\n", + "Id: 30_79 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_79', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.595926464982455', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030170553331864', 'is_elite: False']\n", + "Id: 30_81 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_71', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_81', 'origin': '29_71~CUW~29_14#MGNP'} Metrics: ['ELUC: -17.597154460135116', 'NSGA-II_crowding_distance: 0.00013556498581115685', 'NSGA-II_rank: 1', 'change: 0.3030168139121239', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 29_71 Identity: {'ancestor_count': 23, 'ancestor_ids': ['28_84', '2_49'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_71', 'origin': '28_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_12 Identity: {'ancestor_count': 24, 'ancestor_ids': ['2_49', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_12', 'origin': '2_49~CUW~29_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_24 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_71', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_24', 'origin': '29_71~CUW~29_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_29 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_71', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_29', 'origin': '29_71~CUW~29_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_36 Identity: {'ancestor_count': 24, 'ancestor_ids': ['28_83', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_36', 'origin': '28_83~CUW~29_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_52 Identity: {'ancestor_count': 25, 'ancestor_ids': ['2_49', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_52', 'origin': '2_49~CUW~29_33#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_66 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_87', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_66', 'origin': '29_87~CUW~29_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_73 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_71', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_73', 'origin': '29_71~CUW~29_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_75 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_65', '2_49'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_75', 'origin': '29_65~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_96 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_59', '29_71'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_96', 'origin': '29_59~CUW~29_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 30_100 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_71', '2_49'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_100', 'origin': '29_71~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 30.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 31...:\n", + "PopulationResponse:\n", + " Generation: 31\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/31/20240219-232344\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 31 and asking ESP for generation 32...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 31 data persisted.\n", + "Evaluated candidates:\n", + "Id: 31_51 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '30_100'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_51', 'origin': '1_1~CUW~30_100#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 31_60 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_34', '2_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_60', 'origin': '30_34~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.306946227132936', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.30082792297537825', 'is_elite: False']\n", + "Id: 31_94 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_37', '30_100'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_94', 'origin': '30_37~CUW~30_100#MGNP'} Metrics: ['ELUC: 20.31590903010759', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2982680698395163', 'is_elite: False']\n", + "Id: 31_76 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_100', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_76', 'origin': '30_100~CUW~30_84#MGNP'} Metrics: ['ELUC: 18.75371599658017', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3029405239581251', 'is_elite: False']\n", + "Id: 31_70 Identity: {'ancestor_count': 26, 'ancestor_ids': ['2_49', '30_89'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_70', 'origin': '2_49~CUW~30_89#MGNP'} Metrics: ['ELUC: 12.997465780830712', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2894845232203936', 'is_elite: False']\n", + "Id: 31_67 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_89', '29_20'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_67', 'origin': '30_89~CUW~29_20#MGNP'} Metrics: ['ELUC: 6.401731944577813', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.19964763651075249', 'is_elite: False']\n", + "Id: 31_23 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_84', '30_100'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_23', 'origin': '30_84~CUW~30_100#MGNP'} Metrics: ['ELUC: 5.695311406340679', 'NSGA-II_crowding_distance: 1.3538473023779347', 'NSGA-II_rank: 9', 'change: 0.2345312794489486', 'is_elite: False']\n", + "Id: 31_11 Identity: {'ancestor_count': 29, 'ancestor_ids': ['1_1', '30_31'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_11', 'origin': '1_1~CUW~30_31#MGNP'} Metrics: ['ELUC: 2.3375105256541233', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1659619911577414', 'is_elite: False']\n", + "Id: 31_66 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_100', '30_70'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_66', 'origin': '30_100~CUW~30_70#MGNP'} Metrics: ['ELUC: 2.0962144930134614', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.264414419985744', 'is_elite: False']\n", + "Id: 31_74 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_100', '30_34'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_74', 'origin': '30_100~CUW~30_34#MGNP'} Metrics: ['ELUC: 1.8839949203482829', 'NSGA-II_crowding_distance: 1.3700896663289852', 'NSGA-II_rank: 9', 'change: 0.248766650779463', 'is_elite: False']\n", + "Id: 31_93 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_93', 'origin': '1_1~CUW~26_69#MGNP'} Metrics: ['ELUC: 0.9899035371273779', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.044407579589200365', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 31_29 Identity: {'ancestor_count': 29, 'ancestor_ids': ['26_69', '30_31'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_29', 'origin': '26_69~CUW~30_31#MGNP'} Metrics: ['ELUC: -0.30172796540537755', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.19449589031711906', 'is_elite: False']\n", + "Id: 31_68 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '1_1'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_68', 'origin': '30_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5354923754016976', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08641250784879381', 'is_elite: False']\n", + "Id: 31_54 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '2_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_54', 'origin': '30_89~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 1.4658299571489382', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 31_80 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_80', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.5341700428510618', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 31_95 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_84', '30_70'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_95', 'origin': '30_84~CUW~30_70#MGNP'} Metrics: ['ELUC: -0.7083495073518755', 'NSGA-II_crowding_distance: 0.6722594169049336', 'NSGA-II_rank: 4', 'change: 0.11097399503266653', 'is_elite: False']\n", + "Id: 31_38 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '1_1'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_38', 'origin': '30_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7196731097520631', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05979373546151901', 'is_elite: False']\n", + "Id: 31_42 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '2_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_42', 'origin': '30_89~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.144153189351053', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2646934210080968', 'is_elite: False']\n", + "Id: 31_20 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_20', 'origin': '30_70~CUW~26_69#MGNP'} Metrics: ['ELUC: -1.3587321542056132', 'NSGA-II_crowding_distance: 0.27449965744677496', 'NSGA-II_rank: 2', 'change: 0.05798554632426342', 'is_elite: False']\n", + "Id: 31_73 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_98', '30_100'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_73', 'origin': '30_98~CUW~30_100#MGNP'} Metrics: ['ELUC: -1.8663185142816083', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2644199704742712', 'is_elite: False']\n", + "Id: 31_33 Identity: {'ancestor_count': 26, 'ancestor_ids': ['26_69', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_33', 'origin': '26_69~CUW~30_84#MGNP'} Metrics: ['ELUC: -2.1787109161684555', 'NSGA-II_crowding_distance: 0.17661475758671494', 'NSGA-II_rank: 2', 'change: 0.07030563461734704', 'is_elite: False']\n", + "Id: 26_69 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_69', 'origin': '23_59~CUW~23_59#MGNP'} Metrics: ['ELUC: -2.3593292124774066', 'NSGA-II_crowding_distance: 0.37085822609651575', 'NSGA-II_rank: 1', 'change: 0.04257255541510991', 'is_elite: True']\n", + "Id: 31_46 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_46', 'origin': '30_89~CUW~26_69#MGNP'} Metrics: ['ELUC: -3.433070011308265', 'NSGA-II_crowding_distance: 0.17784711495174868', 'NSGA-II_rank: 1', 'change: 0.05729368478603369', 'is_elite: False']\n", + "Id: 31_50 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_71', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_50', 'origin': '30_71~CUW~26_69#MGNP'} Metrics: ['ELUC: -3.572431570773956', 'NSGA-II_crowding_distance: 0.13705657090125162', 'NSGA-II_rank: 2', 'change: 0.07217865304209323', 'is_elite: False']\n", + "Id: 31_90 Identity: {'ancestor_count': 23, 'ancestor_ids': ['26_69', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_90', 'origin': '26_69~CUW~29_57#MGNP'} Metrics: ['ELUC: -3.928427280922282', 'NSGA-II_crowding_distance: 0.7164798843464', 'NSGA-II_rank: 3', 'change: 0.1129596352725161', 'is_elite: False']\n", + "Id: 31_72 Identity: {'ancestor_count': 26, 'ancestor_ids': ['1_1', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_72', 'origin': '1_1~CUW~30_84#MGNP'} Metrics: ['ELUC: -3.9689596802995175', 'NSGA-II_crowding_distance: 0.14997498538263004', 'NSGA-II_rank: 2', 'change: 0.08029828211250933', 'is_elite: False']\n", + "Id: 31_88 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_69', '30_62'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_88', 'origin': '26_69~CUW~30_62#MGNP'} Metrics: ['ELUC: -3.9875871831642833', 'NSGA-II_crowding_distance: 0.21518490674708507', 'NSGA-II_rank: 1', 'change: 0.06800613154290952', 'is_elite: True']\n", + "Id: 31_65 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_84', '29_20'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_65', 'origin': '30_84~CUW~29_20#MGNP'} Metrics: ['ELUC: -4.0719233403837745', 'NSGA-II_crowding_distance: 1.0660273610746638', 'NSGA-II_rank: 7', 'change: 0.17206082704308948', 'is_elite: False']\n", + "Id: 31_52 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_84', '30_37'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_52', 'origin': '30_84~CUW~30_37#MGNP'} Metrics: ['ELUC: -4.592636562026299', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.12417176061979981', 'is_elite: False']\n", + "Id: 31_48 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_48', 'origin': '1_1~CUW~26_69#MGNP'} Metrics: ['ELUC: -5.198279462625768', 'NSGA-II_crowding_distance: 0.12625429296874055', 'NSGA-II_rank: 2', 'change: 0.08781514774756816', 'is_elite: False']\n", + "Id: 31_40 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_84', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_40', 'origin': '30_84~CUW~26_69#MGNP'} Metrics: ['ELUC: -5.33119886403827', 'NSGA-II_crowding_distance: 0.10152777685896874', 'NSGA-II_rank: 2', 'change: 0.09355278342923537', 'is_elite: False']\n", + "Id: 31_14 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_84', '30_62'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_14', 'origin': '30_84~CUW~30_62#MGNP'} Metrics: ['ELUC: -5.680154266198266', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.12098195052642444', 'is_elite: False']\n", + "Id: 31_57 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_87', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_57', 'origin': '29_87~CUW~30_84#MGNP'} Metrics: ['ELUC: -5.737747831221566', 'NSGA-II_crowding_distance: 0.2736248224298245', 'NSGA-II_rank: 1', 'change: 0.08238897259723696', 'is_elite: True']\n", + "Id: 31_100 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_87', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_100', 'origin': '29_87~CUW~30_84#MGNP'} Metrics: ['ELUC: -5.832432964926599', 'NSGA-II_crowding_distance: 0.11807903819260104', 'NSGA-II_rank: 2', 'change: 0.10498452251835133', 'is_elite: False']\n", + "Id: 31_39 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_89', '30_31'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_39', 'origin': '30_89~CUW~30_31#MGNP'} Metrics: ['ELUC: -6.065515230492021', 'NSGA-II_crowding_distance: 1.6656181004793431', 'NSGA-II_rank: 6', 'change: 0.1825073540668303', 'is_elite: False']\n", + "Id: 31_19 Identity: {'ancestor_count': 26, 'ancestor_ids': ['1_1', '30_14'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_19', 'origin': '1_1~CUW~30_14#MGNP'} Metrics: ['ELUC: -6.39603589763494', 'NSGA-II_crowding_distance: 0.16549346642381255', 'NSGA-II_rank: 2', 'change: 0.10890159230050865', 'is_elite: False']\n", + "Id: 30_84 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_84', 'origin': '1_1~CUW~29_14#MGNP'} Metrics: ['ELUC: -6.705433220844791', 'NSGA-II_crowding_distance: 0.255018429851977', 'NSGA-II_rank: 1', 'change: 0.10352699584300033', 'is_elite: True']\n", + "Id: 31_26 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_37', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_26', 'origin': '30_37~CUW~26_69#MGNP'} Metrics: ['ELUC: -6.957842657241533', 'NSGA-II_crowding_distance: 0.6671535047870885', 'NSGA-II_rank: 4', 'change: 0.11660418894145146', 'is_elite: False']\n", + "Id: 31_49 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_49', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_49', 'origin': '30_49~CUW~29_57#MGNP'} Metrics: ['ELUC: -7.143338736762406', 'NSGA-II_crowding_distance: 0.7918999478761068', 'NSGA-II_rank: 7', 'change: 0.2021878714486507', 'is_elite: False']\n", + "Id: 31_18 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '30_71'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_18', 'origin': '30_89~CUW~30_71#MGNP'} Metrics: ['ELUC: -7.1866693726541016', 'NSGA-II_crowding_distance: 0.395569577678974', 'NSGA-II_rank: 3', 'change: 0.11538779375477846', 'is_elite: False']\n", + "Id: 31_32 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_84', '29_20'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_32', 'origin': '30_84~CUW~29_20#MGNP'} Metrics: ['ELUC: -7.28325349408471', 'NSGA-II_crowding_distance: 0.9339726389253362', 'NSGA-II_rank: 7', 'change: 0.24233907182937078', 'is_elite: False']\n", + "Id: 31_55 Identity: {'ancestor_count': 26, 'ancestor_ids': ['1_1', '30_37'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_55', 'origin': '1_1~CUW~30_37#MGNP'} Metrics: ['ELUC: -7.606748283275318', 'NSGA-II_crowding_distance: 0.2620466692160737', 'NSGA-II_rank: 4', 'change: 0.1347120167383145', 'is_elite: False']\n", + "Id: 31_98 Identity: {'ancestor_count': 26, 'ancestor_ids': ['26_69', '30_98'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_98', 'origin': '26_69~CUW~30_98#MGNP'} Metrics: ['ELUC: -8.192321872551826', 'NSGA-II_crowding_distance: 1.056915510237428', 'NSGA-II_rank: 5', 'change: 0.14355420660499732', 'is_elite: False']\n", + "Id: 31_12 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_12', 'origin': '30_89~CUW~26_69#MGNP'} Metrics: ['ELUC: -8.19241916083638', 'NSGA-II_crowding_distance: 0.5626751356658145', 'NSGA-II_rank: 4', 'change: 0.14342127980308966', 'is_elite: False']\n", + "Id: 31_84 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '30_89'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_84', 'origin': '30_89~CUW~30_89#MGNP'} Metrics: ['ELUC: -8.260515348806367', 'NSGA-II_crowding_distance: 0.2065157239024976', 'NSGA-II_rank: 2', 'change: 0.11329067610849151', 'is_elite: False']\n", + "Id: 31_82 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_71', '30_98'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_82', 'origin': '30_71~CUW~30_98#MGNP'} Metrics: ['ELUC: -8.399929419763186', 'NSGA-II_crowding_distance: 0.30806070840775945', 'NSGA-II_rank: 3', 'change: 0.12836992531187946', 'is_elite: False']\n", + "Id: 30_89 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_89', 'origin': '29_14~CUW~29_14#MGNP'} Metrics: ['ELUC: -8.511797071769356', 'NSGA-II_crowding_distance: 0.20171917424234875', 'NSGA-II_rank: 1', 'change: 0.11140431833454958', 'is_elite: True']\n", + "Id: 31_28 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_37', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_28', 'origin': '30_37~CUW~26_69#MGNP'} Metrics: ['ELUC: -8.899305532803298', 'NSGA-II_crowding_distance: 0.09519118131934483', 'NSGA-II_rank: 2', 'change: 0.12670025661177278', 'is_elite: False']\n", + "Id: 31_83 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '30_70'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_83', 'origin': '30_89~CUW~30_70#MGNP'} Metrics: ['ELUC: -8.92899849221472', 'NSGA-II_crowding_distance: 0.10277818298943887', 'NSGA-II_rank: 2', 'change: 0.1283453202132341', 'is_elite: False']\n", + "Id: 31_99 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_57', '30_89'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_99', 'origin': '29_57~CUW~30_89#MGNP'} Metrics: ['ELUC: -9.196244263604541', 'NSGA-II_crowding_distance: 0.1807286655693', 'NSGA-II_rank: 1', 'change: 0.12144567101510784', 'is_elite: False']\n", + "Id: 31_31 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_84', '30_34'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_31', 'origin': '30_84~CUW~30_34#MGNP'} Metrics: ['ELUC: -9.4334649903397', 'NSGA-II_crowding_distance: 1.0724366978125415', 'NSGA-II_rank: 6', 'change: 0.19041272017504046', 'is_elite: False']\n", + "Id: 31_87 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_71', '29_20'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_87', 'origin': '30_71~CUW~29_20#MGNP'} Metrics: ['ELUC: -9.55211512588883', 'NSGA-II_crowding_distance: 0.6770265824424051', 'NSGA-II_rank: 5', 'change: 0.1812726925149168', 'is_elite: False']\n", + "Id: 31_91 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '30_100'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_91', 'origin': '1_1~CUW~30_100#MGNP'} Metrics: ['ELUC: -9.558427288615526', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.300608025989648', 'is_elite: False']\n", + "Id: 31_78 Identity: {'ancestor_count': 28, 'ancestor_ids': ['26_69', '29_20'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_78', 'origin': '26_69~CUW~29_20#MGNP'} Metrics: ['ELUC: -9.766674777958462', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2149105097458069', 'is_elite: False']\n", + "Id: 31_77 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_77', 'origin': '30_70~CUW~26_69#MGNP'} Metrics: ['ELUC: -10.02821571561252', 'NSGA-II_crowding_distance: 0.4423115284032292', 'NSGA-II_rank: 3', 'change: 0.13825712560094117', 'is_elite: False']\n", + "Id: 31_36 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_14', '1_1'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_36', 'origin': '30_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.132780513874895', 'NSGA-II_crowding_distance: 0.5189596928334068', 'NSGA-II_rank: 5', 'change: 0.1939564172370492', 'is_elite: False']\n", + "Id: 31_45 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '30_98'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_45', 'origin': '30_70~CUW~30_98#MGNP'} Metrics: ['ELUC: -10.349036799499292', 'NSGA-II_crowding_distance: 0.2312083980736697', 'NSGA-II_rank: 2', 'change: 0.13268024748214885', 'is_elite: False']\n", + "Id: 30_70 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_33', '29_33'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_70', 'origin': '29_33~CUW~29_33#MGNP'} Metrics: ['ELUC: -10.523748258410913', 'NSGA-II_crowding_distance: 0.15167277650664884', 'NSGA-II_rank: 1', 'change: 0.13118629283280353', 'is_elite: False']\n", + "Id: 31_27 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_31', '30_14'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_27', 'origin': '30_31~CUW~30_14#MGNP'} Metrics: ['ELUC: -10.85871648711883', 'NSGA-II_crowding_distance: 0.09025138129588939', 'NSGA-II_rank: 1', 'change: 0.1384887814482254', 'is_elite: False']\n", + "Id: 31_22 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_37', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_22', 'origin': '30_37~CUW~26_69#MGNP'} Metrics: ['ELUC: -10.985233693068785', 'NSGA-II_crowding_distance: 0.1963006644548459', 'NSGA-II_rank: 2', 'change: 0.15880606222098276', 'is_elite: False']\n", + "Id: 31_37 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_14', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_37', 'origin': '30_14~CUW~26_69#MGNP'} Metrics: ['ELUC: -11.494239454213615', 'NSGA-II_crowding_distance: 0.07748712998375072', 'NSGA-II_rank: 1', 'change: 0.14164575903591098', 'is_elite: False']\n", + "Id: 31_43 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_34', '30_14'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_43', 'origin': '30_34~CUW~30_14#MGNP'} Metrics: ['ELUC: -11.837652280448678', 'NSGA-II_crowding_distance: 0.10355727967981945', 'NSGA-II_rank: 2', 'change: 0.1621717456440812', 'is_elite: False']\n", + "Id: 31_24 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_98', '29_20'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_24', 'origin': '30_98~CUW~29_20#MGNP'} Metrics: ['ELUC: -11.863721393484395', 'NSGA-II_crowding_distance: 0.7579983559292146', 'NSGA-II_rank: 5', 'change: 0.20191819162151753', 'is_elite: False']\n", + "Id: 31_44 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '30_14'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_44', 'origin': '30_70~CUW~30_14#MGNP'} Metrics: ['ELUC: -11.935838420035129', 'NSGA-II_crowding_distance: 0.12425377076451782', 'NSGA-II_rank: 1', 'change: 0.14333012305015558', 'is_elite: False']\n", + "Id: 31_25 Identity: {'ancestor_count': 25, 'ancestor_ids': ['30_100', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_25', 'origin': '30_100~CUW~29_57#MGNP'} Metrics: ['ELUC: -11.957130959413181', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.25798635222914523', 'is_elite: False']\n", + "Id: 31_58 Identity: {'ancestor_count': 23, 'ancestor_ids': ['1_1', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_58', 'origin': '1_1~CUW~29_57#MGNP'} Metrics: ['ELUC: -12.033704654908068', 'NSGA-II_crowding_distance: 1.0216157414643616', 'NSGA-II_rank: 4', 'change: 0.1712311337899576', 'is_elite: False']\n", + "Id: 30_34 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_67', '29_76'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_34', 'origin': '29_67~CUW~29_76#MGNP'} Metrics: ['ELUC: -12.3040503172611', 'NSGA-II_crowding_distance: 0.7071984359600978', 'NSGA-II_rank: 3', 'change: 0.16418656233555365', 'is_elite: False']\n", + "Id: 31_59 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_37', '30_34'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_59', 'origin': '30_37~CUW~30_34#MGNP'} Metrics: ['ELUC: -12.547817096960424', 'NSGA-II_crowding_distance: 0.28390383110141887', 'NSGA-II_rank: 2', 'change: 0.16339369330986964', 'is_elite: False']\n", + "Id: 31_56 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_57', '30_70'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_56', 'origin': '29_57~CUW~30_70#MGNP'} Metrics: ['ELUC: -12.548008029684503', 'NSGA-II_crowding_distance: 0.18752873160402067', 'NSGA-II_rank: 1', 'change: 0.16083753769550163', 'is_elite: False']\n", + "Id: 31_71 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '30_14'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_71', 'origin': '30_89~CUW~30_14#MGNP'} Metrics: ['ELUC: -13.145568978558883', 'NSGA-II_crowding_distance: 0.17335259102866363', 'NSGA-II_rank: 1', 'change: 0.1787550169871899', 'is_elite: False']\n", + "Id: 31_64 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_70', '29_20'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_64', 'origin': '30_70~CUW~29_20#MGNP'} Metrics: ['ELUC: -13.479875692868218', 'NSGA-II_crowding_distance: 0.601969588875188', 'NSGA-II_rank: 4', 'change: 0.24234494489547792', 'is_elite: False']\n", + "Id: 31_34 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_70', '30_34'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_34', 'origin': '30_70~CUW~30_34#MGNP'} Metrics: ['ELUC: -13.779572925338496', 'NSGA-II_crowding_distance: 0.15129479614436303', 'NSGA-II_rank: 1', 'change: 0.19166205177929305', 'is_elite: False']\n", + "Id: 31_69 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_49', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_69', 'origin': '30_49~CUW~29_57#MGNP'} Metrics: ['ELUC: -13.875677183157423', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.24462451199337856', 'is_elite: False']\n", + "Id: 31_75 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_17', '30_31'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_75', 'origin': '30_17~CUW~30_31#MGNP'} Metrics: ['ELUC: -13.948347281122132', 'NSGA-II_crowding_distance: 0.6957276200391375', 'NSGA-II_rank: 3', 'change: 0.2349083455683011', 'is_elite: False']\n", + "Id: 31_97 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_37', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_97', 'origin': '30_37~CUW~29_57#MGNP'} Metrics: ['ELUC: -14.184165211426198', 'NSGA-II_crowding_distance: 0.2719309082167216', 'NSGA-II_rank: 2', 'change: 0.20209234085585295', 'is_elite: False']\n", + "Id: 31_30 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_49', '2_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_30', 'origin': '30_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.320453912303464', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29048141322797644', 'is_elite: False']\n", + "Id: 31_53 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_57', '30_14'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_53', 'origin': '29_57~CUW~30_14#MGNP'} Metrics: ['ELUC: -14.43578175158836', 'NSGA-II_crowding_distance: 0.08917191862539796', 'NSGA-II_rank: 1', 'change: 0.20200270409684848', 'is_elite: False']\n", + "Id: 31_47 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_57', '30_89'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_47', 'origin': '29_57~CUW~30_89#MGNP'} Metrics: ['ELUC: -14.458503882378103', 'NSGA-II_crowding_distance: 0.23309601176992434', 'NSGA-II_rank: 2', 'change: 0.20638529621876398', 'is_elite: False']\n", + "Id: 31_86 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_49', '29_87'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_86', 'origin': '30_49~CUW~29_87#MGNP'} Metrics: ['ELUC: -14.524489693123783', 'NSGA-II_crowding_distance: 0.2857236424006022', 'NSGA-II_rank: 2', 'change: 0.2572570868311417', 'is_elite: False']\n", + "Id: 31_15 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_37', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_15', 'origin': '30_37~CUW~30_84#MGNP'} Metrics: ['ELUC: -14.534963472008572', 'NSGA-II_crowding_distance: 0.11489101123473079', 'NSGA-II_rank: 1', 'change: 0.20544975468091137', 'is_elite: False']\n", + "Id: 29_57 Identity: {'ancestor_count': 22, 'ancestor_ids': ['28_16', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_57', 'origin': '28_16~CUW~28_16#MGNP'} Metrics: ['ELUC: -15.149501618737311', 'NSGA-II_crowding_distance: 0.26426565371514876', 'NSGA-II_rank: 1', 'change: 0.22417157534001816', 'is_elite: True']\n", + "Id: 31_61 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_49', '26_69'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_61', 'origin': '30_49~CUW~26_69#MGNP'} Metrics: ['ELUC: -15.407178220551216', 'NSGA-II_crowding_distance: 0.240922008142658', 'NSGA-II_rank: 2', 'change: 0.26650317871285695', 'is_elite: False']\n", + "Id: 31_81 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_31', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_81', 'origin': '30_31~CUW~29_57#MGNP'} Metrics: ['ELUC: -15.925407357227305', 'NSGA-II_crowding_distance: 0.19664055639535782', 'NSGA-II_rank: 1', 'change: 0.26070447520141704', 'is_elite: True']\n", + "Id: 29_20 Identity: {'ancestor_count': 27, 'ancestor_ids': ['28_94', '28_94'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_20', 'origin': '28_94~CUW~28_94#MGNP'} Metrics: ['ELUC: -15.970139583571491', 'NSGA-II_crowding_distance: 0.06574843135161486', 'NSGA-II_rank: 1', 'change: 0.26891825595279273', 'is_elite: False']\n", + "Id: 31_16 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_20', '30_14'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_16', 'origin': '29_20~CUW~30_14#MGNP'} Metrics: ['ELUC: -16.25102408211291', 'NSGA-II_crowding_distance: 0.06905393898235145', 'NSGA-II_rank: 1', 'change: 0.27479652570579644', 'is_elite: False']\n", + "Id: 31_62 Identity: {'ancestor_count': 28, 'ancestor_ids': ['29_20', '30_100'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_62', 'origin': '29_20~CUW~30_100#MGNP'} Metrics: ['ELUC: -16.275045282920804', 'NSGA-II_crowding_distance: 0.1919989209173203', 'NSGA-II_rank: 2', 'change: 0.2945311927856347', 'is_elite: False']\n", + "Id: 31_17 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_34', '30_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_17', 'origin': '30_34~CUW~30_49#MGNP'} Metrics: ['ELUC: -16.72007602569927', 'NSGA-II_crowding_distance: 0.11833273143760176', 'NSGA-II_rank: 1', 'change: 0.2767957599055831', 'is_elite: False']\n", + "Id: 31_21 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_100', '30_37'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_21', 'origin': '30_100~CUW~30_37#MGNP'} Metrics: ['ELUC: -16.799357677181142', 'NSGA-II_crowding_distance: 0.08059401812984827', 'NSGA-II_rank: 2', 'change: 0.2962490759971701', 'is_elite: False']\n", + "Id: 31_41 Identity: {'ancestor_count': 26, 'ancestor_ids': ['2_49', '30_37'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_41', 'origin': '2_49~CUW~30_37#MGNP'} Metrics: ['ELUC: -17.237924967374905', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3016753415300157', 'is_elite: False']\n", + "Id: 31_35 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_31', '30_17'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_35', 'origin': '30_31~CUW~30_17#MGNP'} Metrics: ['ELUC: -17.248635649608904', 'NSGA-II_crowding_distance: 0.09318906070414787', 'NSGA-II_rank: 1', 'change: 0.29317459991542827', 'is_elite: False']\n", + "Id: 31_85 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_49', '30_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_85', 'origin': '30_49~CUW~30_49#MGNP'} Metrics: ['ELUC: -17.301476533743262', 'NSGA-II_crowding_distance: 0.05148923650871132', 'NSGA-II_rank: 1', 'change: 0.2947347530525884', 'is_elite: False']\n", + "Id: 31_79 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_84', '2_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_79', 'origin': '30_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.580152762247636', 'NSGA-II_crowding_distance: 0.044599169094677316', 'NSGA-II_rank: 1', 'change: 0.30291189305530564', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 30_100 Identity: {'ancestor_count': 24, 'ancestor_ids': ['29_71', '2_49'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_100', 'origin': '29_71~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 31_13 Identity: {'ancestor_count': 25, 'ancestor_ids': ['30_100', '30_100'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_13', 'origin': '30_100~CUW~30_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 31_63 Identity: {'ancestor_count': 25, 'ancestor_ids': ['30_100', '2_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_63', 'origin': '30_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 31_89 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_89', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 31_92 Identity: {'ancestor_count': 25, 'ancestor_ids': ['30_100', '1_1'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_92', 'origin': '30_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 31_96 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_100', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_96', 'origin': '30_100~CUW~30_84#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 31.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 32...:\n", + "PopulationResponse:\n", + " Generation: 32\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/32/20240219-233058\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 32 and asking ESP for generation 33...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 32 data persisted.\n", + "Evaluated candidates:\n", + "Id: 32_55 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_96', '29_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_55', 'origin': '31_96~CUW~29_57#MGNP'} Metrics: ['ELUC: 22.791871928987298', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.29501627502324845', 'is_elite: False']\n", + "Id: 32_23 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_96', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_23', 'origin': '31_96~CUW~26_69#MGNP'} Metrics: ['ELUC: 22.055144527398916', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2959131723366261', 'is_elite: False']\n", + "Id: 32_14 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_96', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_14', 'origin': '31_96~CUW~26_69#MGNP'} Metrics: ['ELUC: 11.790213050863834', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2540971959899601', 'is_elite: False']\n", + "Id: 32_36 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_34', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_36', 'origin': '31_34~CUW~2_49#MGNP'} Metrics: ['ELUC: 11.53847477719004', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28448867092186114', 'is_elite: False']\n", + "Id: 32_27 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_27', 'origin': '30_70~CUW~2_49#MGNP'} Metrics: ['ELUC: 9.124018507077212', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2413191314444242', 'is_elite: False']\n", + "Id: 32_12 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '31_96'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_12', 'origin': '31_81~CUW~31_96#MGNP'} Metrics: ['ELUC: 7.646896684031535', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.24976404011100678', 'is_elite: False']\n", + "Id: 32_39 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_44', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_39', 'origin': '31_44~CUW~2_49#MGNP'} Metrics: ['ELUC: 5.715061411580389', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2574002750336985', 'is_elite: False']\n", + "Id: 32_42 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_42', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.8551553877242162', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03909901266200725', 'is_elite: False']\n", + "Id: 32_93 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_93', 'origin': '26_69~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.8220904694192255', 'NSGA-II_crowding_distance: 0.13341384443025944', 'NSGA-II_rank: 2', 'change: 0.04470989225358118', 'is_elite: False']\n", + "Id: 32_66 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_71', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_66', 'origin': '31_71~CUW~26_69#MGNP'} Metrics: ['ELUC: 0.5647905491648358', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09348334331440694', 'is_elite: False']\n", + "Id: 32_58 Identity: {'ancestor_count': 21, 'ancestor_ids': ['1_1', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_58', 'origin': '1_1~CUW~26_69#MGNP'} Metrics: ['ELUC: 0.3865719755059157', 'NSGA-II_crowding_distance: 0.09324544098263102', 'NSGA-II_rank: 2', 'change: 0.049988044878633904', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 32_37 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_37', 'origin': '26_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.3519951294705066', 'NSGA-II_crowding_distance: 0.19163061475380927', 'NSGA-II_rank: 2', 'change: 0.0505079060385384', 'is_elite: False']\n", + "Id: 32_11 Identity: {'ancestor_count': 27, 'ancestor_ids': ['26_69', '31_96'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_11', 'origin': '26_69~CUW~31_96#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 32_38 Identity: {'ancestor_count': 26, 'ancestor_ids': ['31_88', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_38', 'origin': '31_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 32_44 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_44', 'origin': '30_70~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 32_89 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_96', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_89', 'origin': '31_96~CUW~26_69#MGNP'} Metrics: ['ELUC: -0.5782841052078678', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.22835835051251785', 'is_elite: False']\n", + "Id: 32_16 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_56', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_16', 'origin': '31_56~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.711626459812616', 'NSGA-II_crowding_distance: 0.5199370726679298', 'NSGA-II_rank: 4', 'change: 0.09655434586294633', 'is_elite: False']\n", + "Id: 32_95 Identity: {'ancestor_count': 27, 'ancestor_ids': ['1_1', '31_46'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_95', 'origin': '1_1~CUW~31_46#MGNP'} Metrics: ['ELUC: -0.8692432628010838', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06407876003168404', 'is_elite: False']\n", + "Id: 32_51 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_51', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.297358733794656', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3075999455522391', 'is_elite: False']\n", + "Id: 32_82 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_82', 'origin': '26_69~CUW~26_69#MGNP'} Metrics: ['ELUC: -1.6771410833755096', 'NSGA-II_crowding_distance: 0.2604517177260295', 'NSGA-II_rank: 1', 'change: 0.040853686525119996', 'is_elite: True']\n", + "Id: 26_69 Identity: {'ancestor_count': 20, 'ancestor_ids': ['23_59', '23_59'], 'birth_generation': 26, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '26_69', 'origin': '23_59~CUW~23_59#MGNP'} Metrics: ['ELUC: -2.3593292124774066', 'NSGA-II_crowding_distance: 0.09295598591403043', 'NSGA-II_rank: 1', 'change: 0.04257255541510991', 'is_elite: False']\n", + "Id: 32_60 Identity: {'ancestor_count': 27, 'ancestor_ids': ['26_69', '31_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_60', 'origin': '26_69~CUW~31_57#MGNP'} Metrics: ['ELUC: -2.3947299648708635', 'NSGA-II_crowding_distance: 0.38135585683581075', 'NSGA-II_rank: 3', 'change: 0.08525169695504903', 'is_elite: False']\n", + "Id: 32_73 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_73', 'origin': '26_69~CUW~26_69#MGNP'} Metrics: ['ELUC: -2.686786999320467', 'NSGA-II_crowding_distance: 0.22590422380868375', 'NSGA-II_rank: 2', 'change: 0.05379661190874691', 'is_elite: False']\n", + "Id: 32_15 Identity: {'ancestor_count': 23, 'ancestor_ids': ['2_49', '29_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_15', 'origin': '2_49~CUW~29_57#MGNP'} Metrics: ['ELUC: -2.761578884099701', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2598306526148446', 'is_elite: False']\n", + "Id: 32_90 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_90', 'origin': '26_69~CUW~26_69#MGNP'} Metrics: ['ELUC: -2.910077720124723', 'NSGA-II_crowding_distance: 0.10144792481606152', 'NSGA-II_rank: 1', 'change: 0.04766636646236374', 'is_elite: False']\n", + "Id: 32_52 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_52', 'origin': '31_57~CUW~26_69#MGNP'} Metrics: ['ELUC: -2.948449518259053', 'NSGA-II_crowding_distance: 0.23186190076473856', 'NSGA-II_rank: 2', 'change: 0.0675985720016982', 'is_elite: False']\n", + "Id: 32_18 Identity: {'ancestor_count': 26, 'ancestor_ids': ['1_1', '30_84'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_18', 'origin': '1_1~CUW~30_84#MGNP'} Metrics: ['ELUC: -3.133129964654368', 'NSGA-II_crowding_distance: 0.12945146658584816', 'NSGA-II_rank: 1', 'change: 0.05971071812463945', 'is_elite: False']\n", + "Id: 32_87 Identity: {'ancestor_count': 27, 'ancestor_ids': ['1_1', '31_56'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_87', 'origin': '1_1~CUW~31_56#MGNP'} Metrics: ['ELUC: -3.3571804026105223', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15561669108511805', 'is_elite: False']\n", + "Id: 31_88 Identity: {'ancestor_count': 25, 'ancestor_ids': ['26_69', '30_62'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_88', 'origin': '26_69~CUW~30_62#MGNP'} Metrics: ['ELUC: -3.9875871831642833', 'NSGA-II_crowding_distance: 0.1095434101471108', 'NSGA-II_rank: 1', 'change: 0.06800613154290952', 'is_elite: False']\n", + "Id: 32_45 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_99', '31_96'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_45', 'origin': '31_99~CUW~31_96#MGNP'} Metrics: ['ELUC: -4.043946516528623', 'NSGA-II_crowding_distance: 1.8231356822266713', 'NSGA-II_rank: 7', 'change: 0.2515840670554848', 'is_elite: False']\n", + "Id: 32_62 Identity: {'ancestor_count': 26, 'ancestor_ids': ['31_88', '31_88'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_62', 'origin': '31_88~CUW~31_88#MGNP'} Metrics: ['ELUC: -4.197159566209317', 'NSGA-II_crowding_distance: 0.050639880384694275', 'NSGA-II_rank: 1', 'change: 0.07433912023084409', 'is_elite: False']\n", + "Id: 32_28 Identity: {'ancestor_count': 26, 'ancestor_ids': ['1_1', '31_88'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_28', 'origin': '1_1~CUW~31_88#MGNP'} Metrics: ['ELUC: -4.431759354956985', 'NSGA-II_crowding_distance: 0.23583816609947686', 'NSGA-II_rank: 2', 'change: 0.08263014439208743', 'is_elite: False']\n", + "Id: 32_86 Identity: {'ancestor_count': 26, 'ancestor_ids': ['31_88', '31_88'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_86', 'origin': '31_88~CUW~31_88#MGNP'} Metrics: ['ELUC: -4.448396917974708', 'NSGA-II_crowding_distance: 0.11460008015439907', 'NSGA-II_rank: 1', 'change: 0.07529586010173257', 'is_elite: False']\n", + "Id: 32_46 Identity: {'ancestor_count': 27, 'ancestor_ids': ['26_69', '31_46'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_46', 'origin': '26_69~CUW~31_46#MGNP'} Metrics: ['ELUC: -4.615081681182797', 'NSGA-II_crowding_distance: 0.37631954522230554', 'NSGA-II_rank: 3', 'change: 0.09043017543436055', 'is_elite: False']\n", + "Id: 32_94 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_56', '31_88'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_94', 'origin': '31_56~CUW~31_88#MGNP'} Metrics: ['ELUC: -5.691148473682366', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.13012159523854405', 'is_elite: False']\n", + "Id: 32_35 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '31_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_35', 'origin': '31_57~CUW~31_57#MGNP'} Metrics: ['ELUC: -5.703691998981273', 'NSGA-II_crowding_distance: 0.11233726102354255', 'NSGA-II_rank: 2', 'change: 0.08489319809928729', 'is_elite: False']\n", + "Id: 31_57 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_87', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_57', 'origin': '29_87~CUW~30_84#MGNP'} Metrics: ['ELUC: -5.737747831221566', 'NSGA-II_crowding_distance: 0.13954141981804366', 'NSGA-II_rank: 1', 'change: 0.08238897259723696', 'is_elite: False']\n", + "Id: 32_32 Identity: {'ancestor_count': 23, 'ancestor_ids': ['29_57', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_32', 'origin': '29_57~CUW~26_69#MGNP'} Metrics: ['ELUC: -5.877667424205548', 'NSGA-II_crowding_distance: 1.258264518286236', 'NSGA-II_rank: 6', 'change: 0.13617294049146925', 'is_elite: False']\n", + "Id: 32_30 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_34', '31_88'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_30', 'origin': '31_34~CUW~31_88#MGNP'} Metrics: ['ELUC: -5.906009930822955', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11301108662937283', 'is_elite: False']\n", + "Id: 32_78 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_88', '31_99'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_78', 'origin': '31_88~CUW~31_99#MGNP'} Metrics: ['ELUC: -5.977856965708073', 'NSGA-II_crowding_distance: 0.11091516825096287', 'NSGA-II_rank: 2', 'change: 0.08799969855209533', 'is_elite: False']\n", + "Id: 32_81 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '31_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_81', 'origin': '31_57~CUW~31_57#MGNP'} Metrics: ['ELUC: -6.213367180440976', 'NSGA-II_crowding_distance: 0.06652407216363712', 'NSGA-II_rank: 1', 'change: 0.08697982074624894', 'is_elite: False']\n", + "Id: 32_100 Identity: {'ancestor_count': 27, 'ancestor_ids': ['30_84', '31_71'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_100', 'origin': '30_84~CUW~31_71#MGNP'} Metrics: ['ELUC: -6.6228961449258446', 'NSGA-II_crowding_distance: 0.20548038547325476', 'NSGA-II_rank: 3', 'change: 0.10312179105829741', 'is_elite: False']\n", + "Id: 32_72 Identity: {'ancestor_count': 27, 'ancestor_ids': ['30_89', '31_56'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_72', 'origin': '30_89~CUW~31_56#MGNP'} Metrics: ['ELUC: -6.626488354906002', 'NSGA-II_crowding_distance: 0.9538136634086003', 'NSGA-II_rank: 4', 'change: 0.10551153455415471', 'is_elite: False']\n", + "Id: 32_92 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '30_89'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_92', 'origin': '31_57~CUW~30_89#MGNP'} Metrics: ['ELUC: -6.630390730059577', 'NSGA-II_crowding_distance: 0.05581969400673295', 'NSGA-II_rank: 1', 'change: 0.08708984812307881', 'is_elite: False']\n", + "Id: 32_22 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '30_89'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_22', 'origin': '30_70~CUW~30_89#MGNP'} Metrics: ['ELUC: -6.659362817612219', 'NSGA-II_crowding_distance: 0.09165383250196195', 'NSGA-II_rank: 2', 'change: 0.09720181080178956', 'is_elite: False']\n", + "Id: 30_84 Identity: {'ancestor_count': 25, 'ancestor_ids': ['1_1', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_84', 'origin': '1_1~CUW~29_14#MGNP'} Metrics: ['ELUC: -6.705433220844791', 'NSGA-II_crowding_distance: 0.22283181695793014', 'NSGA-II_rank: 3', 'change: 0.10352699584300033', 'is_elite: False']\n", + "Id: 32_48 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_48', 'origin': '30_89~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.771575409727288', 'NSGA-II_crowding_distance: 0.28844625576141786', 'NSGA-II_rank: 2', 'change: 0.09812162509147108', 'is_elite: False']\n", + "Id: 32_26 Identity: {'ancestor_count': 27, 'ancestor_ids': ['30_84', '31_46'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_26', 'origin': '30_84~CUW~31_46#MGNP'} Metrics: ['ELUC: -6.911639113378094', 'NSGA-II_crowding_distance: 0.18849435768833983', 'NSGA-II_rank: 1', 'change: 0.09178528357407047', 'is_elite: True']\n", + "Id: 32_41 Identity: {'ancestor_count': 27, 'ancestor_ids': ['1_1', '31_99'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_41', 'origin': '1_1~CUW~31_99#MGNP'} Metrics: ['ELUC: -7.509317943713302', 'NSGA-II_crowding_distance: 0.36120656462295747', 'NSGA-II_rank: 3', 'change: 0.13843713839148086', 'is_elite: False']\n", + "Id: 30_89 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_89', 'origin': '29_14~CUW~29_14#MGNP'} Metrics: ['ELUC: -8.511797071769356', 'NSGA-II_crowding_distance: 0.23379429066394547', 'NSGA-II_rank: 1', 'change: 0.11140431833454958', 'is_elite: True']\n", + "Id: 32_68 Identity: {'ancestor_count': 27, 'ancestor_ids': ['29_57', '31_46'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_68', 'origin': '29_57~CUW~31_46#MGNP'} Metrics: ['ELUC: -8.863679804260249', 'NSGA-II_crowding_distance: 0.10929170045397497', 'NSGA-II_rank: 1', 'change: 0.12841755757535267', 'is_elite: False']\n", + "Id: 32_71 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_71', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_71', 'origin': '31_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.967269857961083', 'NSGA-II_crowding_distance: 0.28508894777016314', 'NSGA-II_rank: 2', 'change: 0.13138929681375738', 'is_elite: False']\n", + "Id: 32_57 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_56', '30_84'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_57', 'origin': '31_56~CUW~30_84#MGNP'} Metrics: ['ELUC: -9.063483405037553', 'NSGA-II_crowding_distance: 0.012343468890054388', 'NSGA-II_rank: 2', 'change: 0.13177784965574627', 'is_elite: False']\n", + "Id: 32_74 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '30_89'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_74', 'origin': '31_81~CUW~30_89#MGNP'} Metrics: ['ELUC: -9.128278750958506', 'NSGA-II_crowding_distance: 0.6470167343703563', 'NSGA-II_rank: 4', 'change: 0.1793163396884824', 'is_elite: False']\n", + "Id: 32_53 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_99', '31_99'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_53', 'origin': '31_99~CUW~31_99#MGNP'} Metrics: ['ELUC: -9.138243429309513', 'NSGA-II_crowding_distance: 0.030789575742436168', 'NSGA-II_rank: 2', 'change: 0.13196591175862427', 'is_elite: False']\n", + "Id: 32_76 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_17', '31_99'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_76', 'origin': '31_17~CUW~31_99#MGNP'} Metrics: ['ELUC: -9.269041992249942', 'NSGA-II_crowding_distance: 1.715646964513136', 'NSGA-II_rank: 6', 'change: 0.2090217651686665', 'is_elite: False']\n", + "Id: 32_77 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '31_15'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_77', 'origin': '31_57~CUW~31_15#MGNP'} Metrics: ['ELUC: -9.282671348525703', 'NSGA-II_crowding_distance: 0.36634818053129825', 'NSGA-II_rank: 3', 'change: 0.1433318080684358', 'is_elite: False']\n", + "Id: 32_19 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_71', '30_89'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_19', 'origin': '31_71~CUW~30_89#MGNP'} Metrics: ['ELUC: -9.292366422608069', 'NSGA-II_crowding_distance: 0.07279044192818764', 'NSGA-II_rank: 1', 'change: 0.1307680236858183', 'is_elite: False']\n", + "Id: 32_31 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_88', '31_71'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_31', 'origin': '31_88~CUW~31_71#MGNP'} Metrics: ['ELUC: -9.31423045511255', 'NSGA-II_crowding_distance: 0.048906203851583285', 'NSGA-II_rank: 2', 'change: 0.13537317883011565', 'is_elite: False']\n", + "Id: 32_99 Identity: {'ancestor_count': 30, 'ancestor_ids': ['1_1', '31_81'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_99', 'origin': '1_1~CUW~31_81#MGNP'} Metrics: ['ELUC: -9.365219399870886', 'NSGA-II_crowding_distance: 1.2335464823650315', 'NSGA-II_rank: 5', 'change: 0.18111102203511661', 'is_elite: False']\n", + "Id: 32_79 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_88', '31_56'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_79', 'origin': '31_88~CUW~31_56#MGNP'} Metrics: ['ELUC: -9.574820902141495', 'NSGA-II_crowding_distance: 0.3309918177123204', 'NSGA-II_rank: 2', 'change: 0.13720673525632404', 'is_elite: False']\n", + "Id: 32_84 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_84', '29_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_84', 'origin': '30_84~CUW~29_57#MGNP'} Metrics: ['ELUC: -9.690615040837583', 'NSGA-II_crowding_distance: 0.9011225862454401', 'NSGA-II_rank: 5', 'change: 0.1918473328202096', 'is_elite: False']\n", + "Id: 32_88 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '31_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_88', 'origin': '31_81~CUW~31_57#MGNP'} Metrics: ['ELUC: -9.838088974640385', 'NSGA-II_crowding_distance: 0.13678427190339773', 'NSGA-II_rank: 1', 'change: 0.13360057936315073', 'is_elite: False']\n", + "Id: 32_29 Identity: {'ancestor_count': 27, 'ancestor_ids': ['30_70', '31_96'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_29', 'origin': '30_70~CUW~31_96#MGNP'} Metrics: ['ELUC: -10.012160625820496', 'NSGA-II_crowding_distance: 1.1375768791714735', 'NSGA-II_rank: 7', 'change: 0.26351560133169144', 'is_elite: False']\n", + "Id: 32_40 Identity: {'ancestor_count': 27, 'ancestor_ids': ['2_49', '31_99'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_40', 'origin': '2_49~CUW~31_99#MGNP'} Metrics: ['ELUC: -10.125675304022584', 'NSGA-II_crowding_distance: 0.741735481713764', 'NSGA-II_rank: 6', 'change: 0.2633110027391058', 'is_elite: False']\n", + "Id: 32_64 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_96', '31_81'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_64', 'origin': '31_96~CUW~31_81#MGNP'} Metrics: ['ELUC: -10.249869055553647', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.28142831832161436', 'is_elite: False']\n", + "Id: 32_83 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_83', 'origin': '31_57~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.556053850019092', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2810357948108395', 'is_elite: False']\n", + "Id: 32_91 Identity: {'ancestor_count': 23, 'ancestor_ids': ['29_57', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_91', 'origin': '29_57~CUW~26_69#MGNP'} Metrics: ['ELUC: -10.65183990407417', 'NSGA-II_crowding_distance: 0.3036385221366058', 'NSGA-II_rank: 3', 'change: 0.1707241575937649', 'is_elite: False']\n", + "Id: 32_21 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_57', '30_89'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_21', 'origin': '29_57~CUW~30_89#MGNP'} Metrics: ['ELUC: -10.768982042521534', 'NSGA-II_crowding_distance: 0.19166359719073126', 'NSGA-II_rank: 1', 'change: 0.14652277998312305', 'is_elite: True']\n", + "Id: 32_47 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_71', '29_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_47', 'origin': '31_71~CUW~29_57#MGNP'} Metrics: ['ELUC: -10.884791062701629', 'NSGA-II_crowding_distance: 0.18548226895472586', 'NSGA-II_rank: 4', 'change: 0.18009608624830664', 'is_elite: False']\n", + "Id: 32_96 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_71', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_96', 'origin': '31_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.424635441787348', 'NSGA-II_crowding_distance: 0.4032177910073436', 'NSGA-II_rank: 4', 'change: 0.18702694013675744', 'is_elite: False']\n", + "Id: 32_61 Identity: {'ancestor_count': 27, 'ancestor_ids': ['26_69', '31_96'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_61', 'origin': '26_69~CUW~31_96#MGNP'} Metrics: ['ELUC: -11.60836965245317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.251355378332751', 'is_elite: False']\n", + "Id: 32_80 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '30_84'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_80', 'origin': '31_81~CUW~30_84#MGNP'} Metrics: ['ELUC: -11.62328955876566', 'NSGA-II_crowding_distance: 0.132927910585743', 'NSGA-II_rank: 3', 'change: 0.17412945370791016', 'is_elite: False']\n", + "Id: 32_34 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '31_96'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_34', 'origin': '31_57~CUW~31_96#MGNP'} Metrics: ['ELUC: -12.060658170983187', 'NSGA-II_crowding_distance: 0.7085226504595816', 'NSGA-II_rank: 4', 'change: 0.24536036474920483', 'is_elite: False']\n", + "Id: 32_69 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '30_70'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_69', 'origin': '31_81~CUW~30_70#MGNP'} Metrics: ['ELUC: -12.120818916205838', 'NSGA-II_crowding_distance: 0.2000748718448621', 'NSGA-II_rank: 1', 'change: 0.15205009484906773', 'is_elite: True']\n", + "Id: 32_13 Identity: {'ancestor_count': 23, 'ancestor_ids': ['29_57', '1_1'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_13', 'origin': '29_57~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.249591458251436', 'NSGA-II_crowding_distance: 0.6466587230359648', 'NSGA-II_rank: 3', 'change: 0.17544233769872977', 'is_elite: False']\n", + "Id: 32_63 Identity: {'ancestor_count': 27, 'ancestor_ids': ['29_57', '31_99'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_63', 'origin': '29_57~CUW~31_99#MGNP'} Metrics: ['ELUC: -12.383393173193275', 'NSGA-II_crowding_distance: 0.9000056915370284', 'NSGA-II_rank: 2', 'change: 0.16943761153583523', 'is_elite: False']\n", + "Id: 32_17 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_56', '29_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_17', 'origin': '31_56~CUW~29_57#MGNP'} Metrics: ['ELUC: -13.106011892139373', 'NSGA-II_crowding_distance: 0.10849169126556923', 'NSGA-II_rank: 1', 'change: 0.166560546202167', 'is_elite: False']\n", + "Id: 32_24 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_70', '30_89'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_24', 'origin': '30_70~CUW~30_89#MGNP'} Metrics: ['ELUC: -13.168572753288332', 'NSGA-II_crowding_distance: 0.09227358138040082', 'NSGA-II_rank: 1', 'change: 0.16664089221800002', 'is_elite: False']\n", + "Id: 32_43 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_56', '31_34'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_43', 'origin': '31_56~CUW~31_34#MGNP'} Metrics: ['ELUC: -13.34432101736517', 'NSGA-II_crowding_distance: 0.1381497777304006', 'NSGA-II_rank: 1', 'change: 0.1900487472171519', 'is_elite: False']\n", + "Id: 32_50 Identity: {'ancestor_count': 26, 'ancestor_ids': ['2_49', '30_70'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_50', 'origin': '2_49~CUW~30_70#MGNP'} Metrics: ['ELUC: -13.874757296625212', 'NSGA-II_crowding_distance: 0.6986589006847002', 'NSGA-II_rank: 3', 'change: 0.28152305448705994', 'is_elite: False']\n", + "Id: 32_65 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '29_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_65', 'origin': '31_57~CUW~29_57#MGNP'} Metrics: ['ELUC: -13.964036829155898', 'NSGA-II_crowding_distance: 0.17524299669848986', 'NSGA-II_rank: 1', 'change: 0.19436243663438685', 'is_elite: False']\n", + "Id: 32_59 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_84', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_59', 'origin': '30_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.265455652840828', 'NSGA-II_crowding_distance: 0.4298284019543702', 'NSGA-II_rank: 4', 'change: 0.29186223236685566', 'is_elite: False']\n", + "Id: 32_70 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_57', '31_88'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_70', 'origin': '29_57~CUW~31_88#MGNP'} Metrics: ['ELUC: -14.884285222374753', 'NSGA-II_crowding_distance: 0.16732764915738213', 'NSGA-II_rank: 1', 'change: 0.21620368490543032', 'is_elite: False']\n", + "Id: 32_33 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_56', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_33', 'origin': '31_56~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.086442024433586', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.29240617207063374', 'is_elite: False']\n", + "Id: 29_57 Identity: {'ancestor_count': 22, 'ancestor_ids': ['28_16', '28_16'], 'birth_generation': 29, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '29_57', 'origin': '28_16~CUW~28_16#MGNP'} Metrics: ['ELUC: -15.149501618737311', 'NSGA-II_crowding_distance: 0.05620831314808775', 'NSGA-II_rank: 1', 'change: 0.22417157534001816', 'is_elite: False']\n", + "Id: 32_54 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_99', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_54', 'origin': '31_99~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.209719782954357', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.28340253267155296', 'is_elite: False']\n", + "Id: 32_67 Identity: {'ancestor_count': 23, 'ancestor_ids': ['29_57', '29_57'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_67', 'origin': '29_57~CUW~29_57#MGNP'} Metrics: ['ELUC: -15.243695900941116', 'NSGA-II_crowding_distance: 0.11814702169769362', 'NSGA-II_rank: 1', 'change: 0.226875682937223', 'is_elite: False']\n", + "Id: 32_56 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_34', '31_81'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_56', 'origin': '31_34~CUW~31_81#MGNP'} Metrics: ['ELUC: -15.675957591214162', 'NSGA-II_crowding_distance: 0.13398393459089092', 'NSGA-II_rank: 1', 'change: 0.2504898935443958', 'is_elite: False']\n", + "Id: 32_85 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_15', '31_81'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_85', 'origin': '31_15~CUW~31_81#MGNP'} Metrics: ['ELUC: -15.801931227489002', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2558333512277939', 'is_elite: False']\n", + "Id: 32_25 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '31_81'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_25', 'origin': '31_81~CUW~31_81#MGNP'} Metrics: ['ELUC: -15.896039825649757', 'NSGA-II_crowding_distance: 0.04842124717333633', 'NSGA-II_rank: 1', 'change: 0.25578302566940203', 'is_elite: False']\n", + "Id: 31_81 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_31', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_81', 'origin': '30_31~CUW~29_57#MGNP'} Metrics: ['ELUC: -15.925407357227305', 'NSGA-II_crowding_distance: 0.24018058401362563', 'NSGA-II_rank: 1', 'change: 0.26070447520141704', 'is_elite: True']\n", + "Id: 32_98 Identity: {'ancestor_count': 30, 'ancestor_ids': ['2_49', '31_81'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_98', 'origin': '2_49~CUW~31_81#MGNP'} Metrics: ['ELUC: -17.357032944967596', 'NSGA-II_crowding_distance: 0.2369144563055045', 'NSGA-II_rank: 1', 'change: 0.3026540558981913', 'is_elite: True']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 31_96 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_100', '30_84'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_96', 'origin': '30_100~CUW~30_84#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 32_20 Identity: {'ancestor_count': 30, 'ancestor_ids': ['2_49', '31_17'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_20', 'origin': '2_49~CUW~31_17#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 32_49 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_49', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 32_75 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_75', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 32_97 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_97', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 32.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 33...:\n", + "PopulationResponse:\n", + " Generation: 33\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/33/20240219-233811\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 33 and asking ESP for generation 34...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 33 data persisted.\n", + "Evaluated candidates:\n", + "Id: 33_88 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '2_49'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_88', 'origin': '30_89~CUW~2_49#MGNP'} Metrics: ['ELUC: 17.996828380198824', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.29918467039423313', 'is_elite: False']\n", + "Id: 33_51 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '2_49'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_51', 'origin': '31_57~CUW~2_49#MGNP'} Metrics: ['ELUC: 17.938480310452885', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2786430113149484', 'is_elite: False']\n", + "Id: 33_98 Identity: {'ancestor_count': 22, 'ancestor_ids': ['32_97', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_98', 'origin': '32_97~CUW~32_82#MGNP'} Metrics: ['ELUC: 17.565780384164754', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.291855576078921', 'is_elite: False']\n", + "Id: 33_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_54', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 14.95049577771143', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.2800605382747807', 'is_elite: False']\n", + "Id: 33_99 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_98', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_99', 'origin': '32_98~CUW~32_97#MGNP'} Metrics: ['ELUC: 14.411752562641768', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2779682147357819', 'is_elite: False']\n", + "Id: 33_47 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_47', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.8588184821685183', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23987534436846428', 'is_elite: False']\n", + "Id: 33_63 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_43', '32_98'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_63', 'origin': '32_43~CUW~32_98#MGNP'} Metrics: ['ELUC: 2.527317535969431', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.35166354327194366', 'is_elite: False']\n", + "Id: 33_22 Identity: {'ancestor_count': 22, 'ancestor_ids': ['2_49', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_22', 'origin': '2_49~CUW~32_82#MGNP'} Metrics: ['ELUC: 1.6356128973755704', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3118401964206997', 'is_elite: False']\n", + "Id: 33_85 Identity: {'ancestor_count': 30, 'ancestor_ids': ['30_89', '31_81'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_85', 'origin': '30_89~CUW~31_81#MGNP'} Metrics: ['ELUC: 0.2087241726676334', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.13645569186757697', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 33_16 Identity: {'ancestor_count': 31, 'ancestor_ids': ['2_49', '32_69'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_16', 'origin': '2_49~CUW~32_69#MGNP'} Metrics: ['ELUC: -0.48474618135115255', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2685696076691994', 'is_elite: False']\n", + "Id: 33_28 Identity: {'ancestor_count': 28, 'ancestor_ids': ['2_49', '32_26'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_28', 'origin': '2_49~CUW~32_26#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 33_82 Identity: {'ancestor_count': 22, 'ancestor_ids': ['32_82', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_82', 'origin': '32_82~CUW~32_82#MGNP'} Metrics: ['ELUC: -1.159438981555866', 'NSGA-II_crowding_distance: 0.22326155178717827', 'NSGA-II_rank: 1', 'change: 0.04005765814965266', 'is_elite: True']\n", + "Id: 33_60 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_60', 'origin': '1_1~CUW~32_97#MGNP'} Metrics: ['ELUC: -1.1964050276590437', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.2440377905070395', 'is_elite: False']\n", + "Id: 33_91 Identity: {'ancestor_count': 22, 'ancestor_ids': ['32_82', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_91', 'origin': '32_82~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2511306364609844', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.054134488181957215', 'is_elite: False']\n", + "Id: 33_92 Identity: {'ancestor_count': 22, 'ancestor_ids': ['32_82', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_92', 'origin': '32_82~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6759441882874206', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05053423438746604', 'is_elite: False']\n", + "Id: 32_82 Identity: {'ancestor_count': 21, 'ancestor_ids': ['26_69', '26_69'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_82', 'origin': '26_69~CUW~26_69#MGNP'} Metrics: ['ELUC: -1.6771410833755096', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.040853686525119996', 'is_elite: False']\n", + "Id: 33_41 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_18', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_41', 'origin': '32_18~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8317501303378378', 'NSGA-II_crowding_distance: 0.14419983137723236', 'NSGA-II_rank: 1', 'change: 0.04042901831194514', 'is_elite: False']\n", + "Id: 33_21 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_21', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_21', 'origin': '32_21~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.3992095581584656', 'NSGA-II_crowding_distance: 0.24588610322317694', 'NSGA-II_rank: 4', 'change: 0.08472998941706819', 'is_elite: False']\n", + "Id: 33_42 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_42', 'origin': '31_57~CUW~32_82#MGNP'} Metrics: ['ELUC: -2.559140370358219', 'NSGA-II_crowding_distance: 0.17763017991771618', 'NSGA-II_rank: 1', 'change: 0.05933031033800357', 'is_elite: False']\n", + "Id: 33_87 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_70', '30_89'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_87', 'origin': '32_70~CUW~30_89#MGNP'} Metrics: ['ELUC: -2.621011214928707', 'NSGA-II_crowding_distance: 0.3956604929085823', 'NSGA-II_rank: 4', 'change: 0.08906576160952104', 'is_elite: False']\n", + "Id: 33_17 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_17', 'origin': '31_81~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.9906128829807197', 'NSGA-II_crowding_distance: 0.6265924472335891', 'NSGA-II_rank: 5', 'change: 0.15564831022816938', 'is_elite: False']\n", + "Id: 33_26 Identity: {'ancestor_count': 26, 'ancestor_ids': ['32_82', '31_88'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_26', 'origin': '32_82~CUW~31_88#MGNP'} Metrics: ['ELUC: -3.313906321317107', 'NSGA-II_crowding_distance: 0.3460813249145701', 'NSGA-II_rank: 3', 'change: 0.07767798065802096', 'is_elite: False']\n", + "Id: 33_75 Identity: {'ancestor_count': 31, 'ancestor_ids': ['31_57', '32_88'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_75', 'origin': '31_57~CUW~32_88#MGNP'} Metrics: ['ELUC: -3.4025763533570195', 'NSGA-II_crowding_distance: 0.13136906342028926', 'NSGA-II_rank: 3', 'change: 0.10836727150010353', 'is_elite: False']\n", + "Id: 33_64 Identity: {'ancestor_count': 31, 'ancestor_ids': ['1_1', '32_56'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_64', 'origin': '1_1~CUW~32_56#MGNP'} Metrics: ['ELUC: -3.4380026379495154', 'NSGA-II_crowding_distance: 0.04218487510922072', 'NSGA-II_rank: 3', 'change: 0.10838975834264655', 'is_elite: False']\n", + "Id: 33_89 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_70', '31_57'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_89', 'origin': '32_70~CUW~31_57#MGNP'} Metrics: ['ELUC: -3.6172762920008044', 'NSGA-II_crowding_distance: 0.32481239683712326', 'NSGA-II_rank: 2', 'change: 0.07605748041393481', 'is_elite: False']\n", + "Id: 33_58 Identity: {'ancestor_count': 28, 'ancestor_ids': ['32_21', '32_26'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_58', 'origin': '32_21~CUW~32_26#MGNP'} Metrics: ['ELUC: -3.8334650366177248', 'NSGA-II_crowding_distance: 0.1889133455557467', 'NSGA-II_rank: 1', 'change: 0.05946018657569259', 'is_elite: True']\n", + "Id: 33_50 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_21', '31_57'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_50', 'origin': '32_21~CUW~31_57#MGNP'} Metrics: ['ELUC: -3.9217056537542163', 'NSGA-II_crowding_distance: 0.290253514796812', 'NSGA-II_rank: 3', 'change: 0.11032826535450478', 'is_elite: False']\n", + "Id: 33_90 Identity: {'ancestor_count': 27, 'ancestor_ids': ['31_57', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_90', 'origin': '31_57~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.199103698040171', 'NSGA-II_crowding_distance: 0.1166053245123096', 'NSGA-II_rank: 2', 'change: 0.08441100730538086', 'is_elite: False']\n", + "Id: 33_59 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_86', '32_18'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_59', 'origin': '32_86~CUW~32_18#MGNP'} Metrics: ['ELUC: -4.498510835597484', 'NSGA-II_crowding_distance: 0.07197851638702082', 'NSGA-II_rank: 2', 'change: 0.09209188491558329', 'is_elite: False']\n", + "Id: 33_25 Identity: {'ancestor_count': 28, 'ancestor_ids': ['1_1', '32_26'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_25', 'origin': '1_1~CUW~32_26#MGNP'} Metrics: ['ELUC: -4.603535558416599', 'NSGA-II_crowding_distance: 0.16420199779434913', 'NSGA-II_rank: 2', 'change: 0.09660805979400122', 'is_elite: False']\n", + "Id: 33_30 Identity: {'ancestor_count': 22, 'ancestor_ids': ['32_82', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_30', 'origin': '32_82~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.703921208136676', 'NSGA-II_crowding_distance: 0.18732676049363428', 'NSGA-II_rank: 1', 'change: 0.07930025082986639', 'is_elite: False']\n", + "Id: 33_20 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_70', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_20', 'origin': '32_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.419477154265124', 'NSGA-II_crowding_distance: 0.4815400823602537', 'NSGA-II_rank: 4', 'change: 0.12739222777078607', 'is_elite: False']\n", + "Id: 33_67 Identity: {'ancestor_count': 27, 'ancestor_ids': ['30_89', '32_86'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_67', 'origin': '30_89~CUW~32_86#MGNP'} Metrics: ['ELUC: -5.697158404740293', 'NSGA-II_crowding_distance: 0.08146673139738486', 'NSGA-II_rank: 1', 'change: 0.08372686642524282', 'is_elite: False']\n", + "Id: 33_32 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_32', 'origin': '1_1~CUW~32_97#MGNP'} Metrics: ['ELUC: -5.749032653604464', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2814436443957855', 'is_elite: False']\n", + "Id: 33_84 Identity: {'ancestor_count': 31, 'ancestor_ids': ['31_57', '32_43'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_84', 'origin': '31_57~CUW~32_43#MGNP'} Metrics: ['ELUC: -5.796439262363305', 'NSGA-II_crowding_distance: 0.14827791181991773', 'NSGA-II_rank: 2', 'change: 0.11373231208904709', 'is_elite: False']\n", + "Id: 33_66 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_66', 'origin': '30_89~CUW~32_82#MGNP'} Metrics: ['ELUC: -5.810356190626065', 'NSGA-II_crowding_distance: 0.09608133468872032', 'NSGA-II_rank: 1', 'change: 0.08483156532111692', 'is_elite: False']\n", + "Id: 33_23 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '32_21'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_23', 'origin': '31_81~CUW~32_21#MGNP'} Metrics: ['ELUC: -5.846331805939566', 'NSGA-II_crowding_distance: 0.16987260327515025', 'NSGA-II_rank: 2', 'change: 0.11498421284835947', 'is_elite: False']\n", + "Id: 33_71 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '32_98'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_71', 'origin': '32_69~CUW~32_98#MGNP'} Metrics: ['ELUC: -6.107967099181727', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2594719730240084', 'is_elite: False']\n", + "Id: 33_18 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_18', 'origin': '31_81~CUW~32_82#MGNP'} Metrics: ['ELUC: -6.395170584322808', 'NSGA-II_crowding_distance: 0.2778815221288277', 'NSGA-II_rank: 4', 'change: 0.1393555277755468', 'is_elite: False']\n", + "Id: 32_26 Identity: {'ancestor_count': 27, 'ancestor_ids': ['30_84', '31_46'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_26', 'origin': '30_84~CUW~31_46#MGNP'} Metrics: ['ELUC: -6.911639113378094', 'NSGA-II_crowding_distance: 0.11691150445202927', 'NSGA-II_rank: 1', 'change: 0.09178528357407047', 'is_elite: False']\n", + "Id: 33_69 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_69', 'origin': '30_89~CUW~32_82#MGNP'} Metrics: ['ELUC: -6.946739361194406', 'NSGA-II_crowding_distance: 0.5688521051952784', 'NSGA-II_rank: 3', 'change: 0.12292325585296465', 'is_elite: False']\n", + "Id: 33_76 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_43', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_76', 'origin': '32_43~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.044781475522215', 'NSGA-II_crowding_distance: 0.40826128450542554', 'NSGA-II_rank: 5', 'change: 0.16057812554308817', 'is_elite: False']\n", + "Id: 33_55 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_67', '32_21'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_55', 'origin': '32_67~CUW~32_21#MGNP'} Metrics: ['ELUC: -7.182978761343017', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.17381759084591253', 'is_elite: False']\n", + "Id: 33_62 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_89', '32_26'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_62', 'origin': '30_89~CUW~32_26#MGNP'} Metrics: ['ELUC: -7.253858040606483', 'NSGA-II_crowding_distance: 0.07374080253489326', 'NSGA-II_rank: 1', 'change: 0.09521868156838328', 'is_elite: False']\n", + "Id: 33_11 Identity: {'ancestor_count': 27, 'ancestor_ids': ['30_89', '31_57'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_11', 'origin': '30_89~CUW~31_57#MGNP'} Metrics: ['ELUC: -7.490358825787974', 'NSGA-II_crowding_distance: 0.12579106271475934', 'NSGA-II_rank: 1', 'change: 0.10396684382804769', 'is_elite: False']\n", + "Id: 33_33 Identity: {'ancestor_count': 31, 'ancestor_ids': ['1_1', '32_69'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_33', 'origin': '1_1~CUW~32_69#MGNP'} Metrics: ['ELUC: -8.037165918781017', 'NSGA-II_crowding_distance: 0.23089412140993448', 'NSGA-II_rank: 4', 'change: 0.1491124004721692', 'is_elite: False']\n", + "Id: 33_45 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_89', '32_26'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_45', 'origin': '30_89~CUW~32_26#MGNP'} Metrics: ['ELUC: -8.334762223217174', 'NSGA-II_crowding_distance: 0.42990741912975594', 'NSGA-II_rank: 2', 'change: 0.116419868703189', 'is_elite: False']\n", + "Id: 33_81 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '32_26'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_81', 'origin': '32_69~CUW~32_26#MGNP'} Metrics: ['ELUC: -8.341451025658953', 'NSGA-II_crowding_distance: 0.24465613321396193', 'NSGA-II_rank: 5', 'change: 0.16521101239672242', 'is_elite: False']\n", + "Id: 33_13 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_98', '31_57'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_13', 'origin': '32_98~CUW~31_57#MGNP'} Metrics: ['ELUC: -8.455050138114757', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2591663134711705', 'is_elite: False']\n", + "Id: 30_89 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_89', 'origin': '29_14~CUW~29_14#MGNP'} Metrics: ['ELUC: -8.511797071769356', 'NSGA-II_crowding_distance: 0.2759116331381019', 'NSGA-II_rank: 1', 'change: 0.11140431833454958', 'is_elite: True']\n", + "Id: 33_78 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_21', '32_70'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_78', 'origin': '32_21~CUW~32_70#MGNP'} Metrics: ['ELUC: -8.815936803504941', 'NSGA-II_crowding_distance: 0.20960995047360953', 'NSGA-II_rank: 4', 'change: 0.15332385557296896', 'is_elite: False']\n", + "Id: 33_38 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_18', '32_98'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_38', 'origin': '32_18~CUW~32_98#MGNP'} Metrics: ['ELUC: -9.25497036556434', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.23489292370591514', 'is_elite: False']\n", + "Id: 33_96 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_70', '32_21'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_96', 'origin': '32_70~CUW~32_21#MGNP'} Metrics: ['ELUC: -9.364113753385944', 'NSGA-II_crowding_distance: 0.3788106010588118', 'NSGA-II_rank: 5', 'change: 0.17504875521390248', 'is_elite: False']\n", + "Id: 33_15 Identity: {'ancestor_count': 31, 'ancestor_ids': ['1_1', '32_88'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_15', 'origin': '1_1~CUW~32_88#MGNP'} Metrics: ['ELUC: -9.634019440977395', 'NSGA-II_crowding_distance: 0.23268305291852104', 'NSGA-II_rank: 4', 'change: 0.17176680346707057', 'is_elite: False']\n", + "Id: 33_61 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_61', 'origin': '31_81~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.784101603282414', 'NSGA-II_crowding_distance: 0.18262444648174897', 'NSGA-II_rank: 4', 'change: 0.19182747011444864', 'is_elite: False']\n", + "Id: 33_39 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_39', 'origin': '1_1~CUW~32_97#MGNP'} Metrics: ['ELUC: -9.812869152068348', 'NSGA-II_crowding_distance: 1.128751419552449', 'NSGA-II_rank: 5', 'change: 0.20849742502284666', 'is_elite: False']\n", + "Id: 33_19 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '32_43'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_19', 'origin': '32_69~CUW~32_43#MGNP'} Metrics: ['ELUC: -10.312615082220324', 'NSGA-II_crowding_distance: 0.5346338616352273', 'NSGA-II_rank: 3', 'change: 0.1468181629467007', 'is_elite: False']\n", + "Id: 33_43 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '32_70'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_43', 'origin': '31_81~CUW~32_70#MGNP'} Metrics: ['ELUC: -10.542137626527891', 'NSGA-II_crowding_distance: 0.8089966400881139', 'NSGA-II_rank: 4', 'change: 0.19952583233315838', 'is_elite: False']\n", + "Id: 32_21 Identity: {'ancestor_count': 26, 'ancestor_ids': ['29_57', '30_89'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_21', 'origin': '29_57~CUW~30_89#MGNP'} Metrics: ['ELUC: -10.768982042521534', 'NSGA-II_crowding_distance: 0.41129669832385185', 'NSGA-II_rank: 2', 'change: 0.14652277998312305', 'is_elite: False']\n", + "Id: 33_53 Identity: {'ancestor_count': 28, 'ancestor_ids': ['32_65', '32_18'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_53', 'origin': '32_65~CUW~32_18#MGNP'} Metrics: ['ELUC: -10.79133210153087', 'NSGA-II_crowding_distance: 0.2356683566018615', 'NSGA-II_rank: 1', 'change: 0.13027419254949799', 'is_elite: True']\n", + "Id: 33_56 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_82', '32_69'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_56', 'origin': '32_82~CUW~32_69#MGNP'} Metrics: ['ELUC: -10.943847625853355', 'NSGA-II_crowding_distance: 0.2445589469719873', 'NSGA-II_rank: 3', 'change: 0.19034327284692107', 'is_elite: False']\n", + "Id: 33_97 Identity: {'ancestor_count': 28, 'ancestor_ids': ['32_21', '32_26'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_97', 'origin': '32_21~CUW~32_26#MGNP'} Metrics: ['ELUC: -10.960547511581101', 'NSGA-II_crowding_distance: 0.1301637655099815', 'NSGA-II_rank: 1', 'change: 0.140166454337666', 'is_elite: False']\n", + "Id: 33_35 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_35', 'origin': '31_81~CUW~32_97#MGNP'} Metrics: ['ELUC: -11.06604654035491', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3202190402100344', 'is_elite: False']\n", + "Id: 33_36 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_36', 'origin': '32_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.254320214452203', 'NSGA-II_crowding_distance: 0.40872326589761865', 'NSGA-II_rank: 3', 'change: 0.1922758613431296', 'is_elite: False']\n", + "Id: 33_86 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '32_69'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_86', 'origin': '32_69~CUW~32_69#MGNP'} Metrics: ['ELUC: -11.946642649572158', 'NSGA-II_crowding_distance: 0.1058182373726741', 'NSGA-II_rank: 1', 'change: 0.1495061833667053', 'is_elite: False']\n", + "Id: 33_73 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_21', '32_21'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_73', 'origin': '32_21~CUW~32_21#MGNP'} Metrics: ['ELUC: -12.039731856422886', 'NSGA-II_crowding_distance: 0.351262980539611', 'NSGA-II_rank: 2', 'change: 0.16314622636631587', 'is_elite: False']\n", + "Id: 32_69 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '30_70'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_69', 'origin': '31_81~CUW~30_70#MGNP'} Metrics: ['ELUC: -12.120818916205838', 'NSGA-II_crowding_distance: 0.14787028591611606', 'NSGA-II_rank: 1', 'change: 0.15205009484906773', 'is_elite: False']\n", + "Id: 33_100 Identity: {'ancestor_count': 31, 'ancestor_ids': ['30_89', '32_43'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_100', 'origin': '30_89~CUW~32_43#MGNP'} Metrics: ['ELUC: -12.755843130210803', 'NSGA-II_crowding_distance: 0.18947431319900704', 'NSGA-II_rank: 1', 'change: 0.17989499977600443', 'is_elite: True']\n", + "Id: 33_94 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '31_88'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_94', 'origin': '31_81~CUW~31_88#MGNP'} Metrics: ['ELUC: -13.504374439716035', 'NSGA-II_crowding_distance: 0.5579339973171197', 'NSGA-II_rank: 3', 'change: 0.2500493655856229', 'is_elite: False']\n", + "Id: 33_70 Identity: {'ancestor_count': 28, 'ancestor_ids': ['32_65', '32_70'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_70', 'origin': '32_65~CUW~32_70#MGNP'} Metrics: ['ELUC: -13.557503959860242', 'NSGA-II_crowding_distance: 0.21985482805493273', 'NSGA-II_rank: 2', 'change: 0.1926188998971817', 'is_elite: False']\n", + "Id: 33_52 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '32_70'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_52', 'origin': '32_69~CUW~32_70#MGNP'} Metrics: ['ELUC: -13.591666439251808', 'NSGA-II_crowding_distance: 0.32088610004200996', 'NSGA-II_rank: 2', 'change: 0.1951844105995757', 'is_elite: False']\n", + "Id: 33_44 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '32_21'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_44', 'origin': '32_69~CUW~32_21#MGNP'} Metrics: ['ELUC: -13.595148885911184', 'NSGA-II_crowding_distance: 0.41973579478356104', 'NSGA-II_rank: 1', 'change: 0.1835651734267595', 'is_elite: True']\n", + "Id: 33_72 Identity: {'ancestor_count': 30, 'ancestor_ids': ['30_89', '31_81'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_72', 'origin': '30_89~CUW~31_81#MGNP'} Metrics: ['ELUC: -15.029072863104542', 'NSGA-II_crowding_distance: 0.3351488969406185', 'NSGA-II_rank: 2', 'change: 0.2524554000936593', 'is_elite: False']\n", + "Id: 33_37 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_37', 'origin': '31_81~CUW~32_97#MGNP'} Metrics: ['ELUC: -15.110279827194221', 'NSGA-II_crowding_distance: 0.2756049998232878', 'NSGA-II_rank: 3', 'change: 0.26783276894444646', 'is_elite: False']\n", + "Id: 33_14 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_82', '32_98'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_14', 'origin': '32_82~CUW~32_98#MGNP'} Metrics: ['ELUC: -15.2754246668303', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2889890684592874', 'is_elite: False']\n", + "Id: 33_34 Identity: {'ancestor_count': 31, 'ancestor_ids': ['31_81', '32_56'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_34', 'origin': '31_81~CUW~32_56#MGNP'} Metrics: ['ELUC: -15.374920483454748', 'NSGA-II_crowding_distance: 0.06266967287440708', 'NSGA-II_rank: 2', 'change: 0.25362247332858423', 'is_elite: False']\n", + "Id: 33_24 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_70', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_24', 'origin': '32_70~CUW~32_97#MGNP'} Metrics: ['ELUC: -15.37944383441115', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28868881789038', 'is_elite: False']\n", + "Id: 33_65 Identity: {'ancestor_count': 31, 'ancestor_ids': ['31_81', '32_69'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_65', 'origin': '31_81~CUW~32_69#MGNP'} Metrics: ['ELUC: -15.734338086281928', 'NSGA-II_crowding_distance: 0.13612044456817382', 'NSGA-II_rank: 2', 'change: 0.2572561506871504', 'is_elite: False']\n", + "Id: 33_48 Identity: {'ancestor_count': 31, 'ancestor_ids': ['31_81', '32_69'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_48', 'origin': '31_81~CUW~32_69#MGNP'} Metrics: ['ELUC: -15.860369092506621', 'NSGA-II_crowding_distance: 0.39106307382537486', 'NSGA-II_rank: 1', 'change: 0.25245004456874914', 'is_elite: True']\n", + "Id: 33_74 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_98', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_74', 'origin': '32_98~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.877951708929203', 'NSGA-II_crowding_distance: 0.2403887504918238', 'NSGA-II_rank: 3', 'change: 0.27964366451939365', 'is_elite: False']\n", + "Id: 31_81 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_31', '29_57'], 'birth_generation': 31, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '31_81', 'origin': '30_31~CUW~29_57#MGNP'} Metrics: ['ELUC: -15.925407357227305', 'NSGA-II_crowding_distance: 0.08018051332413646', 'NSGA-II_rank: 1', 'change: 0.26070447520141704', 'is_elite: False']\n", + "Id: 33_27 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '31_81'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_27', 'origin': '31_81~CUW~31_81#MGNP'} Metrics: ['ELUC: -16.307120811843713', 'NSGA-II_crowding_distance: 0.06027692849121973', 'NSGA-II_rank: 1', 'change: 0.26879260851997894', 'is_elite: False']\n", + "Id: 33_31 Identity: {'ancestor_count': 30, 'ancestor_ids': ['31_81', '32_70'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_31', 'origin': '31_81~CUW~32_70#MGNP'} Metrics: ['ELUC: -16.408404664368177', 'NSGA-II_crowding_distance: 0.12441467885242997', 'NSGA-II_rank: 2', 'change: 0.27226187346782227', 'is_elite: False']\n", + "Id: 33_49 Identity: {'ancestor_count': 30, 'ancestor_ids': ['32_65', '31_81'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_49', 'origin': '32_65~CUW~31_81#MGNP'} Metrics: ['ELUC: -16.432769173712384', 'NSGA-II_crowding_distance: 0.13593124153948144', 'NSGA-II_rank: 2', 'change: 0.27834907774196266', 'is_elite: False']\n", + "Id: 33_46 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_21', '32_56'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_46', 'origin': '32_21~CUW~32_56#MGNP'} Metrics: ['ELUC: -16.46472327670166', 'NSGA-II_crowding_distance: 0.13349225494500294', 'NSGA-II_rank: 1', 'change: 0.26953741000073755', 'is_elite: False']\n", + "Id: 33_83 Identity: {'ancestor_count': 22, 'ancestor_ids': ['2_49', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_83', 'origin': '2_49~CUW~32_82#MGNP'} Metrics: ['ELUC: -16.80181900823394', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2998893423372419', 'is_elite: False']\n", + "Id: 33_68 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_21', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_68', 'origin': '32_21~CUW~32_97#MGNP'} Metrics: ['ELUC: -17.131680029293914', 'NSGA-II_crowding_distance: 0.15087355518470863', 'NSGA-II_rank: 2', 'change: 0.2959632075003273', 'is_elite: False']\n", + "Id: 33_77 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_43', '32_98'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_77', 'origin': '32_43~CUW~32_98#MGNP'} Metrics: ['ELUC: -17.15736127904031', 'NSGA-II_crowding_distance: 0.17449104119088393', 'NSGA-II_rank: 1', 'change: 0.2941948796918439', 'is_elite: False']\n", + "Id: 32_98 Identity: {'ancestor_count': 30, 'ancestor_ids': ['2_49', '31_81'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_98', 'origin': '2_49~CUW~31_81#MGNP'} Metrics: ['ELUC: -17.357032944967596', 'NSGA-II_crowding_distance: 0.054621379327685245', 'NSGA-II_rank: 2', 'change: 0.3026540558981913', 'is_elite: False']\n", + "Id: 33_79 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_21', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_79', 'origin': '32_21~CUW~32_97#MGNP'} Metrics: ['ELUC: -17.579800231109935', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3028921414042052', 'is_elite: False']\n", + "Id: 33_12 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_98', '31_81'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_12', 'origin': '32_98~CUW~31_81#MGNP'} Metrics: ['ELUC: -17.58343218743461', 'NSGA-II_crowding_distance: 0.054605122960957694', 'NSGA-II_rank: 1', 'change: 0.3026168130845546', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 32_97 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 32, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '32_97', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 33_29 Identity: {'ancestor_count': 22, 'ancestor_ids': ['32_82', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_29', 'origin': '32_82~CUW~32_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 33_40 Identity: {'ancestor_count': 27, 'ancestor_ids': ['32_97', '31_57'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_40', 'origin': '32_97~CUW~31_57#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 33_57 Identity: {'ancestor_count': 3, 'ancestor_ids': ['32_97', '32_97'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_57', 'origin': '32_97~CUW~32_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 33_80 Identity: {'ancestor_count': 30, 'ancestor_ids': ['2_49', '31_81'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_80', 'origin': '2_49~CUW~31_81#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 33_93 Identity: {'ancestor_count': 31, 'ancestor_ids': ['2_49', '32_69'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_93', 'origin': '2_49~CUW~32_69#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 33_95 Identity: {'ancestor_count': 3, 'ancestor_ids': ['32_97', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_95', 'origin': '32_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 33.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 34...:\n", + "PopulationResponse:\n", + " Generation: 34\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/34/20240219-234525\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 34 and asking ESP for generation 35...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 34 data persisted.\n", + "Evaluated candidates:\n", + "Id: 34_21 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_82', '2_49'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_21', 'origin': '33_82~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 34_92 Identity: {'ancestor_count': 23, 'ancestor_ids': ['2_49', '33_30'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_92', 'origin': '2_49~CUW~33_30#MGNP'} Metrics: ['ELUC: 22.847705008027802', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.30147856143196927', 'is_elite: False']\n", + "Id: 34_15 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_95'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_15', 'origin': '33_44~CUW~33_95#MGNP'} Metrics: ['ELUC: 22.612312414444713', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3020615136059537', 'is_elite: False']\n", + "Id: 34_16 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_30', '2_49'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_16', 'origin': '33_30~CUW~2_49#MGNP'} Metrics: ['ELUC: 17.779715339716326', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28347435769967266', 'is_elite: False']\n", + "Id: 34_42 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_95', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_42', 'origin': '33_95~CUW~33_58#MGNP'} Metrics: ['ELUC: 17.60638588879379', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25840448468089616', 'is_elite: False']\n", + "Id: 34_29 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_58', '2_49'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_29', 'origin': '33_58~CUW~2_49#MGNP'} Metrics: ['ELUC: 16.091560576098537', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2832061780120663', 'is_elite: False']\n", + "Id: 34_57 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_95', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_57', 'origin': '33_95~CUW~33_58#MGNP'} Metrics: ['ELUC: 2.358188839505919', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2597088281058963', 'is_elite: False']\n", + "Id: 34_88 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_95', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_88', 'origin': '33_95~CUW~33_48#MGNP'} Metrics: ['ELUC: 1.6689377245735826', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.22232381665695733', 'is_elite: False']\n", + "Id: 34_98 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_82', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_98', 'origin': '33_82~CUW~33_53#MGNP'} Metrics: ['ELUC: 1.1208670179375815', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06933596558601517', 'is_elite: False']\n", + "Id: 34_71 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_97', '33_30'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_71', 'origin': '33_97~CUW~33_30#MGNP'} Metrics: ['ELUC: 0.28053281590117496', 'NSGA-II_crowding_distance: 0.34931211519296135', 'NSGA-II_rank: 5', 'change: 0.07307430719461025', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 34_38 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_95', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_38', 'origin': '33_95~CUW~33_58#MGNP'} Metrics: ['ELUC: -0.23823125624054128', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2237395983603793', 'is_elite: False']\n", + "Id: 34_73 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '30_89'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_73', 'origin': '33_44~CUW~30_89#MGNP'} Metrics: ['ELUC: -0.27232834748783774', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.12313600358567815', 'is_elite: False']\n", + "Id: 34_84 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '30_89'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_84', 'origin': '33_44~CUW~30_89#MGNP'} Metrics: ['ELUC: -0.4363422312088218', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.09560089646837035', 'is_elite: False']\n", + "Id: 34_23 Identity: {'ancestor_count': 29, 'ancestor_ids': ['2_49', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_23', 'origin': '2_49~CUW~33_58#MGNP'} Metrics: ['ELUC: -0.45332600646836324', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.33592227799408636', 'is_elite: False']\n", + "Id: 34_24 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_95', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_24', 'origin': '33_95~CUW~33_58#MGNP'} Metrics: ['ELUC: -0.5456859902192033', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2364474874599016', 'is_elite: False']\n", + "Id: 34_34 Identity: {'ancestor_count': 29, 'ancestor_ids': ['1_1', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_34', 'origin': '1_1~CUW~33_58#MGNP'} Metrics: ['ELUC: -0.7839371184791302', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05985233505916656', 'is_elite: False']\n", + "Id: 34_53 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '1_1'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_53', 'origin': '30_89~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8010749187169635', 'NSGA-II_crowding_distance: 0.05233840131070766', 'NSGA-II_rank: 3', 'change: 0.0603257803478898', 'is_elite: False']\n", + "Id: 34_25 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_82', '33_82'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_25', 'origin': '33_82~CUW~33_82#MGNP'} Metrics: ['ELUC: -1.030257627047968', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.0487025092493944', 'is_elite: False']\n", + "Id: 33_82 Identity: {'ancestor_count': 22, 'ancestor_ids': ['32_82', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_82', 'origin': '32_82~CUW~32_82#MGNP'} Metrics: ['ELUC: -1.159438981555866', 'NSGA-II_crowding_distance: 0.2651695360367316', 'NSGA-II_rank: 1', 'change: 0.04005765814965266', 'is_elite: True']\n", + "Id: 34_80 Identity: {'ancestor_count': 26, 'ancestor_ids': ['1_1', '30_89'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_80', 'origin': '1_1~CUW~30_89#MGNP'} Metrics: ['ELUC: -1.311449950347652', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06702553212569315', 'is_elite: False']\n", + "Id: 34_90 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_82', '1_1'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_90', 'origin': '33_82~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4985817226185423', 'NSGA-II_crowding_distance: 0.1840289319680156', 'NSGA-II_rank: 3', 'change: 0.06125315163282334', 'is_elite: False']\n", + "Id: 34_33 Identity: {'ancestor_count': 28, 'ancestor_ids': ['33_41', '33_30'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_33', 'origin': '33_41~CUW~33_30#MGNP'} Metrics: ['ELUC: -1.5177146487318387', 'NSGA-II_crowding_distance: 0.24115252213553587', 'NSGA-II_rank: 2', 'change: 0.05150458665312349', 'is_elite: False']\n", + "Id: 34_43 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_42'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_43', 'origin': '33_44~CUW~33_42#MGNP'} Metrics: ['ELUC: -1.9782416068198623', 'NSGA-II_crowding_distance: 0.6894350458350109', 'NSGA-II_rank: 6', 'change: 0.10883139009347241', 'is_elite: False']\n", + "Id: 34_56 Identity: {'ancestor_count': 28, 'ancestor_ids': ['33_41', '33_42'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_56', 'origin': '33_41~CUW~33_42#MGNP'} Metrics: ['ELUC: -1.9874568910168877', 'NSGA-II_crowding_distance: 0.15238426928379362', 'NSGA-II_rank: 4', 'change: 0.07623434537889033', 'is_elite: False']\n", + "Id: 34_49 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_30', '33_82'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_49', 'origin': '33_30~CUW~33_82#MGNP'} Metrics: ['ELUC: -2.1511368058543368', 'NSGA-II_crowding_distance: 0.21711264450646914', 'NSGA-II_rank: 1', 'change: 0.04751333655808081', 'is_elite: True']\n", + "Id: 34_68 Identity: {'ancestor_count': 28, 'ancestor_ids': ['33_11', '1_1'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_68', 'origin': '33_11~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.1635133184345205', 'NSGA-II_crowding_distance: 0.6366853823701811', 'NSGA-II_rank: 5', 'change: 0.09177357920178554', 'is_elite: False']\n", + "Id: 34_22 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '1_1'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_22', 'origin': '33_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2011861709150056', 'NSGA-II_crowding_distance: 1.1578278913000108', 'NSGA-II_rank: 6', 'change: 0.16481451781907802', 'is_elite: False']\n", + "Id: 34_32 Identity: {'ancestor_count': 26, 'ancestor_ids': ['1_1', '30_89'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_32', 'origin': '1_1~CUW~30_89#MGNP'} Metrics: ['ELUC: -2.7053368528856243', 'NSGA-II_crowding_distance: 0.3249461582072982', 'NSGA-II_rank: 4', 'change: 0.07811965454522514', 'is_elite: False']\n", + "Id: 34_19 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '1_1'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_19', 'origin': '33_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.0358737998410805', 'NSGA-II_crowding_distance: 0.9029712981119881', 'NSGA-II_rank: 5', 'change: 0.15917130054204093', 'is_elite: False']\n", + "Id: 34_31 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_53', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_31', 'origin': '33_53~CUW~33_58#MGNP'} Metrics: ['ELUC: -3.192510537623331', 'NSGA-II_crowding_distance: 0.26371634784439235', 'NSGA-II_rank: 3', 'change: 0.06708479003646095', 'is_elite: False']\n", + "Id: 34_47 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_53', '1_1'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_47', 'origin': '33_53~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.617169269794523', 'NSGA-II_crowding_distance: 0.30150508797768205', 'NSGA-II_rank: 2', 'change: 0.06578853486119862', 'is_elite: False']\n", + "Id: 34_13 Identity: {'ancestor_count': 32, 'ancestor_ids': ['1_1', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_13', 'origin': '1_1~CUW~33_48#MGNP'} Metrics: ['ELUC: -3.6454660608336362', 'NSGA-II_crowding_distance: 0.4889829830586935', 'NSGA-II_rank: 4', 'change: 0.12347113705356969', 'is_elite: False']\n", + "Id: 34_86 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_100', '1_1'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_86', 'origin': '33_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.736565278563039', 'NSGA-II_crowding_distance: 0.23202557512274', 'NSGA-II_rank: 3', 'change: 0.08890364639966955', 'is_elite: False']\n", + "Id: 33_58 Identity: {'ancestor_count': 28, 'ancestor_ids': ['32_21', '32_26'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_58', 'origin': '32_21~CUW~32_26#MGNP'} Metrics: ['ELUC: -3.8334650366177248', 'NSGA-II_crowding_distance: 0.19121391907415608', 'NSGA-II_rank: 1', 'change: 0.05946018657569259', 'is_elite: False']\n", + "Id: 34_28 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_89', '33_42'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_28', 'origin': '30_89~CUW~33_42#MGNP'} Metrics: ['ELUC: -3.8636234644994563', 'NSGA-II_crowding_distance: 0.2610038361241239', 'NSGA-II_rank: 2', 'change: 0.08688231444069414', 'is_elite: False']\n", + "Id: 34_100 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_100', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_100', 'origin': '33_100~CUW~33_53#MGNP'} Metrics: ['ELUC: -3.8939058018079677', 'NSGA-II_crowding_distance: 0.3910783988474411', 'NSGA-II_rank: 3', 'change: 0.11056588836025466', 'is_elite: False']\n", + "Id: 34_44 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_58', '33_100'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_44', 'origin': '33_58~CUW~33_100#MGNP'} Metrics: ['ELUC: -4.274529603726422', 'NSGA-II_crowding_distance: 0.24690441908724564', 'NSGA-II_rank: 1', 'change: 0.06853267854643033', 'is_elite: True']\n", + "Id: 34_78 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_100', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_78', 'origin': '33_100~CUW~33_58#MGNP'} Metrics: ['ELUC: -5.832743048930462', 'NSGA-II_crowding_distance: 0.19675438649779822', 'NSGA-II_rank: 2', 'change: 0.09349871747894892', 'is_elite: False']\n", + "Id: 34_97 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_100', '33_82'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_97', 'origin': '33_100~CUW~33_82#MGNP'} Metrics: ['ELUC: -5.871606593174884', 'NSGA-II_crowding_distance: 0.20667902631128016', 'NSGA-II_rank: 2', 'change: 0.1024421692478363', 'is_elite: False']\n", + "Id: 34_76 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_97', '33_44'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_76', 'origin': '33_97~CUW~33_44#MGNP'} Metrics: ['ELUC: -6.05343534181428', 'NSGA-II_crowding_distance: 0.4774321210135047', 'NSGA-II_rank: 4', 'change: 0.13389717609779042', 'is_elite: False']\n", + "Id: 34_91 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_53', '33_82'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_91', 'origin': '33_53~CUW~33_82#MGNP'} Metrics: ['ELUC: -6.722828080723802', 'NSGA-II_crowding_distance: 0.3846781075846901', 'NSGA-II_rank: 1', 'change: 0.08409758154423877', 'is_elite: True']\n", + "Id: 34_20 Identity: {'ancestor_count': 29, 'ancestor_ids': ['30_89', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_20', 'origin': '30_89~CUW~33_53#MGNP'} Metrics: ['ELUC: -7.674355279254145', 'NSGA-II_crowding_distance: 0.18945558698904155', 'NSGA-II_rank: 2', 'change: 0.11406596328760754', 'is_elite: False']\n", + "Id: 34_65 Identity: {'ancestor_count': 28, 'ancestor_ids': ['30_89', '33_42'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_65', 'origin': '30_89~CUW~33_42#MGNP'} Metrics: ['ELUC: -7.752252917861319', 'NSGA-II_crowding_distance: 0.5231628535520206', 'NSGA-II_rank: 3', 'change: 0.11937875541488684', 'is_elite: False']\n", + "Id: 34_52 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_58', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_52', 'origin': '33_58~CUW~33_53#MGNP'} Metrics: ['ELUC: -7.795695238659966', 'NSGA-II_crowding_distance: 0.12526760391045902', 'NSGA-II_rank: 2', 'change: 0.11757320919836604', 'is_elite: False']\n", + "Id: 34_60 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_48', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_60', 'origin': '33_48~CUW~33_58#MGNP'} Metrics: ['ELUC: -8.246690804880108', 'NSGA-II_crowding_distance: 0.4211420108732689', 'NSGA-II_rank: 4', 'change: 0.1540307044517339', 'is_elite: False']\n", + "Id: 30_89 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_89', 'origin': '29_14~CUW~29_14#MGNP'} Metrics: ['ELUC: -8.511797071769356', 'NSGA-II_crowding_distance: 0.27404493927015194', 'NSGA-II_rank: 1', 'change: 0.11140431833454958', 'is_elite: True']\n", + "Id: 34_83 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_42'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_83', 'origin': '33_44~CUW~33_42#MGNP'} Metrics: ['ELUC: -8.80808535332908', 'NSGA-II_crowding_distance: 1.310564954164989', 'NSGA-II_rank: 6', 'change: 0.16875432325401668', 'is_elite: False']\n", + "Id: 34_51 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_58', '30_89'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_51', 'origin': '33_58~CUW~30_89#MGNP'} Metrics: ['ELUC: -8.823162739825195', 'NSGA-II_crowding_distance: 0.13196594532799', 'NSGA-II_rank: 2', 'change: 0.12601724538029854', 'is_elite: False']\n", + "Id: 34_67 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '30_89'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_67', 'origin': '30_89~CUW~30_89#MGNP'} Metrics: ['ELUC: -9.137193713170323', 'NSGA-II_crowding_distance: 0.14763178517600697', 'NSGA-II_rank: 2', 'change: 0.1280927858238789', 'is_elite: False']\n", + "Id: 34_17 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_11', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_17', 'origin': '33_11~CUW~33_53#MGNP'} Metrics: ['ELUC: -9.295238576645264', 'NSGA-II_crowding_distance: 0.1835122744857859', 'NSGA-II_rank: 1', 'change: 0.12221188530912361', 'is_elite: False']\n", + "Id: 34_77 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_48', '33_42'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_77', 'origin': '33_48~CUW~33_42#MGNP'} Metrics: ['ELUC: -9.608572270778586', 'NSGA-II_crowding_distance: 0.5738204414951186', 'NSGA-II_rank: 5', 'change: 0.16746668709826637', 'is_elite: False']\n", + "Id: 34_58 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_58', 'origin': '32_69~CUW~33_58#MGNP'} Metrics: ['ELUC: -9.801997764797504', 'NSGA-II_crowding_distance: 0.21045017026209928', 'NSGA-II_rank: 5', 'change: 0.17282315082980493', 'is_elite: False']\n", + "Id: 34_40 Identity: {'ancestor_count': 32, 'ancestor_ids': ['30_89', '33_44'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_40', 'origin': '30_89~CUW~33_44#MGNP'} Metrics: ['ELUC: -9.874213053421508', 'NSGA-II_crowding_distance: 0.37628047409558957', 'NSGA-II_rank: 4', 'change: 0.16512268977106853', 'is_elite: False']\n", + "Id: 34_35 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_30', '33_95'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_35', 'origin': '33_30~CUW~33_95#MGNP'} Metrics: ['ELUC: -9.888200664830492', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2332803213895059', 'is_elite: False']\n", + "Id: 34_45 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_97', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_45', 'origin': '33_97~CUW~33_53#MGNP'} Metrics: ['ELUC: -10.060830934888225', 'NSGA-II_crowding_distance: 0.3770111824090734', 'NSGA-II_rank: 3', 'change: 0.13932242757468172', 'is_elite: False']\n", + "Id: 34_93 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_82', '33_44'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_93', 'origin': '33_82~CUW~33_44#MGNP'} Metrics: ['ELUC: -10.091145735222241', 'NSGA-II_crowding_distance: 0.20923642226392092', 'NSGA-II_rank: 3', 'change: 0.17191045868273105', 'is_elite: False']\n", + "Id: 34_64 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_53', '33_97'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_64', 'origin': '33_53~CUW~33_97#MGNP'} Metrics: ['ELUC: -10.591928162839007', 'NSGA-II_crowding_distance: 0.3845178581130258', 'NSGA-II_rank: 2', 'change: 0.1335574277625101', 'is_elite: False']\n", + "Id: 34_81 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_53', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_81', 'origin': '33_53~CUW~33_53#MGNP'} Metrics: ['ELUC: -10.633380009378442', 'NSGA-II_crowding_distance: 0.11211117249795216', 'NSGA-II_rank: 1', 'change: 0.13015637510011355', 'is_elite: False']\n", + "Id: 34_87 Identity: {'ancestor_count': 32, 'ancestor_ids': ['1_1', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_87', 'origin': '1_1~CUW~33_48#MGNP'} Metrics: ['ELUC: -10.646491661032801', 'NSGA-II_crowding_distance: 0.7090833537830855', 'NSGA-II_rank: 5', 'change: 0.19691195180616503', 'is_elite: False']\n", + "Id: 33_53 Identity: {'ancestor_count': 28, 'ancestor_ids': ['32_65', '32_18'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_53', 'origin': '32_65~CUW~32_18#MGNP'} Metrics: ['ELUC: -10.79133210153087', 'NSGA-II_crowding_distance: 0.06752373288372393', 'NSGA-II_rank: 1', 'change: 0.13027419254949799', 'is_elite: False']\n", + "Id: 34_94 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_48', '33_42'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_94', 'origin': '33_48~CUW~33_42#MGNP'} Metrics: ['ELUC: -10.941150342622253', 'NSGA-II_crowding_distance: 0.2844090034502292', 'NSGA-II_rank: 4', 'change: 0.1948347083993324', 'is_elite: False']\n", + "Id: 34_39 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_53', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_39', 'origin': '33_53~CUW~33_53#MGNP'} Metrics: ['ELUC: -10.99217956393319', 'NSGA-II_crowding_distance: 0.09587796171814865', 'NSGA-II_rank: 1', 'change: 0.14421501317259985', 'is_elite: False']\n", + "Id: 34_70 Identity: {'ancestor_count': 31, 'ancestor_ids': ['33_97', '32_69'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_70', 'origin': '33_97~CUW~32_69#MGNP'} Metrics: ['ELUC: -11.11924307232212', 'NSGA-II_crowding_distance: 0.27139958856114466', 'NSGA-II_rank: 3', 'change: 0.17209771567709398', 'is_elite: False']\n", + "Id: 34_30 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_48', '33_30'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_30', 'origin': '33_48~CUW~33_30#MGNP'} Metrics: ['ELUC: -11.191510075021194', 'NSGA-II_crowding_distance: 0.15633101107397462', 'NSGA-II_rank: 1', 'change: 0.15209089609356807', 'is_elite: False']\n", + "Id: 34_61 Identity: {'ancestor_count': 32, 'ancestor_ids': ['1_1', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_61', 'origin': '1_1~CUW~33_48#MGNP'} Metrics: ['ELUC: -11.237513874468352', 'NSGA-II_crowding_distance: 0.2603944319213912', 'NSGA-II_rank: 4', 'change: 0.20804310862982853', 'is_elite: False']\n", + "Id: 34_41 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_77', '33_82'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_41', 'origin': '33_77~CUW~33_82#MGNP'} Metrics: ['ELUC: -11.247498617302284', 'NSGA-II_crowding_distance: 0.4201339441090043', 'NSGA-II_rank: 4', 'change: 0.25102796683191136', 'is_elite: False']\n", + "Id: 34_89 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_100', '2_49'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_89', 'origin': '33_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.075834993668993', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2927442050879739', 'is_elite: False']\n", + "Id: 34_36 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '2_49'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_36', 'origin': '33_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.119538026213503', 'NSGA-II_crowding_distance: 0.4708836434227328', 'NSGA-II_rank: 4', 'change: 0.29175195785841046', 'is_elite: False']\n", + "Id: 34_63 Identity: {'ancestor_count': 32, 'ancestor_ids': ['30_89', '33_46'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_63', 'origin': '30_89~CUW~33_46#MGNP'} Metrics: ['ELUC: -12.16360201457975', 'NSGA-II_crowding_distance: 0.2565523058562137', 'NSGA-II_rank: 3', 'change: 0.203852712386446', 'is_elite: False']\n", + "Id: 34_59 Identity: {'ancestor_count': 32, 'ancestor_ids': ['30_89', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_59', 'origin': '30_89~CUW~33_48#MGNP'} Metrics: ['ELUC: -12.219808607018638', 'NSGA-II_crowding_distance: 0.33519637874636', 'NSGA-II_rank: 2', 'change: 0.1717783535646874', 'is_elite: False']\n", + "Id: 34_69 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_46', '33_44'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_69', 'origin': '33_46~CUW~33_44#MGNP'} Metrics: ['ELUC: -12.439050976269643', 'NSGA-II_crowding_distance: 0.14977963096977165', 'NSGA-II_rank: 1', 'change: 0.1663068491958523', 'is_elite: False']\n", + "Id: 34_75 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_11', '33_46'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_75', 'origin': '33_11~CUW~33_46#MGNP'} Metrics: ['ELUC: -12.603299247121841', 'NSGA-II_crowding_distance: 0.4759824488450344', 'NSGA-II_rank: 3', 'change: 0.20946982023089963', 'is_elite: False']\n", + "Id: 33_100 Identity: {'ancestor_count': 31, 'ancestor_ids': ['30_89', '32_43'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_100', 'origin': '30_89~CUW~32_43#MGNP'} Metrics: ['ELUC: -12.755843130210803', 'NSGA-II_crowding_distance: 0.24370664332925185', 'NSGA-II_rank: 2', 'change: 0.17989499977600443', 'is_elite: False']\n", + "Id: 34_37 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_37', 'origin': '33_44~CUW~33_48#MGNP'} Metrics: ['ELUC: -12.818305520723985', 'NSGA-II_crowding_distance: 0.08132701451999391', 'NSGA-II_rank: 1', 'change: 0.16917458000231383', 'is_elite: False']\n", + "Id: 34_85 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_53'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_85', 'origin': '33_44~CUW~33_53#MGNP'} Metrics: ['ELUC: -13.18295884364811', 'NSGA-II_crowding_distance: 0.09241261462095599', 'NSGA-II_rank: 1', 'change: 0.1779486721471976', 'is_elite: False']\n", + "Id: 33_44 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '32_21'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_44', 'origin': '32_69~CUW~32_21#MGNP'} Metrics: ['ELUC: -13.595148885911184', 'NSGA-II_crowding_distance: 0.1483284252517167', 'NSGA-II_rank: 1', 'change: 0.1835651734267595', 'is_elite: False']\n", + "Id: 34_48 Identity: {'ancestor_count': 31, 'ancestor_ids': ['32_69', '2_49'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_48', 'origin': '32_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.948976935365378', 'NSGA-II_crowding_distance: 0.5918515970076811', 'NSGA-II_rank: 3', 'change: 0.2878151638865412', 'is_elite: False']\n", + "Id: 34_46 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_46'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_46', 'origin': '33_44~CUW~33_46#MGNP'} Metrics: ['ELUC: -13.998701251780318', 'NSGA-II_crowding_distance: 0.5188643335709158', 'NSGA-II_rank: 2', 'change: 0.2022247860167564', 'is_elite: False']\n", + "Id: 34_50 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_100'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_50', 'origin': '33_44~CUW~33_100#MGNP'} Metrics: ['ELUC: -14.366995534352572', 'NSGA-II_crowding_distance: 0.27144648437359087', 'NSGA-II_rank: 1', 'change: 0.20211310112703576', 'is_elite: True']\n", + "Id: 34_82 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_95'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_82', 'origin': '33_44~CUW~33_95#MGNP'} Metrics: ['ELUC: -14.516734563866448', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.3039324482040546', 'is_elite: False']\n", + "Id: 34_12 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_95', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_12', 'origin': '33_95~CUW~33_58#MGNP'} Metrics: ['ELUC: -14.866432903917573', 'NSGA-II_crowding_distance: 0.2536380878591299', 'NSGA-II_rank: 1', 'change: 0.24298467345426136', 'is_elite: True']\n", + "Id: 34_11 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_42', '33_77'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_11', 'origin': '33_42~CUW~33_77#MGNP'} Metrics: ['ELUC: -15.116755551889048', 'NSGA-II_crowding_distance: 0.5083925126557042', 'NSGA-II_rank: 2', 'change: 0.26722046351060647', 'is_elite: False']\n", + "Id: 33_48 Identity: {'ancestor_count': 31, 'ancestor_ids': ['31_81', '32_69'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_48', 'origin': '31_81~CUW~32_69#MGNP'} Metrics: ['ELUC: -15.860369092506621', 'NSGA-II_crowding_distance: 0.11622230767933112', 'NSGA-II_rank: 1', 'change: 0.25245004456874914', 'is_elite: False']\n", + "Id: 34_96 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_53', '33_46'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_96', 'origin': '33_53~CUW~33_46#MGNP'} Metrics: ['ELUC: -15.96819188626734', 'NSGA-II_crowding_distance: 0.06539769785305631', 'NSGA-II_rank: 1', 'change: 0.2589656305215901', 'is_elite: False']\n", + "Id: 34_79 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_48', '33_95'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_79', 'origin': '33_48~CUW~33_95#MGNP'} Metrics: ['ELUC: -16.209638220856366', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29292457950094625', 'is_elite: False']\n", + "Id: 34_74 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_46', '2_49'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_74', 'origin': '33_46~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.24867455232535', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.28878629662661764', 'is_elite: False']\n", + "Id: 34_66 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_46', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_66', 'origin': '33_46~CUW~33_48#MGNP'} Metrics: ['ELUC: -16.26671161073897', 'NSGA-II_crowding_distance: 0.0453879825546504', 'NSGA-II_rank: 1', 'change: 0.26506750242328714', 'is_elite: False']\n", + "Id: 34_27 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_46', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_27', 'origin': '33_46~CUW~33_48#MGNP'} Metrics: ['ELUC: -16.341507138554537', 'NSGA-II_crowding_distance: 0.021581474819340737', 'NSGA-II_rank: 1', 'change: 0.26617311814117006', 'is_elite: False']\n", + "Id: 34_72 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_58', '33_48'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_72', 'origin': '33_58~CUW~33_48#MGNP'} Metrics: ['ELUC: -16.45214923947345', 'NSGA-II_crowding_distance: 0.05617930837071526', 'NSGA-II_rank: 1', 'change: 0.2683599998471383', 'is_elite: False']\n", + "Id: 34_99 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_48', '33_77'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_99', 'origin': '33_48~CUW~33_77#MGNP'} Metrics: ['ELUC: -16.582821821457884', 'NSGA-II_crowding_distance: 0.13586444707897338', 'NSGA-II_rank: 1', 'change: 0.2788405872335736', 'is_elite: False']\n", + "Id: 34_18 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_58', '33_95'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_18', 'origin': '33_58~CUW~33_95#MGNP'} Metrics: ['ELUC: -17.03373704968284', 'NSGA-II_crowding_distance: 0.09906097865579654', 'NSGA-II_rank: 1', 'change: 0.299029198665172', 'is_elite: False']\n", + "Id: 34_95 Identity: {'ancestor_count': 29, 'ancestor_ids': ['2_49', '33_97'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_95', 'origin': '2_49~CUW~33_97#MGNP'} Metrics: ['ELUC: -17.084287708078342', 'NSGA-II_crowding_distance: 0.03273559384315077', 'NSGA-II_rank: 1', 'change: 0.2998881449968132', 'is_elite: False']\n", + "Id: 34_55 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_77'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_55', 'origin': '33_44~CUW~33_77#MGNP'} Metrics: ['ELUC: -17.514208483804303', 'NSGA-II_crowding_distance: 0.039680468496795254', 'NSGA-II_rank: 1', 'change: 0.3006430220318423', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 33_95 Identity: {'ancestor_count': 3, 'ancestor_ids': ['32_97', '1_1'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_95', 'origin': '32_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 34_14 Identity: {'ancestor_count': 4, 'ancestor_ids': ['33_95', '33_95'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_14', 'origin': '33_95~CUW~33_95#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 34_26 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_86', '33_77'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_26', 'origin': '33_86~CUW~33_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 34_54 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_77'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_54', 'origin': '33_44~CUW~33_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 34_62 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_100', '33_95'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_62', 'origin': '33_100~CUW~33_95#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 34.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 35...:\n", + "PopulationResponse:\n", + " Generation: 35\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/35/20240219-235239\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 35 and asking ESP for generation 36...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 35 data persisted.\n", + "Evaluated candidates:\n", + "Id: 35_96 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_96', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 23.83149939835274', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.30378813400790916', 'is_elite: False']\n", + "Id: 35_45 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_81', '34_62'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_45', 'origin': '34_81~CUW~34_62#MGNP'} Metrics: ['ELUC: 18.84087561894233', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2816311032162721', 'is_elite: False']\n", + "Id: 35_40 Identity: {'ancestor_count': 32, 'ancestor_ids': ['2_49', '33_44'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_40', 'origin': '2_49~CUW~33_44#MGNP'} Metrics: ['ELUC: 12.697251229584884', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.29334258473580843', 'is_elite: False']\n", + "Id: 35_19 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '33_48'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_19', 'origin': '34_44~CUW~33_48#MGNP'} Metrics: ['ELUC: 7.296113747724554', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.13550317457478436', 'is_elite: False']\n", + "Id: 35_37 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_69', '34_12'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_37', 'origin': '34_69~CUW~34_12#MGNP'} Metrics: ['ELUC: 6.9089399707982615', 'NSGA-II_crowding_distance: 1.211139419249039', 'NSGA-II_rank: 8', 'change: 0.20187676939008267', 'is_elite: False']\n", + "Id: 35_70 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_70', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 3.394748733862662', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26822530261152594', 'is_elite: False']\n", + "Id: 35_23 Identity: {'ancestor_count': 29, 'ancestor_ids': ['1_1', '33_58'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_23', 'origin': '1_1~CUW~33_58#MGNP'} Metrics: ['ELUC: 2.5796671114892424', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.058582463544095804', 'is_elite: False']\n", + "Id: 35_72 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '34_62'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_72', 'origin': '34_44~CUW~34_62#MGNP'} Metrics: ['ELUC: 0.7375948471240005', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3118070604226802', 'is_elite: False']\n", + "Id: 35_89 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '34_62'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_89', 'origin': '34_50~CUW~34_62#MGNP'} Metrics: ['ELUC: 0.36304084603638304', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27871695618697406', 'is_elite: False']\n", + "Id: 35_12 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_82', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_12', 'origin': '33_82~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.3544179132941578', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07748571056166226', 'is_elite: False']\n", + "Id: 35_82 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_49', '34_12'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_82', 'origin': '34_49~CUW~34_12#MGNP'} Metrics: ['ELUC: 0.258303755711873', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2636640210605975', 'is_elite: False']\n", + "Id: 35_56 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_69', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_56', 'origin': '34_69~CUW~33_82#MGNP'} Metrics: ['ELUC: 0.024429385853996153', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.13477058100661257', 'is_elite: False']\n", + "Id: 35_97 Identity: {'ancestor_count': 33, 'ancestor_ids': ['33_82', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_97', 'origin': '33_82~CUW~34_50#MGNP'} Metrics: ['ELUC: 0.007252267517960803', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10614706275779612', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 35_73 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_73', 'origin': '34_62~CUW~34_91#MGNP'} Metrics: ['ELUC: -0.0422449637147517', 'NSGA-II_crowding_distance: 1.519850773334815', 'NSGA-II_rank: 8', 'change: 0.23964946177359783', 'is_elite: False']\n", + "Id: 35_69 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_69', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.10880550382266538', 'NSGA-II_crowding_distance: 0.15873026439854399', 'NSGA-II_rank: 1', 'change: 0.028552223089241234', 'is_elite: False']\n", + "Id: 35_46 Identity: {'ancestor_count': 29, 'ancestor_ids': ['1_1', '33_58'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_46', 'origin': '1_1~CUW~33_58#MGNP'} Metrics: ['ELUC: -0.6950577112185036', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04309880690129704', 'is_elite: False']\n", + "Id: 35_52 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_52', 'origin': '34_44~CUW~33_82#MGNP'} Metrics: ['ELUC: -0.8010073863966902', 'NSGA-II_crowding_distance: 0.21389941897674897', 'NSGA-II_rank: 3', 'change: 0.06270440921095119', 'is_elite: False']\n", + "Id: 33_82 Identity: {'ancestor_count': 22, 'ancestor_ids': ['32_82', '32_82'], 'birth_generation': 33, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '33_82', 'origin': '32_82~CUW~32_82#MGNP'} Metrics: ['ELUC: -1.159438981555866', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04005765814965266', 'is_elite: False']\n", + "Id: 35_90 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_90', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.195851539473917', 'NSGA-II_crowding_distance: 0.17970546211152372', 'NSGA-II_rank: 1', 'change: 0.03196571532584666', 'is_elite: False']\n", + "Id: 35_92 Identity: {'ancestor_count': 29, 'ancestor_ids': ['1_1', '33_58'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_92', 'origin': '1_1~CUW~33_58#MGNP'} Metrics: ['ELUC: -1.490079273342722', 'NSGA-II_crowding_distance: 0.38824335332549176', 'NSGA-II_rank: 4', 'change: 0.06777241376333636', 'is_elite: False']\n", + "Id: 35_44 Identity: {'ancestor_count': 24, 'ancestor_ids': ['34_49', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_44', 'origin': '34_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5453927889697945', 'NSGA-II_crowding_distance: 0.18348246581857913', 'NSGA-II_rank: 2', 'change: 0.0536249011919823', 'is_elite: False']\n", + "Id: 35_95 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '34_44'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_95', 'origin': '34_50~CUW~34_44#MGNP'} Metrics: ['ELUC: -1.747448051283553', 'NSGA-II_crowding_distance: 0.1372087512471742', 'NSGA-II_rank: 4', 'change: 0.08260760388247691', 'is_elite: False']\n", + "Id: 35_81 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_69', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_81', 'origin': '34_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.7942332669523726', 'NSGA-II_crowding_distance: 0.7662643418537464', 'NSGA-II_rank: 6', 'change: 0.12281547882816544', 'is_elite: False']\n", + "Id: 35_98 Identity: {'ancestor_count': 33, 'ancestor_ids': ['33_82', '34_30'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_98', 'origin': '33_82~CUW~34_30#MGNP'} Metrics: ['ELUC: -1.9829060388856', 'NSGA-II_crowding_distance: 0.4368511548043098', 'NSGA-II_rank: 3', 'change: 0.06657748562030073', 'is_elite: False']\n", + "Id: 34_49 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_30', '33_82'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_49', 'origin': '33_30~CUW~33_82#MGNP'} Metrics: ['ELUC: -2.1511368058543368', 'NSGA-II_crowding_distance: 0.1321137186031414', 'NSGA-II_rank: 1', 'change: 0.04751333655808081', 'is_elite: False']\n", + "Id: 35_17 Identity: {'ancestor_count': 33, 'ancestor_ids': ['1_1', '34_44'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_17', 'origin': '1_1~CUW~34_44#MGNP'} Metrics: ['ELUC: -2.2177507079573187', 'NSGA-II_crowding_distance: 0.0624381751872562', 'NSGA-II_rank: 1', 'change: 0.05404356091431903', 'is_elite: False']\n", + "Id: 35_74 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_74', 'origin': '34_50~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.387743256809557', 'NSGA-II_crowding_distance: 0.7621808998701947', 'NSGA-II_rank: 5', 'change: 0.1043319850524273', 'is_elite: False']\n", + "Id: 35_14 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_14', 'origin': '34_44~CUW~33_82#MGNP'} Metrics: ['ELUC: -2.511160925598841', 'NSGA-II_crowding_distance: 0.14271340410354105', 'NSGA-II_rank: 4', 'change: 0.08336444235171274', 'is_elite: False']\n", + "Id: 35_65 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_91', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_65', 'origin': '34_91~CUW~33_82#MGNP'} Metrics: ['ELUC: -2.6896264340142877', 'NSGA-II_crowding_distance: 0.20690353266465575', 'NSGA-II_rank: 2', 'change: 0.057256172456991314', 'is_elite: False']\n", + "Id: 35_93 Identity: {'ancestor_count': 30, 'ancestor_ids': ['33_82', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_93', 'origin': '33_82~CUW~34_91#MGNP'} Metrics: ['ELUC: -2.795001003409311', 'NSGA-II_crowding_distance: 0.10405249928661947', 'NSGA-II_rank: 1', 'change: 0.05521692270931534', 'is_elite: False']\n", + "Id: 35_94 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_94', 'origin': '34_62~CUW~34_91#MGNP'} Metrics: ['ELUC: -3.0137501339515245', 'NSGA-II_crowding_distance: 1.4088522794162148', 'NSGA-II_rank: 7', 'change: 0.1758957685851178', 'is_elite: False']\n", + "Id: 35_58 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_58', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_58', 'origin': '33_58~CUW~33_82#MGNP'} Metrics: ['ELUC: -3.298420855943731', 'NSGA-II_crowding_distance: 0.09557971264287056', 'NSGA-II_rank: 1', 'change: 0.06675120238712241', 'is_elite: False']\n", + "Id: 35_67 Identity: {'ancestor_count': 30, 'ancestor_ids': ['33_82', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_67', 'origin': '33_82~CUW~34_91#MGNP'} Metrics: ['ELUC: -3.5483060228519765', 'NSGA-II_crowding_distance: 0.13203459177267957', 'NSGA-II_rank: 2', 'change: 0.06820683694944644', 'is_elite: False']\n", + "Id: 35_13 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '33_58'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_13', 'origin': '34_44~CUW~33_58#MGNP'} Metrics: ['ELUC: -3.7243761264190285', 'NSGA-II_crowding_distance: 0.14189917949457606', 'NSGA-II_rank: 4', 'change: 0.08604008414815603', 'is_elite: False']\n", + "Id: 35_63 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_30', '33_58'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_63', 'origin': '34_30~CUW~33_58#MGNP'} Metrics: ['ELUC: -3.7740273297779745', 'NSGA-II_crowding_distance: 0.08372154957131162', 'NSGA-II_rank: 2', 'change: 0.06992243572836856', 'is_elite: False']\n", + "Id: 35_62 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_91', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_62', 'origin': '34_91~CUW~33_82#MGNP'} Metrics: ['ELUC: -3.783584606722864', 'NSGA-II_crowding_distance: 0.061486972822582864', 'NSGA-II_rank: 1', 'change: 0.0669592105101986', 'is_elite: False']\n", + "Id: 35_47 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '34_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_47', 'origin': '34_44~CUW~34_49#MGNP'} Metrics: ['ELUC: -3.961530095255865', 'NSGA-II_crowding_distance: 0.20545250240718452', 'NSGA-II_rank: 4', 'change: 0.09397815548442708', 'is_elite: False']\n", + "Id: 35_88 Identity: {'ancestor_count': 30, 'ancestor_ids': ['33_58', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_88', 'origin': '33_58~CUW~34_91#MGNP'} Metrics: ['ELUC: -4.078801443573365', 'NSGA-II_crowding_distance: 0.19433930487599646', 'NSGA-II_rank: 2', 'change: 0.07896366474120502', 'is_elite: False']\n", + "Id: 34_44 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_58', '33_100'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_44', 'origin': '33_58~CUW~33_100#MGNP'} Metrics: ['ELUC: -4.274529603726422', 'NSGA-II_crowding_distance: 0.19194536881746382', 'NSGA-II_rank: 1', 'change: 0.06853267854643033', 'is_elite: False']\n", + "Id: 35_33 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_17', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_33', 'origin': '34_17~CUW~33_82#MGNP'} Metrics: ['ELUC: -4.895349838932608', 'NSGA-II_crowding_distance: 0.24160438082104035', 'NSGA-II_rank: 4', 'change: 0.1143895552489845', 'is_elite: False']\n", + "Id: 35_55 Identity: {'ancestor_count': 32, 'ancestor_ids': ['1_1', '33_48'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_55', 'origin': '1_1~CUW~33_48#MGNP'} Metrics: ['ELUC: -5.302067734081978', 'NSGA-II_crowding_distance: 1.5773330468517504', 'NSGA-II_rank: 6', 'change: 0.14377746994466714', 'is_elite: False']\n", + "Id: 35_25 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_91', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_25', 'origin': '34_91~CUW~30_89#MGNP'} Metrics: ['ELUC: -5.425233925928204', 'NSGA-II_crowding_distance: 0.4399449739439065', 'NSGA-II_rank: 3', 'change: 0.08171684538523281', 'is_elite: False']\n", + "Id: 35_27 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_17', '1_1'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_27', 'origin': '34_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.633344816852428', 'NSGA-II_crowding_distance: 0.31039183702254997', 'NSGA-II_rank: 4', 'change: 0.12319644421841973', 'is_elite: False']\n", + "Id: 35_64 Identity: {'ancestor_count': 33, 'ancestor_ids': ['1_1', '34_69'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_64', 'origin': '1_1~CUW~34_69#MGNP'} Metrics: ['ELUC: -5.761954848698395', 'NSGA-II_crowding_distance: 1.0258485435671487', 'NSGA-II_rank: 5', 'change: 0.14300832358134757', 'is_elite: False']\n", + "Id: 35_53 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_91', '33_58'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_53', 'origin': '34_91~CUW~33_58#MGNP'} Metrics: ['ELUC: -5.770925882451781', 'NSGA-II_crowding_distance: 0.3366364653714363', 'NSGA-II_rank: 3', 'change: 0.09833538943135195', 'is_elite: False']\n", + "Id: 35_61 Identity: {'ancestor_count': 30, 'ancestor_ids': ['33_58', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_61', 'origin': '33_58~CUW~34_91#MGNP'} Metrics: ['ELUC: -5.860850871290695', 'NSGA-II_crowding_distance: 0.3437830794850336', 'NSGA-II_rank: 2', 'change: 0.08005354167753369', 'is_elite: False']\n", + "Id: 35_16 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_16', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 1.1059978197797584', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 35_77 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_91', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_77', 'origin': '34_91~CUW~34_91#MGNP'} Metrics: ['ELUC: -6.392402147732518', 'NSGA-II_crowding_distance: 0.19141269568125235', 'NSGA-II_rank: 1', 'change: 0.07995899331779623', 'is_elite: False']\n", + "Id: 34_91 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_53', '33_82'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_91', 'origin': '33_53~CUW~33_82#MGNP'} Metrics: ['ELUC: -6.722828080723802', 'NSGA-II_crowding_distance: 0.1625246613184868', 'NSGA-II_rank: 1', 'change: 0.08409758154423877', 'is_elite: False']\n", + "Id: 35_86 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_91', '34_17'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_86', 'origin': '34_91~CUW~34_17#MGNP'} Metrics: ['ELUC: -6.788586042850141', 'NSGA-II_crowding_distance: 0.3874094384905796', 'NSGA-II_rank: 3', 'change: 0.12829648718685055', 'is_elite: False']\n", + "Id: 35_100 Identity: {'ancestor_count': 33, 'ancestor_ids': ['30_89', '34_30'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_100', 'origin': '30_89~CUW~34_30#MGNP'} Metrics: ['ELUC: -7.180551793128625', 'NSGA-II_crowding_distance: 0.2449484268014466', 'NSGA-II_rank: 2', 'change: 0.10711647348105062', 'is_elite: False']\n", + "Id: 35_68 Identity: {'ancestor_count': 33, 'ancestor_ids': ['2_49', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_68', 'origin': '2_49~CUW~34_50#MGNP'} Metrics: ['ELUC: -7.408373935007396', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2817588570800818', 'is_elite: False']\n", + "Id: 35_24 Identity: {'ancestor_count': 30, 'ancestor_ids': ['30_89', '34_39'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_24', 'origin': '30_89~CUW~34_39#MGNP'} Metrics: ['ELUC: -7.538529333769146', 'NSGA-II_crowding_distance: 0.10759590776304717', 'NSGA-II_rank: 2', 'change: 0.1093469633280179', 'is_elite: False']\n", + "Id: 35_84 Identity: {'ancestor_count': 33, 'ancestor_ids': ['30_89', '34_30'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_84', 'origin': '30_89~CUW~34_30#MGNP'} Metrics: ['ELUC: -7.614417238842586', 'NSGA-II_crowding_distance: 0.17788947829885626', 'NSGA-II_rank: 2', 'change: 0.1252410825439946', 'is_elite: False']\n", + "Id: 35_80 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_30', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_80', 'origin': '34_30~CUW~33_82#MGNP'} Metrics: ['ELUC: -7.7004180582542086', 'NSGA-II_crowding_distance: 0.2651683636743237', 'NSGA-II_rank: 4', 'change: 0.14274155965751276', 'is_elite: False']\n", + "Id: 35_59 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '34_44'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_59', 'origin': '34_50~CUW~34_44#MGNP'} Metrics: ['ELUC: -7.83552219588922', 'NSGA-II_crowding_distance: 0.13694402401062677', 'NSGA-II_rank: 1', 'change: 0.10396253835081082', 'is_elite: False']\n", + "Id: 35_91 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_17', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_91', 'origin': '34_17~CUW~30_89#MGNP'} Metrics: ['ELUC: -7.958818748152262', 'NSGA-II_crowding_distance: 0.06340410869276882', 'NSGA-II_rank: 1', 'change: 0.10398348390670689', 'is_elite: False']\n", + "Id: 35_22 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '34_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_22', 'origin': '34_62~CUW~34_49#MGNP'} Metrics: ['ELUC: -8.105212315913809', 'NSGA-II_crowding_distance: 0.40407589298561597', 'NSGA-II_rank: 7', 'change: 0.27088083492313175', 'is_elite: False']\n", + "Id: 35_38 Identity: {'ancestor_count': 30, 'ancestor_ids': ['2_49', '34_17'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_38', 'origin': '2_49~CUW~34_17#MGNP'} Metrics: ['ELUC: -8.281902091601845', 'NSGA-II_crowding_distance: 0.3287880020258511', 'NSGA-II_rank: 7', 'change: 0.29113940674637295', 'is_elite: False']\n", + "Id: 35_78 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_30', '34_17'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_78', 'origin': '34_30~CUW~34_17#MGNP'} Metrics: ['ELUC: -8.316552149342206', 'NSGA-II_crowding_distance: 0.29657770446883874', 'NSGA-II_rank: 4', 'change: 0.14340926389607625', 'is_elite: False']\n", + "Id: 35_79 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_69', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_79', 'origin': '34_69~CUW~30_89#MGNP'} Metrics: ['ELUC: -8.443189971123044', 'NSGA-II_crowding_distance: 0.4879788665421144', 'NSGA-II_rank: 3', 'change: 0.13592882338952414', 'is_elite: False']\n", + "Id: 30_89 Identity: {'ancestor_count': 25, 'ancestor_ids': ['29_14', '29_14'], 'birth_generation': 30, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '30_89', 'origin': '29_14~CUW~29_14#MGNP'} Metrics: ['ELUC: -8.511797071769356', 'NSGA-II_crowding_distance: 0.10917342604287039', 'NSGA-II_rank: 1', 'change: 0.11140431833454958', 'is_elite: False']\n", + "Id: 35_34 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_34', 'origin': '34_44~CUW~34_50#MGNP'} Metrics: ['ELUC: -8.76817232131272', 'NSGA-II_crowding_distance: 0.38767777308120455', 'NSGA-II_rank: 2', 'change: 0.13042549845744192', 'is_elite: False']\n", + "Id: 35_43 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_43', 'origin': '30_89~CUW~30_89#MGNP'} Metrics: ['ELUC: -9.070637173838016', 'NSGA-II_crowding_distance: 0.24163421273285107', 'NSGA-II_rank: 1', 'change: 0.1176904999290556', 'is_elite: True']\n", + "Id: 35_32 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_12', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_32', 'origin': '34_12~CUW~30_89#MGNP'} Metrics: ['ELUC: -9.28212869975734', 'NSGA-II_crowding_distance: 1.2337356581462537', 'NSGA-II_rank: 6', 'change: 0.26166220908610693', 'is_elite: False']\n", + "Id: 35_99 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_58', '2_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_99', 'origin': '33_58~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.630428901197451', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2989198240122743', 'is_elite: False']\n", + "Id: 35_42 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_91', '34_62'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_42', 'origin': '34_91~CUW~34_62#MGNP'} Metrics: ['ELUC: -9.632829947270967', 'NSGA-II_crowding_distance: 0.9491240953823562', 'NSGA-II_rank: 5', 'change: 0.20876463282045524', 'is_elite: False']\n", + "Id: 35_83 Identity: {'ancestor_count': 33, 'ancestor_ids': ['2_49', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_83', 'origin': '2_49~CUW~34_50#MGNP'} Metrics: ['ELUC: -9.67455625899759', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2788560441844823', 'is_elite: False']\n", + "Id: 35_71 Identity: {'ancestor_count': 33, 'ancestor_ids': ['33_82', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_71', 'origin': '33_82~CUW~34_50#MGNP'} Metrics: ['ELUC: -9.823379215473597', 'NSGA-II_crowding_distance: 0.6296415090538715', 'NSGA-II_rank: 4', 'change: 0.1776193016240256', 'is_elite: False']\n", + "Id: 35_54 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_48', '34_17'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_54', 'origin': '33_48~CUW~34_17#MGNP'} Metrics: ['ELUC: -10.465622073935767', 'NSGA-II_crowding_distance: 0.871381576924761', 'NSGA-II_rank: 3', 'change: 0.17113459028851497', 'is_elite: False']\n", + "Id: 35_35 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_35', 'origin': '34_44~CUW~34_50#MGNP'} Metrics: ['ELUC: -10.506297791142526', 'NSGA-II_crowding_distance: 0.3148112410206001', 'NSGA-II_rank: 1', 'change: 0.14965529059530483', 'is_elite: True']\n", + "Id: 35_11 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_69', '34_81'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_11', 'origin': '34_69~CUW~34_81#MGNP'} Metrics: ['ELUC: -10.862286419977435', 'NSGA-II_crowding_distance: 0.5603683338930612', 'NSGA-II_rank: 2', 'change: 0.16132364909331204', 'is_elite: False']\n", + "Id: 35_30 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '34_30'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_30', 'origin': '34_62~CUW~34_30#MGNP'} Metrics: ['ELUC: -10.90665869917899', 'NSGA-II_crowding_distance: 0.6440448814250483', 'NSGA-II_rank: 5', 'change: 0.2652745616184695', 'is_elite: False']\n", + "Id: 35_36 Identity: {'ancestor_count': 33, 'ancestor_ids': ['30_89', '34_62'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_36', 'origin': '30_89~CUW~34_62#MGNP'} Metrics: ['ELUC: -11.0093441151323', 'NSGA-II_crowding_distance: 0.5642433861090369', 'NSGA-II_rank: 4', 'change: 0.24280967390888172', 'is_elite: False']\n", + "Id: 35_57 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '2_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_57', 'origin': '34_50~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.934225469290109', 'NSGA-II_crowding_distance: 0.2809264639628143', 'NSGA-II_rank: 4', 'change: 0.2709193377477817', 'is_elite: False']\n", + "Id: 35_26 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_30', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_26', 'origin': '34_30~CUW~34_50#MGNP'} Metrics: ['ELUC: -12.38145269568598', 'NSGA-II_crowding_distance: 0.23440217710877448', 'NSGA-II_rank: 1', 'change: 0.1554375987910164', 'is_elite: True']\n", + "Id: 35_60 Identity: {'ancestor_count': 33, 'ancestor_ids': ['1_1', '34_62'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_60', 'origin': '1_1~CUW~34_62#MGNP'} Metrics: ['ELUC: -12.895026169954663', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.29549583055304424', 'is_elite: False']\n", + "Id: 35_66 Identity: {'ancestor_count': 32, 'ancestor_ids': ['30_89', '33_44'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_66', 'origin': '30_89~CUW~33_44#MGNP'} Metrics: ['ELUC: -12.974156764141792', 'NSGA-II_crowding_distance: 0.42724098725798965', 'NSGA-II_rank: 2', 'change: 0.19105722923943236', 'is_elite: False']\n", + "Id: 35_21 Identity: {'ancestor_count': 30, 'ancestor_ids': ['2_49', '34_18'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_21', 'origin': '2_49~CUW~34_18#MGNP'} Metrics: ['ELUC: -12.993862038509171', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.27621586805944376', 'is_elite: False']\n", + "Id: 35_15 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '34_69'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_15', 'origin': '34_50~CUW~34_69#MGNP'} Metrics: ['ELUC: -13.17907016487341', 'NSGA-II_crowding_distance: 0.26935917904453555', 'NSGA-II_rank: 1', 'change: 0.1742379056003252', 'is_elite: True']\n", + "Id: 35_41 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_99', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_41', 'origin': '34_99~CUW~34_91#MGNP'} Metrics: ['ELUC: -13.34853840928526', 'NSGA-II_crowding_distance: 0.6312853004922775', 'NSGA-II_rank: 3', 'change: 0.23652597394925642', 'is_elite: False']\n", + "Id: 35_29 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_29', 'origin': '34_50~CUW~30_89#MGNP'} Metrics: ['ELUC: -13.787857843319967', 'NSGA-II_crowding_distance: 0.3217052457832149', 'NSGA-II_rank: 2', 'change: 0.21242871899855634', 'is_elite: False']\n", + "Id: 35_18 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_48', '34_12'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_18', 'origin': '33_48~CUW~34_12#MGNP'} Metrics: ['ELUC: -14.279294487443172', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.24024156872045832', 'is_elite: False']\n", + "Id: 34_50 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_100'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_50', 'origin': '33_44~CUW~33_100#MGNP'} Metrics: ['ELUC: -14.366995534352572', 'NSGA-II_crowding_distance: 0.2484121097770277', 'NSGA-II_rank: 1', 'change: 0.20211310112703576', 'is_elite: True']\n", + "Id: 35_49 Identity: {'ancestor_count': 32, 'ancestor_ids': ['34_91', '33_48'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_49', 'origin': '34_91~CUW~33_48#MGNP'} Metrics: ['ELUC: -14.659504206815646', 'NSGA-II_crowding_distance: 0.20665202419791606', 'NSGA-II_rank: 2', 'change: 0.23851628015730159', 'is_elite: False']\n", + "Id: 34_12 Identity: {'ancestor_count': 29, 'ancestor_ids': ['33_95', '33_58'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_12', 'origin': '33_95~CUW~33_58#MGNP'} Metrics: ['ELUC: -14.866432903917573', 'NSGA-II_crowding_distance: 0.1852321527561659', 'NSGA-II_rank: 2', 'change: 0.24298467345426136', 'is_elite: False']\n", + "Id: 35_87 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_87', 'origin': '34_50~CUW~34_50#MGNP'} Metrics: ['ELUC: -14.874847208785543', 'NSGA-II_crowding_distance: 0.3409677969513347', 'NSGA-II_rank: 1', 'change: 0.2195806841189792', 'is_elite: True']\n", + "Id: 35_76 Identity: {'ancestor_count': 33, 'ancestor_ids': ['2_49', '34_44'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_76', 'origin': '2_49~CUW~34_44#MGNP'} Metrics: ['ELUC: -14.90276669644398', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.27845548422084', 'is_elite: False']\n", + "Id: 35_85 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '33_58'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_85', 'origin': '34_62~CUW~33_58#MGNP'} Metrics: ['ELUC: -16.155161736540855', 'NSGA-II_crowding_distance: 0.33256693299926565', 'NSGA-II_rank: 1', 'change: 0.2735045615496481', 'is_elite: True']\n", + "Id: 35_75 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '33_82'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_75', 'origin': '34_62~CUW~33_82#MGNP'} Metrics: ['ELUC: -16.298943076645777', 'NSGA-II_crowding_distance: 0.15291207056439327', 'NSGA-II_rank: 1', 'change: 0.2946438997251316', 'is_elite: False']\n", + "Id: 35_51 Identity: {'ancestor_count': 23, 'ancestor_ids': ['33_82', '2_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_51', 'origin': '33_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.248312878077403', 'NSGA-II_crowding_distance: 0.10191332899361678', 'NSGA-II_rank: 1', 'change: 0.30057900391876097', 'is_elite: False']\n", + "Id: 35_48 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '34_62'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_48', 'origin': '34_62~CUW~34_62#MGNP'} Metrics: ['ELUC: -17.597295923117176', 'NSGA-II_crowding_distance: 0.02802789401466699', 'NSGA-II_rank: 1', 'change: 0.3030191179791577', 'is_elite: False']\n", + "Id: 35_20 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '34_91'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_20', 'origin': '34_62~CUW~34_91#MGNP'} Metrics: ['ELUC: -17.597310637033395', 'NSGA-II_crowding_distance: 9.675692886357984e-06', 'NSGA-II_rank: 1', 'change: 0.3030193033541715', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 34_62 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_100', '33_95'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_62', 'origin': '33_100~CUW~33_95#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 35_28 Identity: {'ancestor_count': 26, 'ancestor_ids': ['2_49', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_28', 'origin': '2_49~CUW~30_89#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 35_31 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_31', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 35_39 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_39', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 35_50 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '2_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_50', 'origin': '34_50~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 35.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 36...:\n", + "PopulationResponse:\n", + " Generation: 36\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/36/20240219-235953\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 36 and asking ESP for generation 37...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 36 data persisted.\n", + "Evaluated candidates:\n", + "Id: 36_86 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_44', '35_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_86', 'origin': '34_44~CUW~35_50#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 36_94 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_50', '34_44'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_94', 'origin': '35_50~CUW~34_44#MGNP'} Metrics: ['ELUC: 15.067818247230854', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2763631810993574', 'is_elite: False']\n", + "Id: 36_89 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_59', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_89', 'origin': '35_59~CUW~2_49#MGNP'} Metrics: ['ELUC: 12.205015800556172', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2586862113154988', 'is_elite: False']\n", + "Id: 36_44 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_91', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_44', 'origin': '34_91~CUW~2_49#MGNP'} Metrics: ['ELUC: 7.8577694941467815', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.2687866645778979', 'is_elite: False']\n", + "Id: 36_80 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_80', 'origin': '2_49~CUW~35_50#MGNP'} Metrics: ['ELUC: 5.938058060070632', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23948588638275878', 'is_elite: False']\n", + "Id: 36_13 Identity: {'ancestor_count': 33, 'ancestor_ids': ['1_1', '34_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_13', 'origin': '1_1~CUW~34_50#MGNP'} Metrics: ['ELUC: 2.6892072688822535', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.06710594622475333', 'is_elite: False']\n", + "Id: 36_14 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_50', '35_87'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_14', 'origin': '35_50~CUW~35_87#MGNP'} Metrics: ['ELUC: 2.372207025454473', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.34492621118080974', 'is_elite: False']\n", + "Id: 36_98 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_15', '35_90'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_98', 'origin': '35_15~CUW~35_90#MGNP'} Metrics: ['ELUC: 0.963660874792449', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09300389153699559', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 36_68 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_87', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_68', 'origin': '35_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.21217653198281244', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07334471503466565', 'is_elite: False']\n", + "Id: 36_46 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_46', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.22561297220792242', 'NSGA-II_crowding_distance: 0.12231350808828362', 'NSGA-II_rank: 1', 'change: 0.02329684278063441', 'is_elite: False']\n", + "Id: 36_31 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_31', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7695029744203141', 'NSGA-II_crowding_distance: 0.06510278934489805', 'NSGA-II_rank: 1', 'change: 0.028335033348996206', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.17567728503203636', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 36_93 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_87', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_93', 'origin': '35_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.5929309108866576', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3006074711717094', 'is_elite: False']\n", + "Id: 36_99 Identity: {'ancestor_count': 34, 'ancestor_ids': ['1_1', '35_59'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_99', 'origin': '1_1~CUW~35_59#MGNP'} Metrics: ['ELUC: -2.3722695772721227', 'NSGA-II_crowding_distance: 0.2126834551833191', 'NSGA-II_rank: 1', 'change: 0.053553776952555227', 'is_elite: True']\n", + "Id: 36_66 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_87', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_66', 'origin': '35_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.5346930342490905', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07122064053755081', 'is_elite: False']\n", + "Id: 36_62 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '35_90'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_62', 'origin': '34_44~CUW~35_90#MGNP'} Metrics: ['ELUC: -2.7363643291921105', 'NSGA-II_crowding_distance: 0.07804555679568564', 'NSGA-II_rank: 1', 'change: 0.06357384324632075', 'is_elite: False']\n", + "Id: 36_58 Identity: {'ancestor_count': 33, 'ancestor_ids': ['35_90', '34_44'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_58', 'origin': '35_90~CUW~34_44#MGNP'} Metrics: ['ELUC: -2.9073126178478805', 'NSGA-II_crowding_distance: 0.11705109843426911', 'NSGA-II_rank: 1', 'change: 0.0677609865245748', 'is_elite: False']\n", + "Id: 36_64 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_15', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_64', 'origin': '35_15~CUW~35_85#MGNP'} Metrics: ['ELUC: -3.9633583996414683', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.211092986339127', 'is_elite: False']\n", + "Id: 36_49 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_44', '35_15'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_49', 'origin': '34_44~CUW~35_15#MGNP'} Metrics: ['ELUC: -3.996263886755282', 'NSGA-II_crowding_distance: 0.28864679340971733', 'NSGA-II_rank: 3', 'change: 0.07670987794885674', 'is_elite: False']\n", + "Id: 36_11 Identity: {'ancestor_count': 34, 'ancestor_ids': ['1_1', '35_26'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_11', 'origin': '1_1~CUW~35_26#MGNP'} Metrics: ['ELUC: -4.049346338757302', 'NSGA-II_crowding_distance: 0.596982092874502', 'NSGA-II_rank: 3', 'change: 0.10935350198530164', 'is_elite: False']\n", + "Id: 36_51 Identity: {'ancestor_count': 30, 'ancestor_ids': ['1_1', '34_91'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_51', 'origin': '1_1~CUW~34_91#MGNP'} Metrics: ['ELUC: -4.450932156729579', 'NSGA-II_crowding_distance: 0.11862856476473735', 'NSGA-II_rank: 1', 'change: 0.06940253805398836', 'is_elite: False']\n", + "Id: 36_67 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_85', '35_90'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_67', 'origin': '35_85~CUW~35_90#MGNP'} Metrics: ['ELUC: -4.546062525290723', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.16133045894070921', 'is_elite: False']\n", + "Id: 36_22 Identity: {'ancestor_count': 27, 'ancestor_ids': ['35_43', '35_69'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_22', 'origin': '35_43~CUW~35_69#MGNP'} Metrics: ['ELUC: -4.572767132180196', 'NSGA-II_crowding_distance: 0.744320870263028', 'NSGA-II_rank: 2', 'change: 0.0707655175436697', 'is_elite: False']\n", + "Id: 36_34 Identity: {'ancestor_count': 26, 'ancestor_ids': ['35_90', '30_89'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_34', 'origin': '35_90~CUW~30_89#MGNP'} Metrics: ['ELUC: -4.879894610222508', 'NSGA-II_crowding_distance: 0.04586387621753175', 'NSGA-II_rank: 1', 'change: 0.06968178224147335', 'is_elite: False']\n", + "Id: 36_91 Identity: {'ancestor_count': 30, 'ancestor_ids': ['35_43', '34_91'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_91', 'origin': '35_43~CUW~34_91#MGNP'} Metrics: ['ELUC: -4.954977346855037', 'NSGA-II_crowding_distance: 0.26462266188341643', 'NSGA-II_rank: 1', 'change: 0.07453349440510564', 'is_elite: True']\n", + "Id: 36_96 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_75', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_96', 'origin': '35_75~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.3017459633806805', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.25810288865388265', 'is_elite: False']\n", + "Id: 36_26 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_15', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_26', 'origin': '35_15~CUW~35_85#MGNP'} Metrics: ['ELUC: -6.4915333662165455', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.17881170830052612', 'is_elite: False']\n", + "Id: 36_87 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_15', '34_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_87', 'origin': '35_15~CUW~34_49#MGNP'} Metrics: ['ELUC: -6.725126466680632', 'NSGA-II_crowding_distance: 0.3787180330789284', 'NSGA-II_rank: 1', 'change: 0.11732513402028041', 'is_elite: True']\n", + "Id: 36_27 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_27', 'origin': '35_35~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.811563677129052', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23829328992959595', 'is_elite: False']\n", + "Id: 36_40 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_87', '35_43'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_40', 'origin': '35_87~CUW~35_43#MGNP'} Metrics: ['ELUC: -7.145587971293236', 'NSGA-II_crowding_distance: 0.3929831156828226', 'NSGA-II_rank: 2', 'change: 0.12825572405422092', 'is_elite: False']\n", + "Id: 36_56 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_85', '34_44'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_56', 'origin': '35_85~CUW~34_44#MGNP'} Metrics: ['ELUC: -7.193016500249428', 'NSGA-II_crowding_distance: 1.464123128202136', 'NSGA-II_rank: 6', 'change: 0.16565305507135344', 'is_elite: False']\n", + "Id: 36_65 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_90', '35_26'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_65', 'origin': '35_90~CUW~35_26#MGNP'} Metrics: ['ELUC: -7.371251165643264', 'NSGA-II_crowding_distance: 0.08443047225509578', 'NSGA-II_rank: 2', 'change: 0.13090830165594047', 'is_elite: False']\n", + "Id: 36_57 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_50', '35_35'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_57', 'origin': '35_50~CUW~35_35#MGNP'} Metrics: ['ELUC: -7.551059552401706', 'NSGA-II_crowding_distance: 1.3214860793103196', 'NSGA-II_rank: 8', 'change: 0.23489016247925568', 'is_elite: False']\n", + "Id: 36_28 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_87', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_28', 'origin': '35_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.098534194799154', 'NSGA-II_crowding_distance: 1.492844065039987', 'NSGA-II_rank: 5', 'change: 0.15871419757769384', 'is_elite: False']\n", + "Id: 36_76 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_49', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_76', 'origin': '34_49~CUW~35_85#MGNP'} Metrics: ['ELUC: -8.196822633213479', 'NSGA-II_crowding_distance: 0.5219109205671978', 'NSGA-II_rank: 5', 'change: 0.19940427294858246', 'is_elite: False']\n", + "Id: 36_30 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_43', '35_15'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_30', 'origin': '35_43~CUW~35_15#MGNP'} Metrics: ['ELUC: -8.359146942878521', 'NSGA-II_crowding_distance: 1.3220884419631251', 'NSGA-II_rank: 4', 'change: 0.13999178132346876', 'is_elite: False']\n", + "Id: 36_78 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_77', '35_26'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_78', 'origin': '35_77~CUW~35_26#MGNP'} Metrics: ['ELUC: -8.394457490379043', 'NSGA-II_crowding_distance: 0.9964684732609304', 'NSGA-II_rank: 3', 'change: 0.1344633692822161', 'is_elite: False']\n", + "Id: 36_39 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_39', 'origin': '35_35~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.437485187242336', 'NSGA-II_crowding_distance: 0.16318061959539132', 'NSGA-II_rank: 2', 'change: 0.13314059536598022', 'is_elite: False']\n", + "Id: 36_48 Identity: {'ancestor_count': 34, 'ancestor_ids': ['1_1', '35_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_48', 'origin': '1_1~CUW~35_50#MGNP'} Metrics: ['ELUC: -8.751256826620635', 'NSGA-II_crowding_distance: 0.8909292230912254', 'NSGA-II_rank: 8', 'change: 0.2565358127615303', 'is_elite: False']\n", + "Id: 36_23 Identity: {'ancestor_count': 33, 'ancestor_ids': ['2_49', '34_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_23', 'origin': '2_49~CUW~34_50#MGNP'} Metrics: ['ELUC: -9.007995023890246', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.3038395388768275', 'is_elite: False']\n", + "Id: 36_54 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_85', '35_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_54', 'origin': '35_85~CUW~35_50#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 35_43 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_43', 'origin': '30_89~CUW~30_89#MGNP'} Metrics: ['ELUC: -9.070637173838016', 'NSGA-II_crowding_distance: 0.2186662898330391', 'NSGA-II_rank: 1', 'change: 0.1176904999290556', 'is_elite: True']\n", + "Id: 36_36 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_90', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_36', 'origin': '35_90~CUW~35_85#MGNP'} Metrics: ['ELUC: -9.08330202002738', 'NSGA-II_crowding_distance: 1.6113918362887478', 'NSGA-II_rank: 7', 'change: 0.21637210090364042', 'is_elite: False']\n", + "Id: 36_19 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_91', '35_35'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_19', 'origin': '34_91~CUW~35_35#MGNP'} Metrics: ['ELUC: -9.150751032224793', 'NSGA-II_crowding_distance: 0.22253030491604492', 'NSGA-II_rank: 2', 'change: 0.14869683685461235', 'is_elite: False']\n", + "Id: 36_16 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_35'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_16', 'origin': '2_49~CUW~35_35#MGNP'} Metrics: ['ELUC: -9.35778336882877', 'NSGA-II_crowding_distance: 1.0128866656873832', 'NSGA-II_rank: 7', 'change: 0.2709719892287651', 'is_elite: False']\n", + "Id: 36_35 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_91', '35_87'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_35', 'origin': '34_91~CUW~35_87#MGNP'} Metrics: ['ELUC: -9.766634644190324', 'NSGA-II_crowding_distance: 0.09949927366278331', 'NSGA-II_rank: 1', 'change: 0.13095495072369698', 'is_elite: False']\n", + "Id: 36_79 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '35_69'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_79', 'origin': '2_49~CUW~35_69#MGNP'} Metrics: ['ELUC: -9.911207783061544', 'NSGA-II_crowding_distance: 0.6785139206896803', 'NSGA-II_rank: 8', 'change: 0.2767100605645515', 'is_elite: False']\n", + "Id: 36_12 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_44', '35_35'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_12', 'origin': '34_44~CUW~35_35#MGNP'} Metrics: ['ELUC: -9.920021689828253', 'NSGA-II_crowding_distance: 0.1047419090312304', 'NSGA-II_rank: 1', 'change: 0.13296454879696365', 'is_elite: False']\n", + "Id: 36_71 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_35'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_71', 'origin': '2_49~CUW~35_35#MGNP'} Metrics: ['ELUC: -10.254952014100288', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2921704162910906', 'is_elite: False']\n", + "Id: 36_60 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_43', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_60', 'origin': '35_43~CUW~35_85#MGNP'} Metrics: ['ELUC: -10.30415069220873', 'NSGA-II_crowding_distance: 0.3915975849198753', 'NSGA-II_rank: 5', 'change: 0.2059872171747786', 'is_elite: False']\n", + "Id: 36_82 Identity: {'ancestor_count': 34, 'ancestor_ids': ['1_1', '35_75'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_82', 'origin': '1_1~CUW~35_75#MGNP'} Metrics: ['ELUC: -10.352298765406042', 'NSGA-II_crowding_distance: 1.5594806269114931', 'NSGA-II_rank: 6', 'change: 0.21599895999518495', 'is_elite: False']\n", + "Id: 35_35 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_44', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_35', 'origin': '34_44~CUW~34_50#MGNP'} Metrics: ['ELUC: -10.506297791142526', 'NSGA-II_crowding_distance: 0.16627185560172675', 'NSGA-II_rank: 1', 'change: 0.14965529059530483', 'is_elite: False']\n", + "Id: 36_45 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_75', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_45', 'origin': '35_75~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.800521878929239', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2762108425312625', 'is_elite: False']\n", + "Id: 36_15 Identity: {'ancestor_count': 30, 'ancestor_ids': ['34_91', '35_43'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_15', 'origin': '34_91~CUW~35_43#MGNP'} Metrics: ['ELUC: -11.155708855696446', 'NSGA-II_crowding_distance: 0.19676560124661063', 'NSGA-II_rank: 2', 'change: 0.15400689801652992', 'is_elite: False']\n", + "Id: 36_32 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_75', '35_77'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_32', 'origin': '35_75~CUW~35_77#MGNP'} Metrics: ['ELUC: -11.283072356678195', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.25209949422700584', 'is_elite: False']\n", + "Id: 36_17 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_77', '35_87'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_17', 'origin': '35_77~CUW~35_87#MGNP'} Metrics: ['ELUC: -11.469557448834156', 'NSGA-II_crowding_distance: 0.13986217075386886', 'NSGA-II_rank: 2', 'change: 0.16813279233197678', 'is_elite: False']\n", + "Id: 36_42 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_50', '35_15'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_42', 'origin': '34_50~CUW~35_15#MGNP'} Metrics: ['ELUC: -11.697509125649884', 'NSGA-II_crowding_distance: 0.1260290664378084', 'NSGA-II_rank: 1', 'change: 0.152411855485573', 'is_elite: False']\n", + "Id: 36_88 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_85', '35_35'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_88', 'origin': '35_85~CUW~35_35#MGNP'} Metrics: ['ELUC: -11.817305971900785', 'NSGA-II_crowding_distance: 0.2979906519389759', 'NSGA-II_rank: 5', 'change: 0.2150113789142722', 'is_elite: False']\n", + "Id: 36_100 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_77', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_100', 'origin': '35_77~CUW~35_85#MGNP'} Metrics: ['ELUC: -12.225760486421086', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.22628568703663082', 'is_elite: False']\n", + "Id: 35_26 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_30', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_26', 'origin': '34_30~CUW~34_50#MGNP'} Metrics: ['ELUC: -12.38145269568598', 'NSGA-II_crowding_distance: 0.14414811256031776', 'NSGA-II_rank: 1', 'change: 0.1554375987910164', 'is_elite: False']\n", + "Id: 36_90 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_77', '35_15'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_90', 'origin': '35_77~CUW~35_15#MGNP'} Metrics: ['ELUC: -12.608774276901901', 'NSGA-II_crowding_distance: 0.11020217138517878', 'NSGA-II_rank: 2', 'change: 0.17009293526664918', 'is_elite: False']\n", + "Id: 36_38 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_15', '35_26'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_38', 'origin': '35_15~CUW~35_26#MGNP'} Metrics: ['ELUC: -13.059867507572035', 'NSGA-II_crowding_distance: 0.9435717761515041', 'NSGA-II_rank: 4', 'change: 0.17640228123819593', 'is_elite: False']\n", + "Id: 36_70 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_26', '35_87'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_70', 'origin': '35_26~CUW~35_87#MGNP'} Metrics: ['ELUC: -13.162477206855655', 'NSGA-II_crowding_distance: 1.009575021726186', 'NSGA-II_rank: 3', 'change: 0.17619624980754697', 'is_elite: False']\n", + "Id: 35_15 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '34_69'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_15', 'origin': '34_50~CUW~34_69#MGNP'} Metrics: ['ELUC: -13.17907016487341', 'NSGA-II_crowding_distance: 0.24908587082033645', 'NSGA-II_rank: 2', 'change: 0.1742379056003252', 'is_elite: False']\n", + "Id: 36_59 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_50', '35_15'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_59', 'origin': '34_50~CUW~35_15#MGNP'} Metrics: ['ELUC: -13.201366608330877', 'NSGA-II_crowding_distance: 0.23491444771943176', 'NSGA-II_rank: 1', 'change: 0.16990151492086397', 'is_elite: True']\n", + "Id: 36_73 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_73', 'origin': '30_89~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.272268930036867', 'NSGA-II_crowding_distance: 0.677911558036875', 'NSGA-II_rank: 4', 'change: 0.275227801569291', 'is_elite: False']\n", + "Id: 36_74 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_50', '35_35'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_74', 'origin': '35_50~CUW~35_35#MGNP'} Metrics: ['ELUC: -13.71346841020956', 'NSGA-II_crowding_distance: 0.7148847333293523', 'NSGA-II_rank: 3', 'change: 0.2674814074698995', 'is_elite: False']\n", + "Id: 36_61 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_90', '35_87'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_61', 'origin': '35_90~CUW~35_87#MGNP'} Metrics: ['ELUC: -13.910357499176286', 'NSGA-II_crowding_distance: 0.5675907019369744', 'NSGA-II_rank: 2', 'change: 0.21370786468408726', 'is_elite: False']\n", + "Id: 36_75 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_87', '34_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_75', 'origin': '35_87~CUW~34_50#MGNP'} Metrics: ['ELUC: -14.05675425959281', 'NSGA-II_crowding_distance: 0.17425117824030784', 'NSGA-II_rank: 1', 'change: 0.19710045096112314', 'is_elite: False']\n", + "Id: 34_50 Identity: {'ancestor_count': 32, 'ancestor_ids': ['33_44', '33_100'], 'birth_generation': 34, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '34_50', 'origin': '33_44~CUW~33_100#MGNP'} Metrics: ['ELUC: -14.366995534352572', 'NSGA-II_crowding_distance: 0.05114938068487239', 'NSGA-II_rank: 1', 'change: 0.20211310112703576', 'is_elite: False']\n", + "Id: 36_85 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '35_87'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_85', 'origin': '35_35~CUW~35_87#MGNP'} Metrics: ['ELUC: -14.418859478748939', 'NSGA-II_crowding_distance: 0.03177719518573866', 'NSGA-II_rank: 1', 'change: 0.20621724910319625', 'is_elite: False']\n", + "Id: 36_69 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_15', '34_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_69', 'origin': '35_15~CUW~34_50#MGNP'} Metrics: ['ELUC: -14.527435731858354', 'NSGA-II_crowding_distance: 0.04435376433044333', 'NSGA-II_rank: 1', 'change: 0.20887198840155213', 'is_elite: False']\n", + "Id: 36_24 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_87', '35_43'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_24', 'origin': '35_87~CUW~35_43#MGNP'} Metrics: ['ELUC: -14.660183687274833', 'NSGA-II_crowding_distance: 0.05564884621771958', 'NSGA-II_rank: 1', 'change: 0.21535607774089865', 'is_elite: False']\n", + "Id: 35_87 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '34_50'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_87', 'origin': '34_50~CUW~34_50#MGNP'} Metrics: ['ELUC: -14.874847208785543', 'NSGA-II_crowding_distance: 0.057893497731573554', 'NSGA-II_rank: 1', 'change: 0.2195806841189792', 'is_elite: False']\n", + "Id: 36_20 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_50', '35_87'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_20', 'origin': '34_50~CUW~35_87#MGNP'} Metrics: ['ELUC: -15.082199567754461', 'NSGA-II_crowding_distance: 0.1241538976117931', 'NSGA-II_rank: 1', 'change: 0.22546846772763016', 'is_elite: False']\n", + "Id: 36_43 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_50', '35_26'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_43', 'origin': '35_50~CUW~35_26#MGNP'} Metrics: ['ELUC: -15.30855304028762', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2921302619590261', 'is_elite: False']\n", + "Id: 36_83 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_83', 'origin': '35_35~CUW~35_85#MGNP'} Metrics: ['ELUC: -15.495546120122349', 'NSGA-II_crowding_distance: 0.188886810475129', 'NSGA-II_rank: 1', 'change: 0.24609198851403055', 'is_elite: True']\n", + "Id: 36_47 Identity: {'ancestor_count': 34, 'ancestor_ids': ['1_1', '35_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_47', 'origin': '1_1~CUW~35_50#MGNP'} Metrics: ['ELUC: -15.701014896582729', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29087135034401673', 'is_elite: False']\n", + "Id: 36_37 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_85', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_37', 'origin': '35_85~CUW~35_85#MGNP'} Metrics: ['ELUC: -15.847970213390889', 'NSGA-II_crowding_distance: 0.1366060755740121', 'NSGA-II_rank: 1', 'change: 0.2688327186700286', 'is_elite: False']\n", + "Id: 35_85 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_62', '33_58'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_85', 'origin': '34_62~CUW~33_58#MGNP'} Metrics: ['ELUC: -16.155161736540855', 'NSGA-II_crowding_distance: 0.5063768948890967', 'NSGA-II_rank: 2', 'change: 0.2735045615496481', 'is_elite: False']\n", + "Id: 36_84 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_26'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_84', 'origin': '2_49~CUW~35_26#MGNP'} Metrics: ['ELUC: -16.415849964101263', 'NSGA-II_crowding_distance: 0.09076641089893862', 'NSGA-II_rank: 1', 'change: 0.2712343572728707', 'is_elite: False']\n", + "Id: 36_92 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_92', 'origin': '2_49~CUW~35_50#MGNP'} Metrics: ['ELUC: -16.682037336651867', 'NSGA-II_crowding_distance: 0.17345752760499422', 'NSGA-II_rank: 2', 'change: 0.30091251900694993', 'is_elite: False']\n", + "Id: 36_33 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_87', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_33', 'origin': '35_87~CUW~35_85#MGNP'} Metrics: ['ELUC: -16.772954022549555', 'NSGA-II_crowding_distance: 0.13304400513355696', 'NSGA-II_rank: 1', 'change: 0.2802181326041905', 'is_elite: False']\n", + "Id: 36_95 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_75', '35_26'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_95', 'origin': '35_75~CUW~35_26#MGNP'} Metrics: ['ELUC: -17.13392289531217', 'NSGA-II_crowding_distance: 0.11421419961909221', 'NSGA-II_rank: 1', 'change: 0.2987458045059894', 'is_elite: False']\n", + "Id: 36_52 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_52', 'origin': '2_49~CUW~35_85#MGNP'} Metrics: ['ELUC: -17.14334560261308', 'NSGA-II_crowding_distance: 0.05339341610252951', 'NSGA-II_rank: 2', 'change: 0.30292523543743455', 'is_elite: False']\n", + "Id: 36_77 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_77', 'origin': '2_49~CUW~35_50#MGNP'} Metrics: ['ELUC: -17.52427182031449', 'NSGA-II_crowding_distance: 0.040547993128807', 'NSGA-II_rank: 1', 'change: 0.30154700987539873', 'is_elite: False']\n", + "Id: 36_25 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_85', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_25', 'origin': '35_85~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.584310376304593', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30300932480331433', 'is_elite: False']\n", + "Id: 36_63 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_63', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59580511215276', 'NSGA-II_crowding_distance: 0.00903506647968311', 'NSGA-II_rank: 1', 'change: 0.30300613846113666', 'is_elite: False']\n", + "Id: 36_41 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_43', '35_75'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_41', 'origin': '35_43~CUW~35_75#MGNP'} Metrics: ['ELUC: -17.59698426299667', 'NSGA-II_crowding_distance: 9.039877988458622e-05', 'NSGA-II_rank: 1', 'change: 0.30300891980085976', 'is_elite: False']\n", + "Id: 36_97 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '35_50'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_97', 'origin': '35_35~CUW~35_50#MGNP'} Metrics: ['ELUC: -17.597076166481926', 'NSGA-II_crowding_distance: 6.158019459860182e-05', 'NSGA-II_rank: 1', 'change: 0.3030115412587967', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 35_50 Identity: {'ancestor_count': 33, 'ancestor_ids': ['34_50', '2_49'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_50', 'origin': '34_50~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 36_18 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_18', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 36_21 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_21', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 36_29 Identity: {'ancestor_count': 27, 'ancestor_ids': ['2_49', '35_43'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_29', 'origin': '2_49~CUW~35_43#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 36_50 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_15'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_50', 'origin': '2_49~CUW~35_15#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 36_53 Identity: {'ancestor_count': 27, 'ancestor_ids': ['35_43', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_53', 'origin': '35_43~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 36_55 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_55', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 36_81 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_81', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 36.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 37...:\n", + "PopulationResponse:\n", + " Generation: 37\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/37/20240220-000707\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 37 and asking ESP for generation 38...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 37 data persisted.\n", + "Evaluated candidates:\n", + "Id: 37_42 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_81', '36_83'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_42', 'origin': '36_81~CUW~36_83#MGNP'} Metrics: ['ELUC: 18.385676120386663', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2635499157190645', 'is_elite: False']\n", + "Id: 37_67 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_67', 'origin': '35_35~CUW~36_81#MGNP'} Metrics: ['ELUC: 17.3033151278557', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2545120594325746', 'is_elite: False']\n", + "Id: 37_27 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_81', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_27', 'origin': '36_81~CUW~36_87#MGNP'} Metrics: ['ELUC: 16.985143751966053', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.2910173881169901', 'is_elite: False']\n", + "Id: 37_90 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_90', 'origin': '36_59~CUW~36_81#MGNP'} Metrics: ['ELUC: 15.89160178367303', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.2818674394486447', 'is_elite: False']\n", + "Id: 37_71 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '2_49'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_71', 'origin': '36_59~CUW~2_49#MGNP'} Metrics: ['ELUC: 10.654325794101064', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2777488703954066', 'is_elite: False']\n", + "Id: 37_64 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_75', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_64', 'origin': '36_75~CUW~36_81#MGNP'} Metrics: ['ELUC: 6.509342367058872', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.23608641756425622', 'is_elite: False']\n", + "Id: 37_15 Identity: {'ancestor_count': 35, 'ancestor_ids': ['2_49', '36_83'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_15', 'origin': '2_49~CUW~36_83#MGNP'} Metrics: ['ELUC: 3.8350652784164643', 'NSGA-II_crowding_distance: 1.2019715965135271', 'NSGA-II_rank: 12', 'change: 0.2562989028617126', 'is_elite: False']\n", + "Id: 37_55 Identity: {'ancestor_count': 34, 'ancestor_ids': ['36_81', '35_26'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_55', 'origin': '36_81~CUW~35_26#MGNP'} Metrics: ['ELUC: 3.006320315986242', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2309820743947552', 'is_elite: False']\n", + "Id: 37_38 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '36_72'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_38', 'origin': '36_59~CUW~36_72#MGNP'} Metrics: ['ELUC: 1.8171684086329543', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.09967693214334866', 'is_elite: False']\n", + "Id: 37_100 Identity: {'ancestor_count': 35, 'ancestor_ids': ['1_1', '36_42'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_100', 'origin': '1_1~CUW~36_42#MGNP'} Metrics: ['ELUC: 1.5064627042319363', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.08732785962281124', 'is_elite: False']\n", + "Id: 37_75 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_75', 'origin': '36_87~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.479058321002175', 'NSGA-II_crowding_distance: 1.2115820537416757', 'NSGA-II_rank: 7', 'change: 0.10405297247663488', 'is_elite: False']\n", + "Id: 37_54 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '36_72'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_54', 'origin': '36_87~CUW~36_72#MGNP'} Metrics: ['ELUC: 1.3211770687789748', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08223692316427578', 'is_elite: False']\n", + "Id: 37_60 Identity: {'ancestor_count': 34, 'ancestor_ids': ['2_49', '35_26'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_60', 'origin': '2_49~CUW~35_26#MGNP'} Metrics: ['ELUC: 0.38961948577785677', 'NSGA-II_crowding_distance: 1.2076656178305547', 'NSGA-II_rank: 12', 'change: 0.2702167167582419', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 37_58 Identity: {'ancestor_count': 34, 'ancestor_ids': ['1_1', '35_35'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_58', 'origin': '1_1~CUW~35_35#MGNP'} Metrics: ['ELUC: -0.11490805252061266', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07365199760896018', 'is_elite: False']\n", + "Id: 37_51 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '36_46'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_51', 'origin': '35_35~CUW~36_46#MGNP'} Metrics: ['ELUC: -0.21153815163405287', 'NSGA-II_crowding_distance: 0.8592605320961769', 'NSGA-II_rank: 5', 'change: 0.0799050101606391', 'is_elite: False']\n", + "Id: 37_72 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_81', '36_59'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_72', 'origin': '36_81~CUW~36_59#MGNP'} Metrics: ['ELUC: -0.30537560230465005', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.31955773172571944', 'is_elite: False']\n", + "Id: 37_19 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '36_72'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_19', 'origin': '36_87~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.31165709020281035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06805834056507166', 'is_elite: False']\n", + "Id: 37_65 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '36_72'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_65', 'origin': '1_1~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.44875513729210137', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03752533703784865', 'is_elite: False']\n", + "Id: 37_18 Identity: {'ancestor_count': 34, 'ancestor_ids': ['36_81', '35_26'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_18', 'origin': '36_81~CUW~35_26#MGNP'} Metrics: ['ELUC: -0.5623612753581844', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2387218908890423', 'is_elite: False']\n", + "Id: 37_74 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_74', 'origin': '36_59~CUW~36_81#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 37_84 Identity: {'ancestor_count': 27, 'ancestor_ids': ['35_43', '36_72'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_84', 'origin': '35_43~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.6658976593195695', 'NSGA-II_crowding_distance: 0.46629802771157014', 'NSGA-II_rank: 4', 'change: 0.07526929305582451', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.28483698732160245', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 37_16 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_42', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_16', 'origin': '36_42~CUW~36_81#MGNP'} Metrics: ['ELUC: -1.4053271483788183', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2541653026983321', 'is_elite: False']\n", + "Id: 37_35 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_72', '36_99'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_35', 'origin': '36_72~CUW~36_99#MGNP'} Metrics: ['ELUC: -1.9535435388677316', 'NSGA-II_crowding_distance: 0.17257178605570922', 'NSGA-II_rank: 2', 'change: 0.05291397503260634', 'is_elite: False']\n", + "Id: 37_89 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_37', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_89', 'origin': '36_37~CUW~36_87#MGNP'} Metrics: ['ELUC: -2.0033255258905553', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.19985823540535316', 'is_elite: False']\n", + "Id: 37_30 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_46', '36_51'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_30', 'origin': '36_46~CUW~36_51#MGNP'} Metrics: ['ELUC: -2.3544946259900708', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05795540806682162', 'is_elite: False']\n", + "Id: 36_99 Identity: {'ancestor_count': 34, 'ancestor_ids': ['1_1', '35_59'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_99', 'origin': '1_1~CUW~35_59#MGNP'} Metrics: ['ELUC: -2.3722695772721227', 'NSGA-II_crowding_distance: 0.12200686846499006', 'NSGA-II_rank: 2', 'change: 0.053553776952555227', 'is_elite: False']\n", + "Id: 37_85 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_85', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.3856499681365775', 'NSGA-II_crowding_distance: 0.18343232242113555', 'NSGA-II_rank: 1', 'change: 0.049401905086654534', 'is_elite: False']\n", + "Id: 37_91 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_91', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_91', 'origin': '36_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.4447779135690215', 'NSGA-II_crowding_distance: 0.0898986809643951', 'NSGA-II_rank: 3', 'change: 0.06884576002959755', 'is_elite: False']\n", + "Id: 37_97 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_81', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_97', 'origin': '36_81~CUW~36_91#MGNP'} Metrics: ['ELUC: -2.614415132323', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2605233396892827', 'is_elite: False']\n", + "Id: 37_49 Identity: {'ancestor_count': 35, 'ancestor_ids': ['1_1', '36_59'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_49', 'origin': '1_1~CUW~36_59#MGNP'} Metrics: ['ELUC: -2.682892562986258', 'NSGA-II_crowding_distance: 0.421175301996282', 'NSGA-II_rank: 3', 'change: 0.07450581075392872', 'is_elite: False']\n", + "Id: 37_34 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_99', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_34', 'origin': '36_99~CUW~36_91#MGNP'} Metrics: ['ELUC: -2.7630247456800685', 'NSGA-II_crowding_distance: 0.1535495967464987', 'NSGA-II_rank: 1', 'change: 0.054393521626242065', 'is_elite: False']\n", + "Id: 37_46 Identity: {'ancestor_count': 27, 'ancestor_ids': ['35_43', '36_72'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_46', 'origin': '35_43~CUW~36_72#MGNP'} Metrics: ['ELUC: -3.048654483641312', 'NSGA-II_crowding_distance: 0.2316364397410563', 'NSGA-II_rank: 2', 'change: 0.068348036194423', 'is_elite: False']\n", + "Id: 37_50 Identity: {'ancestor_count': 35, 'ancestor_ids': ['1_1', '36_75'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_50', 'origin': '1_1~CUW~36_75#MGNP'} Metrics: ['ELUC: -3.841130038946653', 'NSGA-II_crowding_distance: 0.7718470960383891', 'NSGA-II_rank: 4', 'change: 0.11529733536284995', 'is_elite: False']\n", + "Id: 37_33 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_99', '36_33'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_33', 'origin': '36_99~CUW~36_33#MGNP'} Metrics: ['ELUC: -3.9657243656448817', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.14800490000596436', 'is_elite: False']\n", + "Id: 37_23 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_42', '36_99'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_23', 'origin': '36_42~CUW~36_99#MGNP'} Metrics: ['ELUC: -3.977134867787818', 'NSGA-II_crowding_distance: 0.19216610741398443', 'NSGA-II_rank: 1', 'change: 0.0682096936151932', 'is_elite: True']\n", + "Id: 37_80 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_91', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_80', 'origin': '36_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.882725915813406', 'NSGA-II_crowding_distance: 0.28231661538422775', 'NSGA-II_rank: 2', 'change: 0.07617425740976591', 'is_elite: False']\n", + "Id: 36_91 Identity: {'ancestor_count': 30, 'ancestor_ids': ['35_43', '34_91'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_91', 'origin': '35_43~CUW~34_91#MGNP'} Metrics: ['ELUC: -4.954977346855037', 'NSGA-II_crowding_distance: 0.29323737996460175', 'NSGA-II_rank: 1', 'change: 0.07453349440510564', 'is_elite: True']\n", + "Id: 37_99 Identity: {'ancestor_count': 35, 'ancestor_ids': ['1_1', '36_75'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_99', 'origin': '1_1~CUW~36_75#MGNP'} Metrics: ['ELUC: -5.437683693378037', 'NSGA-II_crowding_distance: 1.892886991612377', 'NSGA-II_rank: 7', 'change: 0.13499686511704825', 'is_elite: False']\n", + "Id: 37_56 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_75', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_56', 'origin': '36_75~CUW~36_87#MGNP'} Metrics: ['ELUC: -5.976992154929452', 'NSGA-II_crowding_distance: 0.9340493894043328', 'NSGA-II_rank: 6', 'change: 0.13000572779535854', 'is_elite: False']\n", + "Id: 37_70 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_42', '35_43'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_70', 'origin': '36_42~CUW~35_43#MGNP'} Metrics: ['ELUC: -6.02955264992263', 'NSGA-II_crowding_distance: 0.20004774414338314', 'NSGA-II_rank: 2', 'change: 0.0971388102303899', 'is_elite: False']\n", + "Id: 37_63 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_81', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_63', 'origin': '36_81~CUW~36_91#MGNP'} Metrics: ['ELUC: -6.0694860972623035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24892983383728273', 'is_elite: False']\n", + "Id: 37_93 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_91', '36_59'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_93', 'origin': '36_91~CUW~36_59#MGNP'} Metrics: ['ELUC: -6.189487717223152', 'NSGA-II_crowding_distance: 0.45492204353721444', 'NSGA-II_rank: 3', 'change: 0.10844854695428663', 'is_elite: False']\n", + "Id: 37_17 Identity: {'ancestor_count': 34, 'ancestor_ids': ['36_72', '35_35'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_17', 'origin': '36_72~CUW~35_35#MGNP'} Metrics: ['ELUC: -6.252711549694195', 'NSGA-II_crowding_distance: 0.11296415485443637', 'NSGA-II_rank: 6', 'change: 0.13210399396591369', 'is_elite: False']\n", + "Id: 37_94 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_99', '35_43'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_94', 'origin': '36_99~CUW~35_43#MGNP'} Metrics: ['ELUC: -6.392456004043104', 'NSGA-II_crowding_distance: 0.9064018348731958', 'NSGA-II_rank: 5', 'change: 0.12128981048343426', 'is_elite: False']\n", + "Id: 36_87 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_15', '34_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_87', 'origin': '35_15~CUW~34_49#MGNP'} Metrics: ['ELUC: -6.725126466680632', 'NSGA-II_crowding_distance: 0.23522352108368155', 'NSGA-II_rank: 3', 'change: 0.11732513402028041', 'is_elite: False']\n", + "Id: 37_43 Identity: {'ancestor_count': 27, 'ancestor_ids': ['35_43', '36_72'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_43', 'origin': '35_43~CUW~36_72#MGNP'} Metrics: ['ELUC: -6.733394368937196', 'NSGA-II_crowding_distance: 0.11502173068403547', 'NSGA-II_rank: 2', 'change: 0.10062739341666246', 'is_elite: False']\n", + "Id: 37_24 Identity: {'ancestor_count': 34, 'ancestor_ids': ['1_1', '35_35'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_24', 'origin': '1_1~CUW~35_35#MGNP'} Metrics: ['ELUC: -6.84299932136918', 'NSGA-II_crowding_distance: 1.0659506105956673', 'NSGA-II_rank: 6', 'change: 0.13702971410650533', 'is_elite: False']\n", + "Id: 37_95 Identity: {'ancestor_count': 27, 'ancestor_ids': ['36_72', '35_43'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_95', 'origin': '36_72~CUW~35_43#MGNP'} Metrics: ['ELUC: -7.108155477319092', 'NSGA-II_crowding_distance: 0.3160756008008522', 'NSGA-II_rank: 5', 'change: 0.1242621964274811', 'is_elite: False']\n", + "Id: 37_52 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_52', 'origin': '35_35~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.312582481278399', 'NSGA-II_crowding_distance: 0.20060380834947317', 'NSGA-II_rank: 2', 'change: 0.10780685836201248', 'is_elite: False']\n", + "Id: 37_44 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_44', 'origin': '36_87~CUW~36_91#MGNP'} Metrics: ['ELUC: -7.6324957427196285', 'NSGA-II_crowding_distance: 0.2798922639800615', 'NSGA-II_rank: 1', 'change: 0.09367259230543952', 'is_elite: True']\n", + "Id: 37_48 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_48', 'origin': '35_35~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.7969920322684', 'NSGA-II_crowding_distance: 1.0543618034327427', 'NSGA-II_rank: 5', 'change: 0.15822607043251127', 'is_elite: False']\n", + "Id: 37_76 Identity: {'ancestor_count': 27, 'ancestor_ids': ['35_43', '35_43'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_76', 'origin': '35_43~CUW~35_43#MGNP'} Metrics: ['ELUC: -7.967328318164707', 'NSGA-II_crowding_distance: 0.16120744583936703', 'NSGA-II_rank: 1', 'change: 0.10692658410928531', 'is_elite: False']\n", + "Id: 37_87 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_42', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_87', 'origin': '36_42~CUW~36_87#MGNP'} Metrics: ['ELUC: -8.844978693094346', 'NSGA-II_crowding_distance: 1.152152970846798', 'NSGA-II_rank: 4', 'change: 0.11942931095564477', 'is_elite: False']\n", + "Id: 37_31 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_31', 'origin': '36_87~CUW~36_91#MGNP'} Metrics: ['ELUC: -8.948290186895731', 'NSGA-II_crowding_distance: 0.30646469718660874', 'NSGA-II_rank: 3', 'change: 0.11909010577739315', 'is_elite: False']\n", + "Id: 35_43 Identity: {'ancestor_count': 26, 'ancestor_ids': ['30_89', '30_89'], 'birth_generation': 35, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '35_43', 'origin': '30_89~CUW~30_89#MGNP'} Metrics: ['ELUC: -9.070637173838016', 'NSGA-II_crowding_distance: 0.2424692206276058', 'NSGA-II_rank: 2', 'change: 0.1176904999290556', 'is_elite: False']\n", + "Id: 37_29 Identity: {'ancestor_count': 31, 'ancestor_ids': ['35_43', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_29', 'origin': '35_43~CUW~36_91#MGNP'} Metrics: ['ELUC: -9.28872950443373', 'NSGA-II_crowding_distance: 0.137071176834247', 'NSGA-II_rank: 1', 'change: 0.11366650420059626', 'is_elite: False']\n", + "Id: 37_98 Identity: {'ancestor_count': 27, 'ancestor_ids': ['35_43', '35_43'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_98', 'origin': '35_43~CUW~35_43#MGNP'} Metrics: ['ELUC: -9.44568269387275', 'NSGA-II_crowding_distance: 0.10682761929620493', 'NSGA-II_rank: 1', 'change: 0.12273743922243656', 'is_elite: False']\n", + "Id: 37_37 Identity: {'ancestor_count': 35, 'ancestor_ids': ['2_49', '36_37'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_37', 'origin': '2_49~CUW~36_37#MGNP'} Metrics: ['ELUC: -9.47452803478648', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29673333004021724', 'is_elite: False']\n", + "Id: 37_41 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_75', '36_99'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_41', 'origin': '36_75~CUW~36_99#MGNP'} Metrics: ['ELUC: -9.588951576678566', 'NSGA-II_crowding_distance: 0.3004353125567083', 'NSGA-II_rank: 3', 'change: 0.1437513008149744', 'is_elite: False']\n", + "Id: 37_21 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_21', 'origin': '36_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.645466223091852', 'NSGA-II_crowding_distance: 0.1897774146652913', 'NSGA-II_rank: 2', 'change: 0.13605481173729306', 'is_elite: False']\n", + "Id: 37_28 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_20', '36_83'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_28', 'origin': '36_20~CUW~36_83#MGNP'} Metrics: ['ELUC: -9.893487029572736', 'NSGA-II_crowding_distance: 0.23619614399660926', 'NSGA-II_rank: 2', 'change: 0.15533865388698892', 'is_elite: False']\n", + "Id: 37_83 Identity: {'ancestor_count': 35, 'ancestor_ids': ['35_43', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_83', 'origin': '35_43~CUW~36_87#MGNP'} Metrics: ['ELUC: -9.949870095672239', 'NSGA-II_crowding_distance: 0.17171575183708085', 'NSGA-II_rank: 1', 'change: 0.13432172550249874', 'is_elite: False']\n", + "Id: 37_78 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_37', '35_43'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_78', 'origin': '36_37~CUW~35_43#MGNP'} Metrics: ['ELUC: -10.004176499835058', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28586920237078045', 'is_elite: False']\n", + "Id: 37_79 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '2_49'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_79', 'origin': '36_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.308455822197955', 'NSGA-II_crowding_distance: 0.8609491462876991', 'NSGA-II_rank: 4', 'change: 0.26483647224655693', 'is_elite: False']\n", + "Id: 37_86 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '35_43'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_86', 'origin': '36_59~CUW~35_43#MGNP'} Metrics: ['ELUC: -10.905873465610961', 'NSGA-II_crowding_distance: 0.19626750068947135', 'NSGA-II_rank: 3', 'change: 0.15961069653289114', 'is_elite: False']\n", + "Id: 37_68 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_83', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_68', 'origin': '36_83~CUW~36_81#MGNP'} Metrics: ['ELUC: -10.994543318514465', 'NSGA-II_crowding_distance: 0.1815172536167339', 'NSGA-II_rank: 4', 'change: 0.27024914679877354', 'is_elite: False']\n", + "Id: 37_22 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '35_35'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_22', 'origin': '36_59~CUW~35_35#MGNP'} Metrics: ['ELUC: -11.157002336993658', 'NSGA-II_crowding_distance: 0.11115997950096834', 'NSGA-II_rank: 3', 'change: 0.1652494591956865', 'is_elite: False']\n", + "Id: 37_77 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '36_75'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_77', 'origin': '36_59~CUW~36_75#MGNP'} Metrics: ['ELUC: -11.478875068037556', 'NSGA-II_crowding_distance: 0.1611754746135015', 'NSGA-II_rank: 1', 'change: 0.1394696916233115', 'is_elite: False']\n", + "Id: 37_25 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '35_35'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_25', 'origin': '36_87~CUW~35_35#MGNP'} Metrics: ['ELUC: -11.759502515741541', 'NSGA-II_crowding_distance: 0.08720013382438441', 'NSGA-II_rank: 1', 'change: 0.15170287539153524', 'is_elite: False']\n", + "Id: 37_66 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_42', '35_35'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_66', 'origin': '36_42~CUW~35_35#MGNP'} Metrics: ['ELUC: -11.966228478805336', 'NSGA-II_crowding_distance: 0.6467310154631027', 'NSGA-II_rank: 3', 'change: 0.1688245545185203', 'is_elite: False']\n", + "Id: 37_20 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '35_43'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_20', 'origin': '36_59~CUW~35_43#MGNP'} Metrics: ['ELUC: -12.18248308851185', 'NSGA-II_crowding_distance: 0.6380429716643288', 'NSGA-II_rank: 2', 'change: 0.15947465886010206', 'is_elite: False']\n", + "Id: 37_14 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_75', '36_59'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_14', 'origin': '36_75~CUW~36_59#MGNP'} Metrics: ['ELUC: -12.263979365579349', 'NSGA-II_crowding_distance: 0.11999283552232967', 'NSGA-II_rank: 1', 'change: 0.15216480637365298', 'is_elite: False']\n", + "Id: 37_32 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_91', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_32', 'origin': '36_91~CUW~36_81#MGNP'} Metrics: ['ELUC: -12.294725820960652', 'NSGA-II_crowding_distance: 0.15756622398098424', 'NSGA-II_rank: 4', 'change: 0.27430747511950665', 'is_elite: False']\n", + "Id: 37_11 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '2_49'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_11', 'origin': '36_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.880876449230165', 'NSGA-II_crowding_distance: 0.2000317478248979', 'NSGA-II_rank: 4', 'change: 0.27610898603621886', 'is_elite: False']\n", + "Id: 37_47 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_75', '36_59'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_47', 'origin': '36_75~CUW~36_59#MGNP'} Metrics: ['ELUC: -13.131063570853465', 'NSGA-II_crowding_distance: 0.1127579484279824', 'NSGA-II_rank: 1', 'change: 0.1642302496195413', 'is_elite: False']\n", + "Id: 36_59 Identity: {'ancestor_count': 34, 'ancestor_ids': ['34_50', '35_15'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_59', 'origin': '34_50~CUW~35_15#MGNP'} Metrics: ['ELUC: -13.201366608330877', 'NSGA-II_crowding_distance: 0.09972423039854364', 'NSGA-II_rank: 1', 'change: 0.16990151492086397', 'is_elite: False']\n", + "Id: 37_53 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_75', '36_42'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_53', 'origin': '36_75~CUW~36_42#MGNP'} Metrics: ['ELUC: -13.419550925488029', 'NSGA-II_crowding_distance: 0.14866289736945476', 'NSGA-II_rank: 1', 'change: 0.18909001824277016', 'is_elite: False']\n", + "Id: 37_96 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_75', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_96', 'origin': '36_75~CUW~36_87#MGNP'} Metrics: ['ELUC: -13.879028054898962', 'NSGA-II_crowding_distance: 0.30911239022337444', 'NSGA-II_rank: 1', 'change: 0.20275908686827326', 'is_elite: True']\n", + "Id: 37_61 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_33', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_61', 'origin': '36_33~CUW~36_87#MGNP'} Metrics: ['ELUC: -14.740477502691371', 'NSGA-II_crowding_distance: 0.5421631664004506', 'NSGA-II_rank: 2', 'change: 0.2496839302032764', 'is_elite: False']\n", + "Id: 37_73 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '36_46'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_73', 'origin': '2_49~CUW~36_46#MGNP'} Metrics: ['ELUC: -14.836955731934141', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.27959828194744796', 'is_elite: False']\n", + "Id: 37_12 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_83', '36_75'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_12', 'origin': '36_83~CUW~36_75#MGNP'} Metrics: ['ELUC: -15.232052978441526', 'NSGA-II_crowding_distance: 0.8816127968292253', 'NSGA-II_rank: 3', 'change: 0.2548649899489032', 'is_elite: False']\n", + "Id: 37_39 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_33', '36_99'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_39', 'origin': '36_33~CUW~36_99#MGNP'} Metrics: ['ELUC: -15.423300009467757', 'NSGA-II_crowding_distance: 0.23740071292686876', 'NSGA-II_rank: 2', 'change: 0.2532409378304575', 'is_elite: False']\n", + "Id: 36_83 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_83', 'origin': '35_35~CUW~35_85#MGNP'} Metrics: ['ELUC: -15.495546120122349', 'NSGA-II_crowding_distance: 0.3364560759604242', 'NSGA-II_rank: 1', 'change: 0.24609198851403055', 'is_elite: True']\n", + "Id: 37_88 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_81', '36_51'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_88', 'origin': '36_81~CUW~36_51#MGNP'} Metrics: ['ELUC: -15.584590364077581', 'NSGA-II_crowding_distance: 0.31409106548260185', 'NSGA-II_rank: 2', 'change: 0.29964901165064795', 'is_elite: False']\n", + "Id: 37_81 Identity: {'ancestor_count': 35, 'ancestor_ids': ['35_35', '36_83'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_81', 'origin': '35_35~CUW~36_83#MGNP'} Metrics: ['ELUC: -16.070337504765387', 'NSGA-II_crowding_distance: 0.19173688679743156', 'NSGA-II_rank: 1', 'change: 0.2659628851448485', 'is_elite: False']\n", + "Id: 37_40 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_81', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_40', 'origin': '36_81~CUW~36_87#MGNP'} Metrics: ['ELUC: -16.713875445015304', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30487036288795055', 'is_elite: False']\n", + "Id: 37_69 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_33', '36_33'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_69', 'origin': '36_33~CUW~36_33#MGNP'} Metrics: ['ELUC: -16.805030073835297', 'NSGA-II_crowding_distance: 0.1945271851735569', 'NSGA-II_rank: 1', 'change: 0.2810796563222519', 'is_elite: True']\n", + "Id: 37_13 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_13', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.37144861463404', 'NSGA-II_crowding_distance: 0.11859915327654413', 'NSGA-II_rank: 1', 'change: 0.3019252055452351', 'is_elite: False']\n", + "Id: 37_57 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_81', '1_1'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_57', 'origin': '36_81~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.590520099477246', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30307435475856104', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 36_81 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_81', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 37_26 Identity: {'ancestor_count': 31, 'ancestor_ids': ['2_49', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_26', 'origin': '2_49~CUW~36_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 37_36 Identity: {'ancestor_count': 2, 'ancestor_ids': ['36_46', '2_49'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_36', 'origin': '36_46~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 37_45 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_45', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 37_59 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_59', '2_49'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_59', 'origin': '36_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 37_62 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_81', '2_49'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_62', 'origin': '36_81~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 37_82 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_81', '2_49'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_82', 'origin': '36_81~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 37_92 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_81', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_92', 'origin': '36_81~CUW~36_81#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 37.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 38...:\n", + "PopulationResponse:\n", + " Generation: 38\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/38/20240220-001420\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 38 and asking ESP for generation 39...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 38 data persisted.\n", + "Evaluated candidates:\n", + "Id: 38_82 Identity: {'ancestor_count': 31, 'ancestor_ids': ['2_49', '36_91'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_82', 'origin': '2_49~CUW~36_91#MGNP'} Metrics: ['ELUC: 20.928956322972493', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3019308473495487', 'is_elite: False']\n", + "Id: 38_60 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_77', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_60', 'origin': '37_77~CUW~2_49#MGNP'} Metrics: ['ELUC: 19.743948326672015', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26770654579095726', 'is_elite: False']\n", + "Id: 38_99 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_91', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_99', 'origin': '36_91~CUW~2_49#MGNP'} Metrics: ['ELUC: 19.267980026741647', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2906452498276633', 'is_elite: False']\n", + "Id: 38_89 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_83', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_89', 'origin': '36_83~CUW~2_49#MGNP'} Metrics: ['ELUC: 13.660247267353228', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27854000147843805', 'is_elite: False']\n", + "Id: 38_18 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_91', '37_92'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_18', 'origin': '36_91~CUW~37_92#MGNP'} Metrics: ['ELUC: 9.57496824620448', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27625288196780556', 'is_elite: False']\n", + "Id: 38_40 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_23', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_40', 'origin': '37_23~CUW~1_1#MGNP'} Metrics: ['ELUC: 4.604749361347226', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08239790696859292', 'is_elite: False']\n", + "Id: 38_73 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_69', '37_92'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_73', 'origin': '37_69~CUW~37_92#MGNP'} Metrics: ['ELUC: 3.8041569408539604', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23301361114121377', 'is_elite: False']\n", + "Id: 38_26 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_72', '37_81'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_26', 'origin': '36_72~CUW~37_81#MGNP'} Metrics: ['ELUC: 2.183298291346067', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06079850162144636', 'is_elite: False']\n", + "Id: 38_94 Identity: {'ancestor_count': 35, 'ancestor_ids': ['37_85', '36_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_94', 'origin': '37_85~CUW~36_83#MGNP'} Metrics: ['ELUC: 1.57539635376231', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10306189848747749', 'is_elite: False']\n", + "Id: 38_70 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_83', '36_72'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_70', 'origin': '36_83~CUW~36_72#MGNP'} Metrics: ['ELUC: 1.1747163502949913', 'NSGA-II_crowding_distance: 0.25681876572088497', 'NSGA-II_rank: 5', 'change: 0.08585498485943749', 'is_elite: False']\n", + "Id: 38_54 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '36_91'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_54', 'origin': '37_96~CUW~36_91#MGNP'} Metrics: ['ELUC: 0.9890509724341503', 'NSGA-II_crowding_distance: 0.16075122996250932', 'NSGA-II_rank: 5', 'change: 0.09082868123179387', 'is_elite: False']\n", + "Id: 38_33 Identity: {'ancestor_count': 36, 'ancestor_ids': ['1_1', '37_44'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_33', 'origin': '1_1~CUW~37_44#MGNP'} Metrics: ['ELUC: 0.5620996026047361', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05248311840010466', 'is_elite: False']\n", + "Id: 38_78 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '36_72'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_78', 'origin': '1_1~CUW~36_72#MGNP'} Metrics: ['ELUC: 0.4200842394812473', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.024100952345289126', 'is_elite: False']\n", + "Id: 38_53 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_85'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_53', 'origin': '37_96~CUW~37_85#MGNP'} Metrics: ['ELUC: 0.2877571361085682', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.15198588231099655', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 38_97 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_91', '36_72'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_97', 'origin': '36_91~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.07125266762757389', 'NSGA-II_crowding_distance: 0.38646566108348845', 'NSGA-II_rank: 4', 'change: 0.0612911805796966', 'is_elite: False']\n", + "Id: 38_28 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '36_72'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_28', 'origin': '1_1~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.12459684674503298', 'NSGA-II_crowding_distance: 0.0745619897526167', 'NSGA-II_rank: 1', 'change: 0.02192552190432766', 'is_elite: False']\n", + "Id: 38_14 Identity: {'ancestor_count': 28, 'ancestor_ids': ['36_72', '37_76'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_14', 'origin': '36_72~CUW~37_76#MGNP'} Metrics: ['ELUC: -0.13108031359050243', 'NSGA-II_crowding_distance: 0.1625914349392834', 'NSGA-II_rank: 3', 'change: 0.0571962551248492', 'is_elite: False']\n", + "Id: 38_92 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_92', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.2528565544907129', 'NSGA-II_crowding_distance: 0.07544402968122574', 'NSGA-II_rank: 1', 'change: 0.022854693410186037', 'is_elite: False']\n", + "Id: 38_36 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_81', '36_72'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_36', 'origin': '37_81~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.5513773948485613', 'NSGA-II_crowding_distance: 0.412877088838684', 'NSGA-II_rank: 5', 'change: 0.09782111291671977', 'is_elite: False']\n", + "Id: 38_27 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_92', '37_96'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_27', 'origin': '37_92~CUW~37_96#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 38_43 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_53', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_43', 'origin': '37_53~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9283544802033389', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.13264504029396273', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.2262982739895406', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 38_59 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_81', '37_29'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_59', 'origin': '37_81~CUW~37_29#MGNP'} Metrics: ['ELUC: -1.077488676384301', 'NSGA-II_crowding_distance: 0.1792021226164849', 'NSGA-II_rank: 3', 'change: 0.06468446473653638', 'is_elite: False']\n", + "Id: 38_31 Identity: {'ancestor_count': 31, 'ancestor_ids': ['36_91', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_31', 'origin': '36_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2428469170584064', 'NSGA-II_crowding_distance: 0.20377249419438487', 'NSGA-II_rank: 3', 'change: 0.08218492545735726', 'is_elite: False']\n", + "Id: 38_76 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_72', '36_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_76', 'origin': '36_72~CUW~36_83#MGNP'} Metrics: ['ELUC: -1.4577416846268174', 'NSGA-II_crowding_distance: 0.502244356723542', 'NSGA-II_rank: 6', 'change: 0.12700345076045946', 'is_elite: False']\n", + "Id: 38_50 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_72', '37_23'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_50', 'origin': '36_72~CUW~37_23#MGNP'} Metrics: ['ELUC: -1.8120403820081579', 'NSGA-II_crowding_distance: 0.3408230138088886', 'NSGA-II_rank: 2', 'change: 0.05473026596803764', 'is_elite: False']\n", + "Id: 38_58 Identity: {'ancestor_count': 36, 'ancestor_ids': ['2_49', '37_53'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_58', 'origin': '2_49~CUW~37_53#MGNP'} Metrics: ['ELUC: -1.9835692011055461', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.22839821214316078', 'is_elite: False']\n", + "Id: 38_61 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_72', '37_81'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_61', 'origin': '36_72~CUW~37_81#MGNP'} Metrics: ['ELUC: -2.046075705973319', 'NSGA-II_crowding_distance: 0.3358368500872674', 'NSGA-II_rank: 4', 'change: 0.08775614809778857', 'is_elite: False']\n", + "Id: 38_100 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_34', '37_23'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_100', 'origin': '37_34~CUW~37_23#MGNP'} Metrics: ['ELUC: -2.1122270796583353', 'NSGA-II_crowding_distance: 0.15840373733462476', 'NSGA-II_rank: 2', 'change: 0.06898762408499078', 'is_elite: False']\n", + "Id: 38_16 Identity: {'ancestor_count': 36, 'ancestor_ids': ['1_1', '37_44'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_16', 'origin': '1_1~CUW~37_44#MGNP'} Metrics: ['ELUC: -2.468260399164382', 'NSGA-II_crowding_distance: 0.2794406379241859', 'NSGA-II_rank: 1', 'change: 0.05278096920936311', 'is_elite: True']\n", + "Id: 38_20 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_53', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_20', 'origin': '37_53~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.5171976539944363', 'NSGA-II_crowding_distance: 0.2612104987661825', 'NSGA-II_rank: 4', 'change: 0.10606756925049307', 'is_elite: False']\n", + "Id: 38_72 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_72', '37_81'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_72', 'origin': '36_72~CUW~37_81#MGNP'} Metrics: ['ELUC: -2.740273969316485', 'NSGA-II_crowding_distance: 0.41089271083723455', 'NSGA-II_rank: 3', 'change: 0.08648373780913823', 'is_elite: False']\n", + "Id: 38_52 Identity: {'ancestor_count': 31, 'ancestor_ids': ['1_1', '36_91'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_52', 'origin': '1_1~CUW~36_91#MGNP'} Metrics: ['ELUC: -3.2518553225259783', 'NSGA-II_crowding_distance: 0.11019972263485144', 'NSGA-II_rank: 2', 'change: 0.07178411699643256', 'is_elite: False']\n", + "Id: 38_98 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_34', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_98', 'origin': '37_34~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.2639692423862936', 'NSGA-II_crowding_distance: 0.1258471427275951', 'NSGA-II_rank: 2', 'change: 0.07867774651217467', 'is_elite: False']\n", + "Id: 38_81 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_81', '37_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_81', 'origin': '37_81~CUW~37_83#MGNP'} Metrics: ['ELUC: -3.2842500343399714', 'NSGA-II_crowding_distance: 0.18560265374431606', 'NSGA-II_rank: 6', 'change: 0.1296878845396888', 'is_elite: False']\n", + "Id: 38_96 Identity: {'ancestor_count': 36, 'ancestor_ids': ['1_1', '37_81'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_96', 'origin': '1_1~CUW~37_81#MGNP'} Metrics: ['ELUC: -3.4225763313443167', 'NSGA-II_crowding_distance: 1.497755643276458', 'NSGA-II_rank: 6', 'change: 0.13448949614029543', 'is_elite: False']\n", + "Id: 38_47 Identity: {'ancestor_count': 28, 'ancestor_ids': ['1_1', '37_76'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_47', 'origin': '1_1~CUW~37_76#MGNP'} Metrics: ['ELUC: -3.534624731676916', 'NSGA-II_crowding_distance: 0.5301201349101818', 'NSGA-II_rank: 5', 'change: 0.12043767107816082', 'is_elite: False']\n", + "Id: 38_25 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_83', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_25', 'origin': '36_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.6514772405910034', 'NSGA-II_crowding_distance: 0.48943724098116903', 'NSGA-II_rank: 5', 'change: 0.16956588940128736', 'is_elite: False']\n", + "Id: 38_68 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_72', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_68', 'origin': '36_72~CUW~37_77#MGNP'} Metrics: ['ELUC: -3.711572192173216', 'NSGA-II_crowding_distance: 0.1375263203259439', 'NSGA-II_rank: 1', 'change: 0.06694312088801761', 'is_elite: False']\n", + "Id: 37_23 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_42', '36_99'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_23', 'origin': '36_42~CUW~36_99#MGNP'} Metrics: ['ELUC: -3.977134867787818', 'NSGA-II_crowding_distance: 0.09615779191093407', 'NSGA-II_rank: 1', 'change: 0.0682096936151932', 'is_elite: False']\n", + "Id: 38_46 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_69', '37_14'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_46', 'origin': '37_69~CUW~37_14#MGNP'} Metrics: ['ELUC: -4.303083795083406', 'NSGA-II_crowding_distance: 0.3042185189128168', 'NSGA-II_rank: 4', 'change: 0.11642483193398434', 'is_elite: False']\n", + "Id: 38_65 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_77', '37_44'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_65', 'origin': '37_77~CUW~37_44#MGNP'} Metrics: ['ELUC: -4.7486232670148745', 'NSGA-II_crowding_distance: 0.15121811758885928', 'NSGA-II_rank: 2', 'change: 0.08022110379848794', 'is_elite: False']\n", + "Id: 36_91 Identity: {'ancestor_count': 30, 'ancestor_ids': ['35_43', '34_91'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_91', 'origin': '35_43~CUW~34_91#MGNP'} Metrics: ['ELUC: -4.954977346855037', 'NSGA-II_crowding_distance: 0.12749312060313667', 'NSGA-II_rank: 1', 'change: 0.07453349440510564', 'is_elite: False']\n", + "Id: 38_67 Identity: {'ancestor_count': 36, 'ancestor_ids': ['1_1', '37_44'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_67', 'origin': '1_1~CUW~37_44#MGNP'} Metrics: ['ELUC: -4.9779298343293386', 'NSGA-II_crowding_distance: 0.19555400853996513', 'NSGA-II_rank: 2', 'change: 0.09004055596434339', 'is_elite: False']\n", + "Id: 38_12 Identity: {'ancestor_count': 28, 'ancestor_ids': ['37_76', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_12', 'origin': '37_76~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.4612267751694', 'NSGA-II_crowding_distance: 0.3959434845966159', 'NSGA-II_rank: 3', 'change: 0.11177642691090477', 'is_elite: False']\n", + "Id: 38_45 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_72', '36_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_45', 'origin': '36_72~CUW~36_83#MGNP'} Metrics: ['ELUC: -5.557914964015735', 'NSGA-II_crowding_distance: 0.21567325156846773', 'NSGA-II_rank: 4', 'change: 0.13229965930047952', 'is_elite: False']\n", + "Id: 38_85 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_44', '37_85'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_85', 'origin': '37_44~CUW~37_85#MGNP'} Metrics: ['ELUC: -5.586937273145861', 'NSGA-II_crowding_distance: 0.0572105119463113', 'NSGA-II_rank: 1', 'change: 0.07893195663075603', 'is_elite: False']\n", + "Id: 38_56 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_91', '37_34'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_56', 'origin': '36_91~CUW~37_34#MGNP'} Metrics: ['ELUC: -5.659348286611859', 'NSGA-II_crowding_distance: 0.16574425936146508', 'NSGA-II_rank: 1', 'change: 0.07965044428559907', 'is_elite: False']\n", + "Id: 38_75 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_83', '36_91'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_75', 'origin': '36_83~CUW~36_91#MGNP'} Metrics: ['ELUC: -6.253959181211258', 'NSGA-II_crowding_distance: 0.2529720945377808', 'NSGA-II_rank: 4', 'change: 0.13857890801549558', 'is_elite: False']\n", + "Id: 38_63 Identity: {'ancestor_count': 36, 'ancestor_ids': ['1_1', '37_69'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_63', 'origin': '1_1~CUW~37_69#MGNP'} Metrics: ['ELUC: -6.580374043021861', 'NSGA-II_crowding_distance: 1.0873104953899406', 'NSGA-II_rank: 5', 'change: 0.18439046051285313', 'is_elite: False']\n", + "Id: 38_49 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_83', '37_23'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_49', 'origin': '37_83~CUW~37_23#MGNP'} Metrics: ['ELUC: -6.876436717720418', 'NSGA-II_crowding_distance: 0.3565790284484696', 'NSGA-II_rank: 3', 'change: 0.11381592440002491', 'is_elite: False']\n", + "Id: 38_22 Identity: {'ancestor_count': 36, 'ancestor_ids': ['2_49', '37_96'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_22', 'origin': '2_49~CUW~37_96#MGNP'} Metrics: ['ELUC: -6.88742444248591', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.33355502995249103', 'is_elite: False']\n", + "Id: 38_57 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_91', '37_44'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_57', 'origin': '36_91~CUW~37_44#MGNP'} Metrics: ['ELUC: -7.011781514782079', 'NSGA-II_crowding_distance: 0.2245254944502911', 'NSGA-II_rank: 2', 'change: 0.09423920345016991', 'is_elite: False']\n", + "Id: 38_64 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_77', '37_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_64', 'origin': '37_77~CUW~37_83#MGNP'} Metrics: ['ELUC: -7.539589124508777', 'NSGA-II_crowding_distance: 0.1871934189103049', 'NSGA-II_rank: 2', 'change: 0.10666835752536796', 'is_elite: False']\n", + "Id: 37_44 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_44', 'origin': '36_87~CUW~36_91#MGNP'} Metrics: ['ELUC: -7.6324957427196285', 'NSGA-II_crowding_distance: 0.3166759370417624', 'NSGA-II_rank: 1', 'change: 0.09367259230543952', 'is_elite: True']\n", + "Id: 38_48 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_69', '37_76'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_48', 'origin': '37_69~CUW~37_76#MGNP'} Metrics: ['ELUC: -7.688341683769761', 'NSGA-II_crowding_distance: 0.24833305522336704', 'NSGA-II_rank: 4', 'change: 0.16102622923413681', 'is_elite: False']\n", + "Id: 38_90 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_90', 'origin': '37_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.075787275777765', 'NSGA-II_crowding_distance: 0.758994364513555', 'NSGA-II_rank: 4', 'change: 0.17145962377715432', 'is_elite: False']\n", + "Id: 38_21 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_83', '37_23'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_21', 'origin': '36_83~CUW~37_23#MGNP'} Metrics: ['ELUC: -8.217307828473654', 'NSGA-II_crowding_distance: 0.13174498403499946', 'NSGA-II_rank: 2', 'change: 0.12157727081769869', 'is_elite: False']\n", + "Id: 38_38 Identity: {'ancestor_count': 35, 'ancestor_ids': ['1_1', '36_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_38', 'origin': '1_1~CUW~36_83#MGNP'} Metrics: ['ELUC: -8.257338899722424', 'NSGA-II_crowding_distance: 0.33211899823149515', 'NSGA-II_rank: 3', 'change: 0.1518078094127707', 'is_elite: False']\n", + "Id: 38_24 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_29', '37_96'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_24', 'origin': '37_29~CUW~37_96#MGNP'} Metrics: ['ELUC: -8.58010308022876', 'NSGA-II_crowding_distance: 0.3075672119762158', 'NSGA-II_rank: 3', 'change: 0.16604990007115972', 'is_elite: False']\n", + "Id: 38_32 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_81', '37_76'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_32', 'origin': '37_81~CUW~37_76#MGNP'} Metrics: ['ELUC: -8.600391530917804', 'NSGA-II_crowding_distance: 0.20928889112993512', 'NSGA-II_rank: 2', 'change: 0.12283231261938422', 'is_elite: False']\n", + "Id: 38_80 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_69', '1_1'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_80', 'origin': '37_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.956053056896588', 'NSGA-II_crowding_distance: 0.45144936967552834', 'NSGA-II_rank: 3', 'change: 0.2147699427925244', 'is_elite: False']\n", + "Id: 38_44 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_91', '37_44'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_44', 'origin': '36_91~CUW~37_44#MGNP'} Metrics: ['ELUC: -9.13157629188264', 'NSGA-II_crowding_distance: 0.35644327215035226', 'NSGA-II_rank: 1', 'change: 0.1152147072985329', 'is_elite: True']\n", + "Id: 38_79 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '37_92'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_79', 'origin': '1_1~CUW~37_92#MGNP'} Metrics: ['ELUC: -9.556958958199644', 'NSGA-II_crowding_distance: 0.5409040717819433', 'NSGA-II_rank: 3', 'change: 0.2592748431193951', 'is_elite: False']\n", + "Id: 38_23 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_23', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_23', 'origin': '37_23~CUW~37_77#MGNP'} Metrics: ['ELUC: -10.175470818621815', 'NSGA-II_crowding_distance: 0.4496143198197197', 'NSGA-II_rank: 2', 'change: 0.14330075051780175', 'is_elite: False']\n", + "Id: 38_35 Identity: {'ancestor_count': 35, 'ancestor_ids': ['37_92', '36_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_35', 'origin': '37_92~CUW~36_83#MGNP'} Metrics: ['ELUC: -10.818902536745442', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2952261116884993', 'is_elite: False']\n", + "Id: 38_42 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_42', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -11.338910654843595', 'NSGA-II_crowding_distance: 0.22872767940907032', 'NSGA-II_rank: 1', 'change: 0.1371283178965993', 'is_elite: True']\n", + "Id: 38_19 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_83', '37_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_19', 'origin': '36_83~CUW~37_83#MGNP'} Metrics: ['ELUC: -11.425009795957061', 'NSGA-II_crowding_distance: 0.35551060413475843', 'NSGA-II_rank: 2', 'change: 0.18952186227809506', 'is_elite: False']\n", + "Id: 38_39 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_77', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_39', 'origin': '37_77~CUW~37_77#MGNP'} Metrics: ['ELUC: -11.642006555169196', 'NSGA-II_crowding_distance: 0.19650001600189515', 'NSGA-II_rank: 1', 'change: 0.14085917429255954', 'is_elite: False']\n", + "Id: 38_87 Identity: {'ancestor_count': 36, 'ancestor_ids': ['2_49', '37_23'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_87', 'origin': '2_49~CUW~37_23#MGNP'} Metrics: ['ELUC: -11.906606286657615', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2908465324718124', 'is_elite: False']\n", + "Id: 38_88 Identity: {'ancestor_count': 2, 'ancestor_ids': ['37_85', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_88', 'origin': '37_85~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.109915604731386', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2905660011667694', 'is_elite: False']\n", + "Id: 38_84 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_34', '37_92'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_84', 'origin': '37_34~CUW~37_92#MGNP'} Metrics: ['ELUC: -12.627724811797641', 'NSGA-II_crowding_distance: 0.8883175333584943', 'NSGA-II_rank: 4', 'change: 0.2724413258495666', 'is_elite: False']\n", + "Id: 38_93 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '36_72'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_93', 'origin': '37_96~CUW~36_72#MGNP'} Metrics: ['ELUC: -12.748806767234793', 'NSGA-II_crowding_distance: 0.1135456747023364', 'NSGA-II_rank: 2', 'change: 0.19110834913129016', 'is_elite: False']\n", + "Id: 38_29 Identity: {'ancestor_count': 36, 'ancestor_ids': ['2_49', '37_23'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_29', 'origin': '2_49~CUW~37_23#MGNP'} Metrics: ['ELUC: -12.776912195853793', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.32061252414100644', 'is_elite: False']\n", + "Id: 38_71 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_71', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -12.882564382626228', 'NSGA-II_crowding_distance: 0.20613380760410666', 'NSGA-II_rank: 1', 'change: 0.16956326408055497', 'is_elite: True']\n", + "Id: 38_77 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_83', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_77', 'origin': '37_83~CUW~37_77#MGNP'} Metrics: ['ELUC: -12.941670774201558', 'NSGA-II_crowding_distance: 0.1821970056289989', 'NSGA-II_rank: 2', 'change: 0.19472654068982007', 'is_elite: False']\n", + "Id: 38_13 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_83', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_13', 'origin': '36_83~CUW~37_77#MGNP'} Metrics: ['ELUC: -13.323550118401073', 'NSGA-II_crowding_distance: 0.14117693151718286', 'NSGA-II_rank: 1', 'change: 0.1738285961947405', 'is_elite: False']\n", + "Id: 38_83 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_69', '37_96'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_83', 'origin': '37_69~CUW~37_96#MGNP'} Metrics: ['ELUC: -13.464671420939531', 'NSGA-II_crowding_distance: 0.23710912606151216', 'NSGA-II_rank: 2', 'change: 0.22434388512537284', 'is_elite: False']\n", + "Id: 38_37 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_83', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_37', 'origin': '36_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.597872235445058', 'NSGA-II_crowding_distance: 0.4541242183626924', 'NSGA-II_rank: 3', 'change: 0.2688501452452478', 'is_elite: False']\n", + "Id: 38_15 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_53', '37_53'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_15', 'origin': '37_53~CUW~37_53#MGNP'} Metrics: ['ELUC: -13.77531338182151', 'NSGA-II_crowding_distance: 0.12855223627196027', 'NSGA-II_rank: 1', 'change: 0.19653708859594085', 'is_elite: False']\n", + "Id: 37_96 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_75', '36_87'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_96', 'origin': '36_75~CUW~36_87#MGNP'} Metrics: ['ELUC: -13.879028054898962', 'NSGA-II_crowding_distance: 0.16663252484901278', 'NSGA-II_rank: 1', 'change: 0.20275908686827326', 'is_elite: False']\n", + "Id: 38_55 Identity: {'ancestor_count': 28, 'ancestor_ids': ['37_76', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_55', 'origin': '37_76~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.043286770385143', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2948990284283733', 'is_elite: False']\n", + "Id: 38_95 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_83', '37_69'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_95', 'origin': '36_83~CUW~37_69#MGNP'} Metrics: ['ELUC: -14.209076439476938', 'NSGA-II_crowding_distance: 0.3229230224071784', 'NSGA-II_rank: 2', 'change: 0.23311465245555232', 'is_elite: False']\n", + "Id: 38_11 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_81', '36_91'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_11', 'origin': '37_81~CUW~36_91#MGNP'} Metrics: ['ELUC: -14.795979717257005', 'NSGA-II_crowding_distance: 0.2055800244258913', 'NSGA-II_rank: 1', 'change: 0.22893549825167567', 'is_elite: True']\n", + "Id: 38_74 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_34', '37_81'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_74', 'origin': '37_34~CUW~37_81#MGNP'} Metrics: ['ELUC: -15.14604522220129', 'NSGA-II_crowding_distance: 0.08796800061409912', 'NSGA-II_rank: 1', 'change: 0.24259791289410831', 'is_elite: False']\n", + "Id: 38_91 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_81', '36_83'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_91', 'origin': '37_81~CUW~36_83#MGNP'} Metrics: ['ELUC: -15.363372722198541', 'NSGA-II_crowding_distance: 0.031588195460213096', 'NSGA-II_rank: 1', 'change: 0.2455543550667199', 'is_elite: False']\n", + "Id: 36_83 Identity: {'ancestor_count': 34, 'ancestor_ids': ['35_35', '35_85'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_83', 'origin': '35_35~CUW~35_85#MGNP'} Metrics: ['ELUC: -15.495546120122349', 'NSGA-II_crowding_distance: 0.09570637676824635', 'NSGA-II_rank: 1', 'change: 0.24609198851403055', 'is_elite: False']\n", + "Id: 38_66 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_69'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_66', 'origin': '37_96~CUW~37_69#MGNP'} Metrics: ['ELUC: -16.101457405531114', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.263433086867565', 'is_elite: False']\n", + "Id: 38_86 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_53', '37_81'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_86', 'origin': '37_53~CUW~37_81#MGNP'} Metrics: ['ELUC: -16.167845166721108', 'NSGA-II_crowding_distance: 0.19173688679743156', 'NSGA-II_rank: 1', 'change: 0.2604588597216468', 'is_elite: False']\n", + "Id: 37_69 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_33', '36_33'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_69', 'origin': '36_33~CUW~36_33#MGNP'} Metrics: ['ELUC: -16.805030073835297', 'NSGA-II_crowding_distance: 0.14368314356214443', 'NSGA-II_rank: 1', 'change: 0.2810796563222519', 'is_elite: False']\n", + "Id: 38_62 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_69'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_62', 'origin': '37_96~CUW~37_69#MGNP'} Metrics: ['ELUC: -17.031477999697316', 'NSGA-II_crowding_distance: 0.09641882764549259', 'NSGA-II_rank: 1', 'change: 0.28867459237214554', 'is_elite: False']\n", + "Id: 38_51 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_92', '37_69'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_51', 'origin': '37_92~CUW~37_69#MGNP'} Metrics: ['ELUC: -17.31896369411333', 'NSGA-II_crowding_distance: 0.08026577050436398', 'NSGA-II_rank: 1', 'change: 0.30112727382368576', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 37_92 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_81', '36_81'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_92', 'origin': '36_81~CUW~36_81#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 38_17 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_17', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 38_30 Identity: {'ancestor_count': 4, 'ancestor_ids': ['2_49', '37_92'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_30', 'origin': '2_49~CUW~37_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 38_34 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_83', '37_92'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_34', 'origin': '37_83~CUW~37_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 38_41 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_92'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_41', 'origin': '37_96~CUW~37_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 38_69 Identity: {'ancestor_count': 4, 'ancestor_ids': ['37_92', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_69', 'origin': '37_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 38.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 39...:\n", + "PopulationResponse:\n", + " Generation: 39\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/39/20240220-002134\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 39 and asking ESP for generation 40...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 39 data persisted.\n", + "Evaluated candidates:\n", + "Id: 39_69 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_11', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_69', 'origin': '38_11~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 39_90 Identity: {'ancestor_count': 5, 'ancestor_ids': ['38_69', '1_1'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_90', 'origin': '38_69~CUW~1_1#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 39_80 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '38_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_80', 'origin': '38_71~CUW~38_69#MGNP'} Metrics: ['ELUC: 23.8167458465154', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.30352522150465816', 'is_elite: False']\n", + "Id: 39_52 Identity: {'ancestor_count': 5, 'ancestor_ids': ['38_69', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_52', 'origin': '38_69~CUW~36_72#MGNP'} Metrics: ['ELUC: 13.577924698285019', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2795067193246794', 'is_elite: False']\n", + "Id: 39_27 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_27', 'origin': '38_42~CUW~2_49#MGNP'} Metrics: ['ELUC: 13.473416513949111', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.27586032382180675', 'is_elite: False']\n", + "Id: 39_53 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_53', 'origin': '38_42~CUW~2_49#MGNP'} Metrics: ['ELUC: 7.9498519148832045', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.26253853234365404', 'is_elite: False']\n", + "Id: 39_83 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_83', 'origin': '38_42~CUW~36_72#MGNP'} Metrics: ['ELUC: 3.839922906726746', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08935105163026245', 'is_elite: False']\n", + "Id: 39_87 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_42'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_87', 'origin': '1_1~CUW~38_42#MGNP'} Metrics: ['ELUC: 2.7004005536138167', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06982942851375105', 'is_elite: False']\n", + "Id: 39_63 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_63', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: 1.6330343931214915', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3427678635214747', 'is_elite: False']\n", + "Id: 39_95 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_42'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_95', 'origin': '1_1~CUW~38_42#MGNP'} Metrics: ['ELUC: 1.0344755996599457', 'NSGA-II_crowding_distance: 0.47452291497641175', 'NSGA-II_rank: 5', 'change: 0.07578770194458505', 'is_elite: False']\n", + "Id: 39_86 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_39'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_86', 'origin': '38_44~CUW~38_39#MGNP'} Metrics: ['ELUC: 0.7238382436589036', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.11468127327462715', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 39_34 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_34', 'origin': '38_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.049902104853572195', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24053718108190858', 'is_elite: False']\n", + "Id: 39_62 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_62', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.09403071814226602', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.053618442194105734', 'is_elite: False']\n", + "Id: 39_11 Identity: {'ancestor_count': 36, 'ancestor_ids': ['2_49', '37_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_11', 'origin': '2_49~CUW~37_44#MGNP'} Metrics: ['ELUC: -0.12635921128857902', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2761135194093455', 'is_elite: False']\n", + "Id: 39_93 Identity: {'ancestor_count': 5, 'ancestor_ids': ['38_69', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_93', 'origin': '38_69~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.2622123148065811', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2552662645315951', 'is_elite: False']\n", + "Id: 39_54 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '38_39'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_54', 'origin': '38_16~CUW~38_39#MGNP'} Metrics: ['ELUC: -0.3227650483753427', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.10962455480569976', 'is_elite: False']\n", + "Id: 39_85 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '37_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_85', 'origin': '38_16~CUW~37_69#MGNP'} Metrics: ['ELUC: -0.35291688480294325', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.14067245498015468', 'is_elite: False']\n", + "Id: 39_26 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '38_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_26', 'origin': '1_1~CUW~38_69#MGNP'} Metrics: ['ELUC: -0.5531707322519565', 'NSGA-II_crowding_distance: 1.9359567776777968', 'NSGA-II_rank: 9', 'change: 0.23870269569276742', 'is_elite: False']\n", + "Id: 39_37 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_37', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.06291089984956855', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 39_50 Identity: {'ancestor_count': 5, 'ancestor_ids': ['38_69', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_50', 'origin': '38_69~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.042879785970365625', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 39_96 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_96', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.5764844877834577', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23885095727891797', 'is_elite: False']\n", + "Id: 39_79 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_39'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_79', 'origin': '1_1~CUW~38_39#MGNP'} Metrics: ['ELUC: -0.8055896800031014', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.1304242810835574', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.3008602637421573', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 39_44 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '38_68'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_44', 'origin': '38_71~CUW~38_68#MGNP'} Metrics: ['ELUC: -1.2750939622569322', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06633766053790448', 'is_elite: False']\n", + "Id: 39_100 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_39'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_100', 'origin': '38_44~CUW~38_39#MGNP'} Metrics: ['ELUC: -1.6354281183607329', 'NSGA-II_crowding_distance: 0.6825468022287675', 'NSGA-II_rank: 6', 'change: 0.09480169414974753', 'is_elite: False']\n", + "Id: 39_74 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_69', '1_1'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_74', 'origin': '37_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6495232605642003', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.14533317502655946', 'is_elite: False']\n", + "Id: 39_17 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_15', '38_16'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_17', 'origin': '38_15~CUW~38_16#MGNP'} Metrics: ['ELUC: -1.8560988000425824', 'NSGA-II_crowding_distance: 0.38264711000795415', 'NSGA-II_rank: 6', 'change: 0.11884620165990717', 'is_elite: False']\n", + "Id: 39_41 Identity: {'ancestor_count': 37, 'ancestor_ids': ['36_72', '38_39'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_41', 'origin': '36_72~CUW~38_39#MGNP'} Metrics: ['ELUC: -1.9394536085563288', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05883072127919596', 'is_elite: False']\n", + "Id: 39_31 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '37_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_31', 'origin': '38_71~CUW~37_44#MGNP'} Metrics: ['ELUC: -1.9698641865254614', 'NSGA-II_crowding_distance: 1.3405045369922854', 'NSGA-II_rank: 7', 'change: 0.12316998131923089', 'is_elite: False']\n", + "Id: 39_42 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '37_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_42', 'origin': '38_42~CUW~37_44#MGNP'} Metrics: ['ELUC: -2.298648942713716', 'NSGA-II_crowding_distance: 0.5967669941435542', 'NSGA-II_rank: 5', 'change: 0.08986623557752232', 'is_elite: False']\n", + "Id: 38_16 Identity: {'ancestor_count': 36, 'ancestor_ids': ['1_1', '37_44'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_16', 'origin': '1_1~CUW~37_44#MGNP'} Metrics: ['ELUC: -2.468260399164382', 'NSGA-II_crowding_distance: 0.19383270727879137', 'NSGA-II_rank: 1', 'change: 0.05278096920936311', 'is_elite: False']\n", + "Id: 39_20 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_42'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_20', 'origin': '38_44~CUW~38_42#MGNP'} Metrics: ['ELUC: -2.693697881557858', 'NSGA-II_crowding_distance: 0.5013456653808336', 'NSGA-II_rank: 4', 'change: 0.08477248514154931', 'is_elite: False']\n", + "Id: 39_84 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_84', 'origin': '38_16~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.7858358430448122', 'NSGA-II_crowding_distance: 0.1919805572024432', 'NSGA-II_rank: 2', 'change: 0.05486128432080961', 'is_elite: False']\n", + "Id: 39_48 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_72', '37_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_48', 'origin': '36_72~CUW~37_44#MGNP'} Metrics: ['ELUC: -2.9576809014878425', 'NSGA-II_crowding_distance: 0.05934820918080479', 'NSGA-II_rank: 1', 'change: 0.0541933897378419', 'is_elite: False']\n", + "Id: 39_55 Identity: {'ancestor_count': 37, 'ancestor_ids': ['37_44', '38_16'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_55', 'origin': '37_44~CUW~38_16#MGNP'} Metrics: ['ELUC: -2.9812511658467806', 'NSGA-II_crowding_distance: 0.11312165779594671', 'NSGA-II_rank: 2', 'change: 0.0603401020527016', 'is_elite: False']\n", + "Id: 39_30 Identity: {'ancestor_count': 37, 'ancestor_ids': ['37_44', '38_56'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_30', 'origin': '37_44~CUW~38_56#MGNP'} Metrics: ['ELUC: -3.2014884535320824', 'NSGA-II_crowding_distance: 0.10174424418339528', 'NSGA-II_rank: 1', 'change: 0.05804604617692448', 'is_elite: False']\n", + "Id: 39_61 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_68', '38_11'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_61', 'origin': '38_68~CUW~38_11#MGNP'} Metrics: ['ELUC: -3.2355768476751607', 'NSGA-II_crowding_distance: 0.3970985270049072', 'NSGA-II_rank: 3', 'change: 0.08126889092266758', 'is_elite: False']\n", + "Id: 39_45 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_45', 'origin': '38_42~CUW~36_72#MGNP'} Metrics: ['ELUC: -3.319610341745348', 'NSGA-II_crowding_distance: 0.2810685571913515', 'NSGA-II_rank: 2', 'change: 0.07546559917475978', 'is_elite: False']\n", + "Id: 39_21 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_44', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_21', 'origin': '37_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.842255256242071', 'NSGA-II_crowding_distance: 1.1944110847583234', 'NSGA-II_rank: 7', 'change: 0.2387350078783383', 'is_elite: False']\n", + "Id: 39_66 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '38_56'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_66', 'origin': '38_16~CUW~38_56#MGNP'} Metrics: ['ELUC: -3.9205592600755486', 'NSGA-II_crowding_distance: 0.1632535144514732', 'NSGA-II_rank: 1', 'change: 0.06821126229449317', 'is_elite: False']\n", + "Id: 39_75 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_44', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_75', 'origin': '37_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.008696689729594', 'NSGA-II_crowding_distance: 0.6594954630077146', 'NSGA-II_rank: 7', 'change: 0.2704684334489475', 'is_elite: False']\n", + "Id: 39_18 Identity: {'ancestor_count': 37, 'ancestor_ids': ['37_69', '38_71'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_18', 'origin': '37_69~CUW~38_71#MGNP'} Metrics: ['ELUC: -4.333362389623418', 'NSGA-II_crowding_distance: 1.2021928405341247', 'NSGA-II_rank: 6', 'change: 0.12005507473411114', 'is_elite: False']\n", + "Id: 39_29 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '38_71'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_29', 'origin': '38_16~CUW~38_71#MGNP'} Metrics: ['ELUC: -4.872503028086853', 'NSGA-II_crowding_distance: 0.4003299168978952', 'NSGA-II_rank: 5', 'change: 0.10734039780480904', 'is_elite: False']\n", + "Id: 39_22 Identity: {'ancestor_count': 37, 'ancestor_ids': ['36_72', '38_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_22', 'origin': '36_72~CUW~38_44#MGNP'} Metrics: ['ELUC: -5.019475853834374', 'NSGA-II_crowding_distance: 0.46164739388428166', 'NSGA-II_rank: 4', 'change: 0.09484979496542642', 'is_elite: False']\n", + "Id: 39_82 Identity: {'ancestor_count': 37, 'ancestor_ids': ['36_72', '38_56'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_82', 'origin': '36_72~CUW~38_56#MGNP'} Metrics: ['ELUC: -5.190341354834091', 'NSGA-II_crowding_distance: 0.25951764909725017', 'NSGA-II_rank: 3', 'change: 0.08661412745049725', 'is_elite: False']\n", + "Id: 39_59 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_42'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_59', 'origin': '38_44~CUW~38_42#MGNP'} Metrics: ['ELUC: -5.2135671725131765', 'NSGA-II_crowding_distance: 0.140386072418103', 'NSGA-II_rank: 3', 'change: 0.10203929020550759', 'is_elite: False']\n", + "Id: 39_40 Identity: {'ancestor_count': 37, 'ancestor_ids': ['37_44', '38_16'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_40', 'origin': '37_44~CUW~38_16#MGNP'} Metrics: ['ELUC: -5.221052598912648', 'NSGA-II_crowding_distance: 0.18251809341257372', 'NSGA-II_rank: 1', 'change: 0.07248463077045231', 'is_elite: False']\n", + "Id: 39_81 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '1_1'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_81', 'origin': '38_42~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.6442329523122865', 'NSGA-II_crowding_distance: 0.10109443455372014', 'NSGA-II_rank: 3', 'change: 0.1088328938181261', 'is_elite: False']\n", + "Id: 39_36 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_15', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_36', 'origin': '38_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.736727003886294', 'NSGA-II_crowding_distance: 1.0817305879792325', 'NSGA-II_rank: 6', 'change: 0.27906843046010615', 'is_elite: False']\n", + "Id: 39_56 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '38_11'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_56', 'origin': '38_16~CUW~38_11#MGNP'} Metrics: ['ELUC: -5.807336359521837', 'NSGA-II_crowding_distance: 0.7440193464375645', 'NSGA-II_rank: 5', 'change: 0.11862456496349269', 'is_elite: False']\n", + "Id: 39_39 Identity: {'ancestor_count': 5, 'ancestor_ids': ['38_69', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_39', 'origin': '38_69~CUW~36_72#MGNP'} Metrics: ['ELUC: -5.8499347318137715', 'NSGA-II_crowding_distance: 0.9069654501786321', 'NSGA-II_rank: 5', 'change: 0.25350782017158074', 'is_elite: False']\n", + "Id: 39_99 Identity: {'ancestor_count': 36, 'ancestor_ids': ['1_1', '37_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_99', 'origin': '1_1~CUW~37_44#MGNP'} Metrics: ['ELUC: -5.8778251652383195', 'NSGA-II_crowding_distance: 0.04417702162428663', 'NSGA-II_rank: 3', 'change: 0.11202465687198601', 'is_elite: False']\n", + "Id: 39_89 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_89', 'origin': '38_44~CUW~36_72#MGNP'} Metrics: ['ELUC: -5.921063649590494', 'NSGA-II_crowding_distance: 0.03798348446821304', 'NSGA-II_rank: 3', 'change: 0.11343599877693794', 'is_elite: False']\n", + "Id: 39_51 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_71'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_51', 'origin': '38_44~CUW~38_71#MGNP'} Metrics: ['ELUC: -5.937499058527559', 'NSGA-II_crowding_distance: 0.3496071846861065', 'NSGA-II_rank: 4', 'change: 0.11496255253941232', 'is_elite: False']\n", + "Id: 39_46 Identity: {'ancestor_count': 37, 'ancestor_ids': ['36_72', '38_86'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_46', 'origin': '36_72~CUW~38_86#MGNP'} Metrics: ['ELUC: -6.091756993147184', 'NSGA-II_crowding_distance: 0.41476209589970997', 'NSGA-II_rank: 4', 'change: 0.14440688721914482', 'is_elite: False']\n", + "Id: 39_65 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_65', 'origin': '38_44~CUW~36_72#MGNP'} Metrics: ['ELUC: -6.194122200493186', 'NSGA-II_crowding_distance: 0.34265855456373556', 'NSGA-II_rank: 3', 'change: 0.1145869921491708', 'is_elite: False']\n", + "Id: 39_76 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_76', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.2238167260767945', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2831398001840791', 'is_elite: False']\n", + "Id: 39_71 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '38_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_71', 'origin': '38_16~CUW~38_44#MGNP'} Metrics: ['ELUC: -6.244504431526956', 'NSGA-II_crowding_distance: 0.3131123359388428', 'NSGA-II_rank: 2', 'change: 0.08392058455391421', 'is_elite: False']\n", + "Id: 39_47 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_39', '38_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_47', 'origin': '38_39~CUW~38_44#MGNP'} Metrics: ['ELUC: -6.247758337617765', 'NSGA-II_crowding_distance: 0.26525962328688346', 'NSGA-II_rank: 2', 'change: 0.11181547231077135', 'is_elite: False']\n", + "Id: 39_24 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_56'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_24', 'origin': '38_44~CUW~38_56#MGNP'} Metrics: ['ELUC: -6.394725300132395', 'NSGA-II_crowding_distance: 0.15886075509626435', 'NSGA-II_rank: 1', 'change: 0.08068323368044818', 'is_elite: False']\n", + "Id: 39_32 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_69', '38_11'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_32', 'origin': '38_69~CUW~38_11#MGNP'} Metrics: ['ELUC: -6.960702469838141', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.27943640865397673', 'is_elite: False']\n", + "Id: 39_67 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_44', '36_72'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_67', 'origin': '37_44~CUW~36_72#MGNP'} Metrics: ['ELUC: -7.046085156590793', 'NSGA-II_crowding_distance: 0.11393178122635367', 'NSGA-II_rank: 1', 'change: 0.08891377485947231', 'is_elite: False']\n", + "Id: 37_44 Identity: {'ancestor_count': 35, 'ancestor_ids': ['36_87', '36_91'], 'birth_generation': 37, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '37_44', 'origin': '36_87~CUW~36_91#MGNP'} Metrics: ['ELUC: -7.6324957427196285', 'NSGA-II_crowding_distance: 0.06632597723354525', 'NSGA-II_rank: 1', 'change: 0.09367259230543952', 'is_elite: False']\n", + "Id: 39_92 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_16'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_92', 'origin': '38_44~CUW~38_16#MGNP'} Metrics: ['ELUC: -7.714903801240207', 'NSGA-II_crowding_distance: 0.1574580527220796', 'NSGA-II_rank: 1', 'change: 0.09735390984186172', 'is_elite: False']\n", + "Id: 39_91 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_13', '37_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_91', 'origin': '38_13~CUW~37_69#MGNP'} Metrics: ['ELUC: -7.874155610277332', 'NSGA-II_crowding_distance: 0.3895622241493695', 'NSGA-II_rank: 2', 'change: 0.126846946366903', 'is_elite: False']\n", + "Id: 39_35 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '1_1'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_35', 'origin': '38_42~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.937841077405', 'NSGA-II_crowding_distance: 1.1490471499330597', 'NSGA-II_rank: 4', 'change: 0.15971235093100028', 'is_elite: False']\n", + "Id: 39_72 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_13'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_72', 'origin': '1_1~CUW~38_13#MGNP'} Metrics: ['ELUC: -8.121498082283916', 'NSGA-II_crowding_distance: 0.3578992017688518', 'NSGA-II_rank: 3', 'change: 0.14819154666683032', 'is_elite: False']\n", + "Id: 39_25 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '38_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_25', 'origin': '1_1~CUW~38_69#MGNP'} Metrics: ['ELUC: -8.437904163776695', 'NSGA-II_crowding_distance: 0.43863981880584946', 'NSGA-II_rank: 5', 'change: 0.27273423416778375', 'is_elite: False']\n", + "Id: 39_68 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_11', '38_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_68', 'origin': '38_11~CUW~38_44#MGNP'} Metrics: ['ELUC: -8.589404993711673', 'NSGA-II_crowding_distance: 0.30511619322968975', 'NSGA-II_rank: 3', 'change: 0.1491595918032277', 'is_elite: False']\n", + "Id: 38_44 Identity: {'ancestor_count': 36, 'ancestor_ids': ['36_91', '37_44'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_44', 'origin': '36_91~CUW~37_44#MGNP'} Metrics: ['ELUC: -9.13157629188264', 'NSGA-II_crowding_distance: 0.19574821589963864', 'NSGA-II_rank: 1', 'change: 0.1152147072985329', 'is_elite: False']\n", + "Id: 39_14 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_44'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_14', 'origin': '38_44~CUW~38_44#MGNP'} Metrics: ['ELUC: -9.697313198317406', 'NSGA-II_crowding_distance: 0.15215221565615378', 'NSGA-II_rank: 1', 'change: 0.12211871671132565', 'is_elite: False']\n", + "Id: 39_60 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_16'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_60', 'origin': '2_49~CUW~38_16#MGNP'} Metrics: ['ELUC: -10.1046777934379', 'NSGA-II_crowding_distance: 0.17543889282206354', 'NSGA-II_rank: 5', 'change: 0.2781558028495314', 'is_elite: False']\n", + "Id: 39_16 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_16', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.319883848659696', 'NSGA-II_crowding_distance: 0.06573136077565428', 'NSGA-II_rank: 5', 'change: 0.2795776881483729', 'is_elite: False']\n", + "Id: 39_43 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_11'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_43', 'origin': '2_49~CUW~38_11#MGNP'} Metrics: ['ELUC: -10.359052128297535', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2882588593910364', 'is_elite: False']\n", + "Id: 39_19 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '37_96'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_19', 'origin': '38_44~CUW~37_96#MGNP'} Metrics: ['ELUC: -10.433417099292408', 'NSGA-II_crowding_distance: 0.8827444731175187', 'NSGA-II_rank: 3', 'change: 0.17285410130613008', 'is_elite: False']\n", + "Id: 39_49 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_11', '38_71'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_49', 'origin': '38_11~CUW~38_71#MGNP'} Metrics: ['ELUC: -10.770465298583893', 'NSGA-II_crowding_distance: 0.14367030057917168', 'NSGA-II_rank: 1', 'change: 0.13280108614616676', 'is_elite: False']\n", + "Id: 39_13 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '38_39'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_13', 'origin': '38_42~CUW~38_39#MGNP'} Metrics: ['ELUC: -11.232281256776185', 'NSGA-II_crowding_distance: 0.7032353056230045', 'NSGA-II_rank: 2', 'change: 0.13791693233127894', 'is_elite: False']\n", + "Id: 38_42 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_42', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -11.338910654843595', 'NSGA-II_crowding_distance: 0.2433330197740141', 'NSGA-II_rank: 1', 'change: 0.1371283178965993', 'is_elite: True']\n", + "Id: 39_77 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_39', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_77', 'origin': '38_39~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.692900882561583', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2672343700007569', 'is_elite: False']\n", + "Id: 39_73 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_73', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.685017242225848', 'NSGA-II_crowding_distance: 0.6467341636592283', 'NSGA-II_rank: 3', 'change: 0.26673802358869625', 'is_elite: False']\n", + "Id: 38_71 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_71', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -12.882564382626228', 'NSGA-II_crowding_distance: 0.22179996045785388', 'NSGA-II_rank: 1', 'change: 0.16956326408055497', 'is_elite: True']\n", + "Id: 39_78 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_78', 'origin': '38_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.991954873777843', 'NSGA-II_crowding_distance: 0.14981813355946805', 'NSGA-II_rank: 3', 'change: 0.2668774587295489', 'is_elite: False']\n", + "Id: 39_28 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '38_71'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_28', 'origin': '38_71~CUW~38_71#MGNP'} Metrics: ['ELUC: -13.15731260324501', 'NSGA-II_crowding_distance: 0.11031427695600361', 'NSGA-II_rank: 1', 'change: 0.1724496417086161', 'is_elite: False']\n", + "Id: 39_97 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_11'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_97', 'origin': '1_1~CUW~38_11#MGNP'} Metrics: ['ELUC: -13.344235006813562', 'NSGA-II_crowding_distance: 0.5699135168616323', 'NSGA-II_rank: 2', 'change: 0.22425999101909527', 'is_elite: False']\n", + "Id: 39_15 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_13', '37_96'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_15', 'origin': '38_13~CUW~37_96#MGNP'} Metrics: ['ELUC: -13.816024668403497', 'NSGA-II_crowding_distance: 0.2825095119102369', 'NSGA-II_rank: 1', 'change: 0.186637477189294', 'is_elite: True']\n", + "Id: 39_57 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_69', '38_39'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_57', 'origin': '38_69~CUW~38_39#MGNP'} Metrics: ['ELUC: -14.050862859507788', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2747361687970396', 'is_elite: False']\n", + "Id: 39_58 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_11', '37_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_58', 'origin': '38_11~CUW~37_69#MGNP'} Metrics: ['ELUC: -14.378189155055372', 'NSGA-II_crowding_distance: 0.5584559566963173', 'NSGA-II_rank: 2', 'change: 0.23521161121386347', 'is_elite: False']\n", + "Id: 38_11 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_81', '36_91'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_11', 'origin': '37_81~CUW~36_91#MGNP'} Metrics: ['ELUC: -14.795979717257005', 'NSGA-II_crowding_distance: 0.2365817114536499', 'NSGA-II_rank: 1', 'change: 0.22893549825167567', 'is_elite: True']\n", + "Id: 39_98 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_13', '38_11'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_98', 'origin': '38_13~CUW~38_11#MGNP'} Metrics: ['ELUC: -15.076306717363499', 'NSGA-II_crowding_distance: 0.11054996807770881', 'NSGA-II_rank: 1', 'change: 0.23584081276598806', 'is_elite: False']\n", + "Id: 39_64 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_86'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_64', 'origin': '1_1~CUW~38_86#MGNP'} Metrics: ['ELUC: -15.670587038328462', 'NSGA-II_crowding_distance: 0.2755787926426646', 'NSGA-II_rank: 1', 'change: 0.24707878928625562', 'is_elite: True']\n", + "Id: 39_33 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_62', '38_11'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_33', 'origin': '38_62~CUW~38_11#MGNP'} Metrics: ['ELUC: -16.958837490922203', 'NSGA-II_crowding_distance: 0.21238967729899833', 'NSGA-II_rank: 1', 'change: 0.2861202556815854', 'is_elite: True']\n", + "Id: 39_38 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_62', '37_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_38', 'origin': '38_62~CUW~37_69#MGNP'} Metrics: ['ELUC: -17.054326331990094', 'NSGA-II_crowding_distance: 0.09227958701478861', 'NSGA-II_rank: 1', 'change: 0.28696865351771755', 'is_elite: False']\n", + "Id: 39_12 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '38_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_12', 'origin': '37_96~CUW~38_69#MGNP'} Metrics: ['ELUC: -17.588630075760463', 'NSGA-II_crowding_distance: 0.08468364607214672', 'NSGA-II_rank: 1', 'change: 0.30296665369179704', 'is_elite: False']\n", + "Id: 39_70 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_70', 'origin': '37_96~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.589102823927824', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30303012630108417', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 38_69 Identity: {'ancestor_count': 4, 'ancestor_ids': ['37_92', '2_49'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_69', 'origin': '37_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 39_23 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_69', '38_39'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_23', 'origin': '38_69~CUW~38_39#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 39_88 Identity: {'ancestor_count': 5, 'ancestor_ids': ['38_69', '2_49'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_88', 'origin': '38_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 39_94 Identity: {'ancestor_count': 36, 'ancestor_ids': ['2_49', '37_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_94', 'origin': '2_49~CUW~37_69#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 39.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 40...:\n", + "PopulationResponse:\n", + " Generation: 40\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/40/20240220-002847\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 40 and asking ESP for generation 41...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 40 data persisted.\n", + "Evaluated candidates:\n", + "Id: 40_28 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_28', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.827587953729658', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.30375117088340564', 'is_elite: False']\n", + "Id: 40_66 Identity: {'ancestor_count': 37, 'ancestor_ids': ['39_94', '36_72'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_66', 'origin': '39_94~CUW~36_72#MGNP'} Metrics: ['ELUC: 21.359681567743564', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2884512595149107', 'is_elite: False']\n", + "Id: 40_19 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_19', 'origin': '38_71~CUW~39_94#MGNP'} Metrics: ['ELUC: 20.403804905439536', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.29100607116251165', 'is_elite: False']\n", + "Id: 40_53 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_33', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_53', 'origin': '39_33~CUW~39_94#MGNP'} Metrics: ['ELUC: 12.625450857797757', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27398431854483607', 'is_elite: False']\n", + "Id: 40_95 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_95', 'origin': '38_16~CUW~39_94#MGNP'} Metrics: ['ELUC: 3.1501203167946907', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23239995681188239', 'is_elite: False']\n", + "Id: 40_100 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '38_71'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_100', 'origin': '38_16~CUW~38_71#MGNP'} Metrics: ['ELUC: 2.9787073030769653', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.0928088928932174', 'is_elite: False']\n", + "Id: 40_96 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_42'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_96', 'origin': '1_1~CUW~38_42#MGNP'} Metrics: ['ELUC: 1.531243821692727', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.054012569656566284', 'is_elite: False']\n", + "Id: 40_98 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_92', '38_71'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_98', 'origin': '39_92~CUW~38_71#MGNP'} Metrics: ['ELUC: 0.6594746793119948', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08285499816234833', 'is_elite: False']\n", + "Id: 40_33 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_33', 'origin': '38_44~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.1678913698089609', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.23335971388955365', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 40_30 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '38_16'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_30', 'origin': '38_42~CUW~38_16#MGNP'} Metrics: ['ELUC: -0.1277587007636139', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06913407520128116', 'is_elite: False']\n", + "Id: 40_62 Identity: {'ancestor_count': 38, 'ancestor_ids': ['2_49', '39_15'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_62', 'origin': '2_49~CUW~39_15#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.9217754899951519', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 40_51 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '39_14'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_51', 'origin': '39_15~CUW~39_14#MGNP'} Metrics: ['ELUC: -0.779248173888869', 'NSGA-II_crowding_distance: 0.25764231695462864', 'NSGA-II_rank: 5', 'change: 0.08887011869851909', 'is_elite: False']\n", + "Id: 40_82 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_42'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_82', 'origin': '1_1~CUW~38_42#MGNP'} Metrics: ['ELUC: -0.8890269196805454', 'NSGA-II_crowding_distance: 0.18936347168071338', 'NSGA-II_rank: 5', 'change: 0.10477349264516701', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.34815984583672055', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 40_84 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_84', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.193780037915165', 'NSGA-II_crowding_distance: 0.3342909255590926', 'NSGA-II_rank: 2', 'change: 0.06644943722050164', 'is_elite: False']\n", + "Id: 40_20 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_42', '39_14'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_20', 'origin': '38_42~CUW~39_14#MGNP'} Metrics: ['ELUC: -1.4012807921159502', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07173526108181431', 'is_elite: False']\n", + "Id: 40_52 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_64', '36_72'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_52', 'origin': '39_64~CUW~36_72#MGNP'} Metrics: ['ELUC: -1.7975695954006332', 'NSGA-II_crowding_distance: 0.559622575415315', 'NSGA-II_rank: 5', 'change: 0.10628102874714641', 'is_elite: False']\n", + "Id: 40_18 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '39_67'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_18', 'origin': '38_42~CUW~39_67#MGNP'} Metrics: ['ELUC: -2.3996584502040688', 'NSGA-II_crowding_distance: 0.277189536742795', 'NSGA-II_rank: 4', 'change: 0.08259636208943871', 'is_elite: False']\n", + "Id: 40_44 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_24', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_44', 'origin': '39_24~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.643766903940853', 'NSGA-II_crowding_distance: 0.31084826330857307', 'NSGA-II_rank: 3', 'change: 0.06999493944126332', 'is_elite: False']\n", + "Id: 40_50 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_40', '39_24'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_50', 'origin': '39_40~CUW~39_24#MGNP'} Metrics: ['ELUC: -3.080507478227238', 'NSGA-II_crowding_distance: 0.2833410329091874', 'NSGA-II_rank: 1', 'change: 0.05650408879897068', 'is_elite: True']\n", + "Id: 40_97 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_33', '39_66'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_97', 'origin': '39_33~CUW~39_66#MGNP'} Metrics: ['ELUC: -3.3491640839537564', 'NSGA-II_crowding_distance: 0.3400029149885906', 'NSGA-II_rank: 4', 'change: 0.0987902067683412', 'is_elite: False']\n", + "Id: 40_73 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_73', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: -3.5653316594016586', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2729005910929419', 'is_elite: False']\n", + "Id: 40_37 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_66', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_37', 'origin': '39_66~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.6556846342158527', 'NSGA-II_crowding_distance: 0.19055568109760151', 'NSGA-II_rank: 2', 'change: 0.06973229173091987', 'is_elite: False']\n", + "Id: 40_64 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_16', '39_92'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_64', 'origin': '38_16~CUW~39_92#MGNP'} Metrics: ['ELUC: -3.663549123072675', 'NSGA-II_crowding_distance: 0.11514174860168794', 'NSGA-II_rank: 1', 'change: 0.06892187811059503', 'is_elite: False']\n", + "Id: 40_16 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_42'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_16', 'origin': '1_1~CUW~38_42#MGNP'} Metrics: ['ELUC: -3.8393932876608985', 'NSGA-II_crowding_distance: 0.43145502466810737', 'NSGA-II_rank: 3', 'change: 0.08660764571144858', 'is_elite: False']\n", + "Id: 40_88 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '38_44'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_88', 'origin': '38_71~CUW~38_44#MGNP'} Metrics: ['ELUC: -3.867771125818586', 'NSGA-II_crowding_distance: 0.2033891120655134', 'NSGA-II_rank: 2', 'change: 0.07909036008440107', 'is_elite: False']\n", + "Id: 40_12 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_14', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_12', 'origin': '39_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.251713711763857', 'NSGA-II_crowding_distance: 0.09236006343786918', 'NSGA-II_rank: 1', 'change: 0.07098408986441729', 'is_elite: False']\n", + "Id: 40_75 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_40', '38_42'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_75', 'origin': '39_40~CUW~38_42#MGNP'} Metrics: ['ELUC: -4.322704529216502', 'NSGA-II_crowding_distance: 0.3583858664834339', 'NSGA-II_rank: 4', 'change: 0.12388820859161638', 'is_elite: False']\n", + "Id: 40_35 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '36_72'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_35', 'origin': '39_15~CUW~36_72#MGNP'} Metrics: ['ELUC: -4.9361733355911195', 'NSGA-II_crowding_distance: 1.666701962622687', 'NSGA-II_rank: 5', 'change: 0.14495769185143484', 'is_elite: False']\n", + "Id: 40_58 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_40', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_58', 'origin': '39_40~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.033124883501339', 'NSGA-II_crowding_distance: 0.1686163796546539', 'NSGA-II_rank: 1', 'change: 0.07323794002483468', 'is_elite: True']\n", + "Id: 40_55 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_55', 'origin': '39_15~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.353943212950434', 'NSGA-II_crowding_distance: 1.0368787495022853', 'NSGA-II_rank: 4', 'change: 0.14270124868902223', 'is_elite: False']\n", + "Id: 40_63 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_66', '39_40'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_63', 'origin': '39_66~CUW~39_40#MGNP'} Metrics: ['ELUC: -6.10373449472216', 'NSGA-II_crowding_distance: 0.2643578290478161', 'NSGA-II_rank: 2', 'change: 0.08851005123462302', 'is_elite: False']\n", + "Id: 40_11 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_11', 'origin': '1_1~CUW~38_11#MGNP'} Metrics: ['ELUC: -6.4261917423277755', 'NSGA-II_crowding_distance: 0.43320420327840575', 'NSGA-II_rank: 3', 'change: 0.11454539492384208', 'is_elite: False']\n", + "Id: 40_57 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_24', '39_24'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_57', 'origin': '39_24~CUW~39_24#MGNP'} Metrics: ['ELUC: -6.475966446588169', 'NSGA-II_crowding_distance: 0.15289767595234902', 'NSGA-II_rank: 1', 'change: 0.08354920547845884', 'is_elite: False']\n", + "Id: 40_92 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_42'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_92', 'origin': '1_1~CUW~38_42#MGNP'} Metrics: ['ELUC: -6.598555772848506', 'NSGA-II_crowding_distance: 0.22718660724282913', 'NSGA-II_rank: 2', 'change: 0.10936928102263958', 'is_elite: False']\n", + "Id: 40_65 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_40', '39_14'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_65', 'origin': '39_40~CUW~39_14#MGNP'} Metrics: ['ELUC: -6.866597686561044', 'NSGA-II_crowding_distance: 0.14282216175836537', 'NSGA-II_rank: 1', 'change: 0.08774460062313198', 'is_elite: False']\n", + "Id: 40_72 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_24', '39_15'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_72', 'origin': '39_24~CUW~39_15#MGNP'} Metrics: ['ELUC: -7.329827652868826', 'NSGA-II_crowding_distance: 0.3294641257994774', 'NSGA-II_rank: 3', 'change: 0.135894237966075', 'is_elite: False']\n", + "Id: 40_15 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_44'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_15', 'origin': '1_1~CUW~38_44#MGNP'} Metrics: ['ELUC: -7.399954339983979', 'NSGA-II_crowding_distance: 0.21349802242963473', 'NSGA-II_rank: 1', 'change: 0.11048379637142026', 'is_elite: True']\n", + "Id: 40_54 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_24', '39_64'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_54', 'origin': '39_24~CUW~39_64#MGNP'} Metrics: ['ELUC: -7.741863012599945', 'NSGA-II_crowding_distance: 0.4954627901144658', 'NSGA-II_rank: 3', 'change: 0.1718760136453613', 'is_elite: False']\n", + "Id: 40_47 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_16', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_47', 'origin': '38_16~CUW~39_94#MGNP'} Metrics: ['ELUC: -7.9702624484387306', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25502076196389384', 'is_elite: False']\n", + "Id: 40_70 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_42', '39_66'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_70', 'origin': '38_42~CUW~39_66#MGNP'} Metrics: ['ELUC: -8.195116479458003', 'NSGA-II_crowding_distance: 0.42853667439057064', 'NSGA-II_rank: 2', 'change: 0.11785653208730709', 'is_elite: False']\n", + "Id: 40_31 Identity: {'ancestor_count': 37, 'ancestor_ids': ['39_94', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_31', 'origin': '39_94~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.673250340819898', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2942747838470902', 'is_elite: False']\n", + "Id: 40_22 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_16'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_22', 'origin': '2_49~CUW~38_16#MGNP'} Metrics: ['ELUC: -8.883315991234047', 'NSGA-II_crowding_distance: 1.2672837479664685', 'NSGA-II_rank: 7', 'change: 0.23993275134630176', 'is_elite: False']\n", + "Id: 40_79 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '38_44'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_79', 'origin': '38_44~CUW~38_44#MGNP'} Metrics: ['ELUC: -9.065058413427716', 'NSGA-II_crowding_distance: 0.1526425643148434', 'NSGA-II_rank: 1', 'change: 0.11413909654897646', 'is_elite: False']\n", + "Id: 40_14 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_24', '38_44'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_14', 'origin': '39_24~CUW~38_44#MGNP'} Metrics: ['ELUC: -9.665961041238948', 'NSGA-II_crowding_distance: 0.16369803579660835', 'NSGA-II_rank: 1', 'change: 0.11757410379699845', 'is_elite: True']\n", + "Id: 40_81 Identity: {'ancestor_count': 37, 'ancestor_ids': ['39_94', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_81', 'origin': '39_94~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.002547395313064', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2900516798983734', 'is_elite: False']\n", + "Id: 40_25 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_42'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_25', 'origin': '2_49~CUW~38_42#MGNP'} Metrics: ['ELUC: -10.329127039147716', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.29091127110674797', 'is_elite: False']\n", + "Id: 40_68 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '38_44'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_68', 'origin': '39_15~CUW~38_44#MGNP'} Metrics: ['ELUC: -10.61510272291863', 'NSGA-II_crowding_distance: 0.45049948178498345', 'NSGA-II_rank: 2', 'change: 0.16379248764558238', 'is_elite: False']\n", + "Id: 40_41 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '39_64'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_41', 'origin': '39_15~CUW~39_64#MGNP'} Metrics: ['ELUC: -11.087127413426568', 'NSGA-II_crowding_distance: 0.160684536016784', 'NSGA-II_rank: 1', 'change: 0.12866780825066765', 'is_elite: False']\n", + "Id: 38_42 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_42', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -11.338910654843595', 'NSGA-II_crowding_distance: 0.23917528372771282', 'NSGA-II_rank: 1', 'change: 0.1371283178965993', 'is_elite: True']\n", + "Id: 40_39 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_11', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_39', 'origin': '38_11~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.792149822284362', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2800167974206299', 'is_elite: False']\n", + "Id: 40_69 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_24', '38_71'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_69', 'origin': '39_24~CUW~38_71#MGNP'} Metrics: ['ELUC: -12.249722746428981', 'NSGA-II_crowding_distance: 0.44188067278541976', 'NSGA-II_rank: 3', 'change: 0.17851079850048146', 'is_elite: False']\n", + "Id: 40_71 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_71', 'origin': '38_71~CUW~39_94#MGNP'} Metrics: ['ELUC: -12.460921804104348', 'NSGA-II_crowding_distance: 0.8903088492602289', 'NSGA-II_rank: 7', 'change: 0.26162457315880794', 'is_elite: False']\n", + "Id: 40_59 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_59', 'origin': '1_1~CUW~38_11#MGNP'} Metrics: ['ELUC: -12.6146728609813', 'NSGA-II_crowding_distance: 0.9797589020138859', 'NSGA-II_rank: 4', 'change: 0.2076098942576118', 'is_elite: False']\n", + "Id: 40_94 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_42', '39_33'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_94', 'origin': '38_42~CUW~39_33#MGNP'} Metrics: ['ELUC: -12.765140431501932', 'NSGA-II_crowding_distance: 0.23091397477176073', 'NSGA-II_rank: 2', 'change: 0.17054370987509007', 'is_elite: False']\n", + "Id: 40_29 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_44', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_29', 'origin': '38_44~CUW~39_94#MGNP'} Metrics: ['ELUC: -12.790922161208435', 'NSGA-II_crowding_distance: 0.3562925174827989', 'NSGA-II_rank: 7', 'change: 0.2680461436258796', 'is_elite: False']\n", + "Id: 38_71 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_71', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -12.882564382626228', 'NSGA-II_crowding_distance: 0.28345825895034077', 'NSGA-II_rank: 1', 'change: 0.16956326408055497', 'is_elite: True']\n", + "Id: 40_34 Identity: {'ancestor_count': 38, 'ancestor_ids': ['2_49', '39_33'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_34', 'origin': '2_49~CUW~39_33#MGNP'} Metrics: ['ELUC: -12.930158021764846', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2758315558757438', 'is_elite: False']\n", + "Id: 40_76 Identity: {'ancestor_count': 38, 'ancestor_ids': ['36_72', '39_64'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_76', 'origin': '36_72~CUW~39_64#MGNP'} Metrics: ['ELUC: -13.000840584943818', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.23507134343468605', 'is_elite: False']\n", + "Id: 40_86 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_33', '36_72'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_86', 'origin': '39_33~CUW~36_72#MGNP'} Metrics: ['ELUC: -13.184211344509832', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.23320188552408683', 'is_elite: False']\n", + "Id: 40_67 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_67', 'origin': '1_1~CUW~38_11#MGNP'} Metrics: ['ELUC: -13.281789519350097', 'NSGA-II_crowding_distance: 0.4479842439887335', 'NSGA-II_rank: 4', 'change: 0.22019973916580576', 'is_elite: False']\n", + "Id: 40_32 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '39_15'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_32', 'origin': '39_15~CUW~39_15#MGNP'} Metrics: ['ELUC: -13.655970097584541', 'NSGA-II_crowding_distance: 0.2655455133205643', 'NSGA-II_rank: 3', 'change: 0.1872595524510634', 'is_elite: False']\n", + "Id: 40_45 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_11', '39_24'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_45', 'origin': '38_11~CUW~39_24#MGNP'} Metrics: ['ELUC: -13.670078953878278', 'NSGA-II_crowding_distance: 0.19193307315927216', 'NSGA-II_rank: 3', 'change: 0.2193834535923962', 'is_elite: False']\n", + "Id: 40_40 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '39_15'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_40', 'origin': '39_15~CUW~39_15#MGNP'} Metrics: ['ELUC: -13.673261589086199', 'NSGA-II_crowding_distance: 0.2721515648714691', 'NSGA-II_rank: 2', 'change: 0.1814820011538152', 'is_elite: False']\n", + "Id: 40_42 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '39_15'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_42', 'origin': '39_15~CUW~39_15#MGNP'} Metrics: ['ELUC: -13.73678234055478', 'NSGA-II_crowding_distance: 0.11031427695600361', 'NSGA-II_rank: 1', 'change: 0.18101332386883554', 'is_elite: False']\n", + "Id: 39_15 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_13', '37_96'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_15', 'origin': '38_13~CUW~37_96#MGNP'} Metrics: ['ELUC: -13.816024668403497', 'NSGA-II_crowding_distance: 0.05188371485299259', 'NSGA-II_rank: 1', 'change: 0.186637477189294', 'is_elite: False']\n", + "Id: 40_43 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_40', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_43', 'origin': '39_40~CUW~38_11#MGNP'} Metrics: ['ELUC: -14.008780612904262', 'NSGA-II_crowding_distance: 0.07301406624302184', 'NSGA-II_rank: 3', 'change: 0.22678973269659652', 'is_elite: False']\n", + "Id: 40_36 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_24', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_36', 'origin': '39_24~CUW~38_11#MGNP'} Metrics: ['ELUC: -14.02132539951712', 'NSGA-II_crowding_distance: 0.1979935589834409', 'NSGA-II_rank: 2', 'change: 0.22195907539578685', 'is_elite: False']\n", + "Id: 40_48 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_94', '39_15'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_48', 'origin': '39_94~CUW~39_15#MGNP'} Metrics: ['ELUC: -14.040290936702085', 'NSGA-II_crowding_distance: 0.3846656947598852', 'NSGA-II_rank: 4', 'change: 0.2812820156775651', 'is_elite: False']\n", + "Id: 40_78 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_14', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_78', 'origin': '39_14~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.042563031075897', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2915146340441202', 'is_elite: False']\n", + "Id: 40_21 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_71', '39_15'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_21', 'origin': '38_71~CUW~39_15#MGNP'} Metrics: ['ELUC: -14.057739285824468', 'NSGA-II_crowding_distance: 0.13513403415959024', 'NSGA-II_rank: 1', 'change: 0.19104752985000575', 'is_elite: False']\n", + "Id: 40_13 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_11', '39_64'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_13', 'origin': '38_11~CUW~39_64#MGNP'} Metrics: ['ELUC: -14.220168059997858', 'NSGA-II_crowding_distance: 0.44165198943436207', 'NSGA-II_rank: 3', 'change: 0.2282567193345171', 'is_elite: False']\n", + "Id: 40_80 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_14', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_80', 'origin': '39_14~CUW~38_11#MGNP'} Metrics: ['ELUC: -14.290554557610387', 'NSGA-II_crowding_distance: 0.14849163748668873', 'NSGA-II_rank: 2', 'change: 0.22274827964967445', 'is_elite: False']\n", + "Id: 40_90 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_11', '38_44'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_90', 'origin': '38_11~CUW~38_44#MGNP'} Metrics: ['ELUC: -14.3408952027285', 'NSGA-II_crowding_distance: 0.14877623516639937', 'NSGA-II_rank: 1', 'change: 0.2180512467200922', 'is_elite: False']\n", + "Id: 40_91 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_11', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_91', 'origin': '38_11~CUW~38_11#MGNP'} Metrics: ['ELUC: -14.642076765623205', 'NSGA-II_crowding_distance: 0.06236114525060178', 'NSGA-II_rank: 1', 'change: 0.2255226557457404', 'is_elite: False']\n", + "Id: 38_11 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_81', '36_91'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_11', 'origin': '37_81~CUW~36_91#MGNP'} Metrics: ['ELUC: -14.795979717257005', 'NSGA-II_crowding_distance: 0.02207890740351525', 'NSGA-II_rank: 1', 'change: 0.22893549825167567', 'is_elite: False']\n", + "Id: 40_93 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_11', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_93', 'origin': '38_11~CUW~38_11#MGNP'} Metrics: ['ELUC: -14.815894128871632', 'NSGA-II_crowding_distance: 0.018383992558192532', 'NSGA-II_rank: 1', 'change: 0.22916077545340255', 'is_elite: False']\n", + "Id: 40_49 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_64', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_49', 'origin': '39_64~CUW~38_11#MGNP'} Metrics: ['ELUC: -14.824228180521201', 'NSGA-II_crowding_distance: 0.055589855478328586', 'NSGA-II_rank: 1', 'change: 0.23394148680537408', 'is_elite: False']\n", + "Id: 40_27 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_27', 'origin': '38_71~CUW~38_11#MGNP'} Metrics: ['ELUC: -15.079434777195841', 'NSGA-II_crowding_distance: 0.2894454160531658', 'NSGA-II_rank: 2', 'change: 0.24516061714865317', 'is_elite: False']\n", + "Id: 40_74 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_66', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_74', 'origin': '39_66~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.283479809074622', 'NSGA-II_crowding_distance: 0.31666821423533414', 'NSGA-II_rank: 2', 'change: 0.2818969584520576', 'is_elite: False']\n", + "Id: 40_24 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_64', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_24', 'origin': '39_64~CUW~38_11#MGNP'} Metrics: ['ELUC: -15.40420960171823', 'NSGA-II_crowding_distance: 0.09216597551951627', 'NSGA-II_rank: 1', 'change: 0.23576365459922477', 'is_elite: False']\n", + "Id: 39_64 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_86'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_64', 'origin': '1_1~CUW~38_86#MGNP'} Metrics: ['ELUC: -15.670587038328462', 'NSGA-II_crowding_distance: 0.05975804500178135', 'NSGA-II_rank: 1', 'change: 0.24707878928625562', 'is_elite: False']\n", + "Id: 40_89 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_71', '39_64'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_89', 'origin': '38_71~CUW~39_64#MGNP'} Metrics: ['ELUC: -15.75582069680896', 'NSGA-II_crowding_distance: 0.027705784602774057', 'NSGA-II_rank: 1', 'change: 0.24762717484332106', 'is_elite: False']\n", + "Id: 40_77 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '39_64'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_77', 'origin': '39_15~CUW~39_64#MGNP'} Metrics: ['ELUC: -15.802453326442839', 'NSGA-II_crowding_distance: 0.034866820119212404', 'NSGA-II_rank: 1', 'change: 0.2531077664246859', 'is_elite: False']\n", + "Id: 40_85 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_33', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_85', 'origin': '39_33~CUW~39_94#MGNP'} Metrics: ['ELUC: -15.860314264654672', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30234006624102155', 'is_elite: False']\n", + "Id: 40_83 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '39_64'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_83', 'origin': '39_15~CUW~39_64#MGNP'} Metrics: ['ELUC: -15.952379359889923', 'NSGA-II_crowding_distance: 0.146087406863643', 'NSGA-II_rank: 1', 'change: 0.2546949958523962', 'is_elite: False']\n", + "Id: 40_99 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_33', '38_11'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_99', 'origin': '39_33~CUW~38_11#MGNP'} Metrics: ['ELUC: -16.723258326504954', 'NSGA-II_crowding_distance: 0.16256296008164295', 'NSGA-II_rank: 1', 'change: 0.28107064836976514', 'is_elite: False']\n", + "Id: 40_26 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_71'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_26', 'origin': '2_49~CUW~38_71#MGNP'} Metrics: ['ELUC: -16.905067159202993', 'NSGA-II_crowding_distance: 0.20579277403905666', 'NSGA-II_rank: 2', 'change: 0.3002481410069401', 'is_elite: False']\n", + "Id: 39_33 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_62', '38_11'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_33', 'origin': '38_62~CUW~38_11#MGNP'} Metrics: ['ELUC: -16.958837490922203', 'NSGA-II_crowding_distance: 0.04755066540948195', 'NSGA-II_rank: 1', 'change: 0.2861202556815854', 'is_elite: False']\n", + "Id: 40_17 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_64', '39_33'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_17', 'origin': '39_64~CUW~39_33#MGNP'} Metrics: ['ELUC: -16.996934514455972', 'NSGA-II_crowding_distance: 0.07302307730906551', 'NSGA-II_rank: 1', 'change: 0.290614337983823', 'is_elite: False']\n", + "Id: 40_87 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_71'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_87', 'origin': '2_49~CUW~38_71#MGNP'} Metrics: ['ELUC: -17.448437531272415', 'NSGA-II_crowding_distance: 0.07211388125215767', 'NSGA-II_rank: 1', 'change: 0.29960005102180176', 'is_elite: False']\n", + "Id: 40_60 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_33', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_60', 'origin': '39_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.56397209496143', 'NSGA-II_crowding_distance: 0.019931418178750087', 'NSGA-II_rank: 1', 'change: 0.3025087105624686', 'is_elite: False']\n", + "Id: 40_46 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_46', 'origin': '2_49~CUW~39_94#MGNP'} Metrics: ['ELUC: -17.597314078758053', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302041301005167', 'is_elite: False']\n", + "Id: 40_61 Identity: {'ancestor_count': 38, 'ancestor_ids': ['2_49', '39_33'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_61', 'origin': '2_49~CUW~39_33#MGNP'} Metrics: ['ELUC: -17.597345770578883', 'NSGA-II_crowding_distance: 0.003615585243088394', 'NSGA-II_rank: 1', 'change: 0.3030201233124242', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 39_94 Identity: {'ancestor_count': 36, 'ancestor_ids': ['2_49', '37_69'], 'birth_generation': 39, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '39_94', 'origin': '2_49~CUW~37_69#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 40_23 Identity: {'ancestor_count': 37, 'ancestor_ids': ['39_94', '39_94'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_23', 'origin': '39_94~CUW~39_94#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 40_38 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_38', 'origin': '39_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 40_56 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_56', 'origin': '39_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 40.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 41...:\n", + "PopulationResponse:\n", + " Generation: 41\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/41/20240220-003558\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 41 and asking ESP for generation 42...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 41 data persisted.\n", + "Evaluated candidates:\n", + "Id: 41_51 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_51', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.82078924454372', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.30375993790671396', 'is_elite: False']\n", + "Id: 41_58 Identity: {'ancestor_count': 39, 'ancestor_ids': ['2_49', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_58', 'origin': '2_49~CUW~40_56#MGNP'} Metrics: ['ELUC: 8.491713810774659', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2699014257792219', 'is_elite: False']\n", + "Id: 41_34 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_56', '40_58'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_34', 'origin': '40_56~CUW~40_58#MGNP'} Metrics: ['ELUC: 1.2479384497992347', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3243678069598304', 'is_elite: False']\n", + "Id: 41_69 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_50'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_69', 'origin': '1_1~CUW~40_50#MGNP'} Metrics: ['ELUC: 0.9658266499323711', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05336126829195365', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 41_77 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_57', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_77', 'origin': '40_57~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.054558072775549554', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04843808281318433', 'is_elite: False']\n", + "Id: 41_92 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '36_72'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_92', 'origin': '36_72~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.3833820189977569', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03588864884683016', 'is_elite: False']\n", + "Id: 41_11 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_11', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 41_33 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_56', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_33', 'origin': '40_56~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 41_74 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_42', '40_65'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_74', 'origin': '40_42~CUW~40_65#MGNP'} Metrics: ['ELUC: -0.5927301201214963', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.1183252985717932', 'is_elite: False']\n", + "Id: 41_98 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_99'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_98', 'origin': '1_1~CUW~40_99#MGNP'} Metrics: ['ELUC: -0.6292420729062334', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.12118699476079302', 'is_elite: False']\n", + "Id: 41_30 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_64', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_30', 'origin': '40_64~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7353072870044717', 'NSGA-II_crowding_distance: 0.2058195737806928', 'NSGA-II_rank: 2', 'change: 0.0364672831205141', 'is_elite: False']\n", + "Id: 41_60 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_58', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_60', 'origin': '40_58~CUW~38_71#MGNP'} Metrics: ['ELUC: -0.8292446890317839', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08816812444919746', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.1918930580861849', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 41_62 Identity: {'ancestor_count': 38, 'ancestor_ids': ['1_1', '40_15'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_62', 'origin': '1_1~CUW~40_15#MGNP'} Metrics: ['ELUC: -1.2598381926369453', 'NSGA-II_crowding_distance: 0.13315771351437883', 'NSGA-II_rank: 1', 'change: 0.040774880685775824', 'is_elite: False']\n", + "Id: 41_13 Identity: {'ancestor_count': 38, 'ancestor_ids': ['40_15', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_13', 'origin': '40_15~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2958205187372327', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07912531734584008', 'is_elite: False']\n", + "Id: 41_72 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_72', 'origin': '38_42~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.552548974504934', 'NSGA-II_crowding_distance: 0.39549908146662194', 'NSGA-II_rank: 4', 'change: 0.07577539007620113', 'is_elite: False']\n", + "Id: 41_50 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_50', '38_42'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_50', 'origin': '40_50~CUW~38_42#MGNP'} Metrics: ['ELUC: -2.034788695886224', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.1374704878563369', 'is_elite: False']\n", + "Id: 41_76 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '36_72'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_76', 'origin': '38_42~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.0434093515042577', 'NSGA-II_crowding_distance: 0.3987147338201711', 'NSGA-II_rank: 4', 'change: 0.09413817453355271', 'is_elite: False']\n", + "Id: 41_93 Identity: {'ancestor_count': 39, 'ancestor_ids': ['36_72', '40_57'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_93', 'origin': '36_72~CUW~40_57#MGNP'} Metrics: ['ELUC: -2.058901972886706', 'NSGA-II_crowding_distance: 0.18245593603392773', 'NSGA-II_rank: 1', 'change: 0.05134187917195516', 'is_elite: False']\n", + "Id: 41_68 Identity: {'ancestor_count': 39, 'ancestor_ids': ['36_72', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_68', 'origin': '36_72~CUW~40_56#MGNP'} Metrics: ['ELUC: -2.2798754036157844', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23576402853406472', 'is_elite: False']\n", + "Id: 41_75 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_50', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_75', 'origin': '40_50~CUW~40_41#MGNP'} Metrics: ['ELUC: -2.3482198021898273', 'NSGA-II_crowding_distance: 0.2685316529112707', 'NSGA-II_rank: 3', 'change: 0.05902165824029149', 'is_elite: False']\n", + "Id: 41_67 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_67', 'origin': '1_1~CUW~40_41#MGNP'} Metrics: ['ELUC: -2.5138547580794164', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.11898467168878399', 'is_elite: False']\n", + "Id: 41_87 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_57'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_87', 'origin': '1_1~CUW~40_57#MGNP'} Metrics: ['ELUC: -2.559269751562052', 'NSGA-II_crowding_distance: 0.34969021874363576', 'NSGA-II_rank: 3', 'change: 0.06785634650653403', 'is_elite: False']\n", + "Id: 41_37 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_57'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_37', 'origin': '1_1~CUW~40_57#MGNP'} Metrics: ['ELUC: -2.818409076821034', 'NSGA-II_crowding_distance: 0.21139609822954283', 'NSGA-II_rank: 2', 'change: 0.053039706366341366', 'is_elite: False']\n", + "Id: 41_35 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_65', '40_90'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_35', 'origin': '40_65~CUW~40_90#MGNP'} Metrics: ['ELUC: -3.0311149466188425', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1153355052111569', 'is_elite: False']\n", + "Id: 40_50 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_40', '39_24'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_50', 'origin': '39_40~CUW~39_24#MGNP'} Metrics: ['ELUC: -3.080507478227238', 'NSGA-II_crowding_distance: 0.09879804242500564', 'NSGA-II_rank: 2', 'change: 0.05650408879897068', 'is_elite: False']\n", + "Id: 41_94 Identity: {'ancestor_count': 39, 'ancestor_ids': ['38_71', '40_50'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_94', 'origin': '38_71~CUW~40_50#MGNP'} Metrics: ['ELUC: -3.1944078971430767', 'NSGA-II_crowding_distance: 0.5713103685914951', 'NSGA-II_rank: 6', 'change: 0.11144409625481484', 'is_elite: False']\n", + "Id: 41_95 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_57', '38_42'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_95', 'origin': '40_57~CUW~38_42#MGNP'} Metrics: ['ELUC: -3.4130624711781112', 'NSGA-II_crowding_distance: 0.12478684542227486', 'NSGA-II_rank: 2', 'change: 0.07019548725025439', 'is_elite: False']\n", + "Id: 41_83 Identity: {'ancestor_count': 39, 'ancestor_ids': ['36_72', '40_50'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_83', 'origin': '36_72~CUW~40_50#MGNP'} Metrics: ['ELUC: -3.6817325380451673', 'NSGA-II_crowding_distance: 0.621100787756415', 'NSGA-II_rank: 5', 'change: 0.10623555609857395', 'is_elite: False']\n", + "Id: 41_47 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_50', '36_72'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_47', 'origin': '40_50~CUW~36_72#MGNP'} Metrics: ['ELUC: -3.780838916722727', 'NSGA-II_crowding_distance: 0.18591295027047694', 'NSGA-II_rank: 1', 'change: 0.05243350667424463', 'is_elite: False']\n", + "Id: 41_17 Identity: {'ancestor_count': 38, 'ancestor_ids': ['40_15', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_17', 'origin': '40_15~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.9558782700824286', 'NSGA-II_crowding_distance: 0.125152699286018', 'NSGA-II_rank: 2', 'change: 0.07624125435739519', 'is_elite: False']\n", + "Id: 41_22 Identity: {'ancestor_count': 37, 'ancestor_ids': ['36_72', '38_42'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_22', 'origin': '36_72~CUW~38_42#MGNP'} Metrics: ['ELUC: -3.9923418213835964', 'NSGA-II_crowding_distance: 0.36773228187789897', 'NSGA-II_rank: 6', 'change: 0.11285430320638173', 'is_elite: False']\n", + "Id: 41_63 Identity: {'ancestor_count': 39, 'ancestor_ids': ['36_72', '40_14'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_63', 'origin': '36_72~CUW~40_14#MGNP'} Metrics: ['ELUC: -4.254083017562885', 'NSGA-II_crowding_distance: 0.14094924015853288', 'NSGA-II_rank: 1', 'change: 0.06956126153360713', 'is_elite: False']\n", + "Id: 41_100 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_14', '38_42'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_100', 'origin': '40_14~CUW~38_42#MGNP'} Metrics: ['ELUC: -4.550578113731373', 'NSGA-II_crowding_distance: 0.13612534306229368', 'NSGA-II_rank: 2', 'change: 0.08595685493084229', 'is_elite: False']\n", + "Id: 41_84 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_84', 'origin': '38_42~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.717508756157653', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1566915951140528', 'is_elite: False']\n", + "Id: 40_58 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_40', '1_1'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_58', 'origin': '39_40~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.033124883501339', 'NSGA-II_crowding_distance: 0.1352298009169572', 'NSGA-II_rank: 1', 'change: 0.07323794002483468', 'is_elite: False']\n", + "Id: 41_42 Identity: {'ancestor_count': 38, 'ancestor_ids': ['40_15', '36_72'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_42', 'origin': '40_15~CUW~36_72#MGNP'} Metrics: ['ELUC: -5.038690148894881', 'NSGA-II_crowding_distance: 0.4257616211403881', 'NSGA-II_rank: 3', 'change: 0.09385141300045814', 'is_elite: False']\n", + "Id: 41_15 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_50', '40_15'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_15', 'origin': '40_50~CUW~40_15#MGNP'} Metrics: ['ELUC: -5.406527755043374', 'NSGA-II_crowding_distance: 0.5846096626952559', 'NSGA-II_rank: 6', 'change: 0.1227837257457366', 'is_elite: False']\n", + "Id: 41_64 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_65', '40_15'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_64', 'origin': '40_65~CUW~40_15#MGNP'} Metrics: ['ELUC: -5.454785199253741', 'NSGA-II_crowding_distance: 0.15707588530627903', 'NSGA-II_rank: 2', 'change: 0.08931846399839659', 'is_elite: False']\n", + "Id: 41_56 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_14', '40_57'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_56', 'origin': '40_14~CUW~40_57#MGNP'} Metrics: ['ELUC: -5.816342182439225', 'NSGA-II_crowding_distance: 0.1735074294347322', 'NSGA-II_rank: 1', 'change: 0.08339880098031278', 'is_elite: False']\n", + "Id: 41_41 Identity: {'ancestor_count': 38, 'ancestor_ids': ['40_15', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_41', 'origin': '40_15~CUW~38_71#MGNP'} Metrics: ['ELUC: -5.915077240635763', 'NSGA-II_crowding_distance: 1.179210184157817', 'NSGA-II_rank: 6', 'change: 0.17205663462224574', 'is_elite: False']\n", + "Id: 41_61 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_15', '40_58'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_61', 'origin': '40_15~CUW~40_58#MGNP'} Metrics: ['ELUC: -5.9495091069208', 'NSGA-II_crowding_distance: 0.3581658250599914', 'NSGA-II_rank: 4', 'change: 0.0962706494297055', 'is_elite: False']\n", + "Id: 41_70 Identity: {'ancestor_count': 38, 'ancestor_ids': ['40_79', '38_42'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_70', 'origin': '40_79~CUW~38_42#MGNP'} Metrics: ['ELUC: -6.149428412292748', 'NSGA-II_crowding_distance: 0.5762684257073197', 'NSGA-II_rank: 5', 'change: 0.11197935678672162', 'is_elite: False']\n", + "Id: 41_31 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_15', '40_99'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_31', 'origin': '40_15~CUW~40_99#MGNP'} Metrics: ['ELUC: -6.261336468019392', 'NSGA-II_crowding_distance: 0.08215580154537352', 'NSGA-II_rank: 4', 'change: 0.10849475933752739', 'is_elite: False']\n", + "Id: 41_12 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_58', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_12', 'origin': '40_58~CUW~40_41#MGNP'} Metrics: ['ELUC: -6.274697884064896', 'NSGA-II_crowding_distance: 0.13936924502201053', 'NSGA-II_rank: 4', 'change: 0.10927591984495971', 'is_elite: False']\n", + "Id: 41_65 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_50', '40_15'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_65', 'origin': '40_50~CUW~40_15#MGNP'} Metrics: ['ELUC: -6.728078480502522', 'NSGA-II_crowding_distance: 0.26663905180442765', 'NSGA-II_rank: 3', 'change: 0.09534432998635443', 'is_elite: False']\n", + "Id: 41_79 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_57', '40_50'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_79', 'origin': '40_57~CUW~40_50#MGNP'} Metrics: ['ELUC: -6.945256777082781', 'NSGA-II_crowding_distance: 0.19235356177170715', 'NSGA-II_rank: 2', 'change: 0.09071184985070768', 'is_elite: False']\n", + "Id: 41_32 Identity: {'ancestor_count': 38, 'ancestor_ids': ['38_71', '40_15'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_32', 'origin': '38_71~CUW~40_15#MGNP'} Metrics: ['ELUC: -7.077773414666772', 'NSGA-II_crowding_distance: 0.9564329672979313', 'NSGA-II_rank: 5', 'change: 0.15894724721301465', 'is_elite: False']\n", + "Id: 41_38 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_14', '40_90'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_38', 'origin': '40_14~CUW~40_90#MGNP'} Metrics: ['ELUC: -7.210361861732345', 'NSGA-II_crowding_distance: 0.19225014085618916', 'NSGA-II_rank: 1', 'change: 0.088060307771272', 'is_elite: True']\n", + "Id: 41_45 Identity: {'ancestor_count': 37, 'ancestor_ids': ['36_72', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_45', 'origin': '36_72~CUW~38_71#MGNP'} Metrics: ['ELUC: -7.262243593810068', 'NSGA-II_crowding_distance: 0.23632405914029025', 'NSGA-II_rank: 4', 'change: 0.12376392343056182', 'is_elite: False']\n", + "Id: 41_36 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_50', '40_21'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_36', 'origin': '40_50~CUW~40_21#MGNP'} Metrics: ['ELUC: -7.396978751499999', 'NSGA-II_crowding_distance: 0.25619536920799735', 'NSGA-II_rank: 3', 'change: 0.11528393853353004', 'is_elite: False']\n", + "Id: 40_15 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_44'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_15', 'origin': '1_1~CUW~38_44#MGNP'} Metrics: ['ELUC: -7.399954339983979', 'NSGA-II_crowding_distance: 0.2051068896764251', 'NSGA-II_rank: 2', 'change: 0.11048379637142026', 'is_elite: False']\n", + "Id: 41_19 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_15', '40_57'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_19', 'origin': '40_15~CUW~40_57#MGNP'} Metrics: ['ELUC: -7.9272905273672905', 'NSGA-II_crowding_distance: 0.1381029822015975', 'NSGA-II_rank: 1', 'change: 0.10493851465700882', 'is_elite: False']\n", + "Id: 41_99 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '2_49'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_99', 'origin': '38_71~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.038610777635975', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.27439167584664714', 'is_elite: False']\n", + "Id: 41_49 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_57', '40_50'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_49', 'origin': '40_57~CUW~40_50#MGNP'} Metrics: ['ELUC: -8.218138396970899', 'NSGA-II_crowding_distance: 0.10724527483384969', 'NSGA-II_rank: 1', 'change: 0.11216488158133422', 'is_elite: False']\n", + "Id: 41_18 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '36_72'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_18', 'origin': '40_99~CUW~36_72#MGNP'} Metrics: ['ELUC: -8.224289610549544', 'NSGA-II_crowding_distance: 0.38120622038466867', 'NSGA-II_rank: 4', 'change: 0.13135116608906214', 'is_elite: False']\n", + "Id: 41_23 Identity: {'ancestor_count': 39, 'ancestor_ids': ['38_42', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_23', 'origin': '38_42~CUW~40_56#MGNP'} Metrics: ['ELUC: -8.472712772655113', 'NSGA-II_crowding_distance: 0.9286033493421428', 'NSGA-II_rank: 5', 'change: 0.26598081869543144', 'is_elite: False']\n", + "Id: 41_97 Identity: {'ancestor_count': 39, 'ancestor_ids': ['38_42', '40_57'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_97', 'origin': '38_42~CUW~40_57#MGNP'} Metrics: ['ELUC: -8.769182371105055', 'NSGA-II_crowding_distance: 0.210232423702718', 'NSGA-II_rank: 3', 'change: 0.11969296639239575', 'is_elite: False']\n", + "Id: 41_27 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_57', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_27', 'origin': '40_57~CUW~38_71#MGNP'} Metrics: ['ELUC: -8.797643522235077', 'NSGA-II_crowding_distance: 0.25730858329163864', 'NSGA-II_rank: 2', 'change: 0.11672631274178732', 'is_elite: False']\n", + "Id: 41_91 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_91', 'origin': '1_1~CUW~40_41#MGNP'} Metrics: ['ELUC: -9.12177586145553', 'NSGA-II_crowding_distance: 0.10047405425129602', 'NSGA-II_rank: 1', 'change: 0.11666733041777211', 'is_elite: False']\n", + "Id: 41_57 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_57', 'origin': '1_1~CUW~40_41#MGNP'} Metrics: ['ELUC: -9.273794390260898', 'NSGA-II_crowding_distance: 0.7172263586205547', 'NSGA-II_rank: 4', 'change: 0.17650838148014794', 'is_elite: False']\n", + "Id: 41_88 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_56', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_88', 'origin': '40_56~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.326088297115685', 'NSGA-II_crowding_distance: 0.7257596280667075', 'NSGA-II_rank: 4', 'change: 0.27115441646504507', 'is_elite: False']\n", + "Id: 41_39 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_58', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_39', 'origin': '40_58~CUW~38_71#MGNP'} Metrics: ['ELUC: -9.351658183807322', 'NSGA-II_crowding_distance: 0.11590031897422659', 'NSGA-II_rank: 3', 'change: 0.13059083057796378', 'is_elite: False']\n", + "Id: 41_44 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_57', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_44', 'origin': '40_57~CUW~40_41#MGNP'} Metrics: ['ELUC: -9.558152214369956', 'NSGA-II_crowding_distance: 0.5081957034617471', 'NSGA-II_rank: 3', 'change: 0.13295332551364633', 'is_elite: False']\n", + "Id: 40_14 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_24', '38_44'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_14', 'origin': '39_24~CUW~38_44#MGNP'} Metrics: ['ELUC: -9.665961041238948', 'NSGA-II_crowding_distance: 0.08024842179155094', 'NSGA-II_rank: 1', 'change: 0.11757410379699845', 'is_elite: False']\n", + "Id: 41_90 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_90', 'origin': '1_1~CUW~40_56#MGNP'} Metrics: ['ELUC: -10.146642323046416', 'NSGA-II_crowding_distance: 0.588592198607152', 'NSGA-II_rank: 3', 'change: 0.23324464632196368', 'is_elite: False']\n", + "Id: 41_54 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_41', '40_83'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_54', 'origin': '40_41~CUW~40_83#MGNP'} Metrics: ['ELUC: -10.211731999971041', 'NSGA-II_crowding_distance: 0.12222041960949939', 'NSGA-II_rank: 1', 'change: 0.12211477953392195', 'is_elite: False']\n", + "Id: 41_29 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '38_42'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_29', 'origin': '38_71~CUW~38_42#MGNP'} Metrics: ['ELUC: -10.609242692185754', 'NSGA-II_crowding_distance: 0.8207361045596102', 'NSGA-II_rank: 2', 'change: 0.12935991051681742', 'is_elite: False']\n", + "Id: 41_52 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_42', '2_49'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_52', 'origin': '38_42~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.761885451744078', 'NSGA-II_crowding_distance: 0.42246624494565366', 'NSGA-II_rank: 5', 'change: 0.27978988569406477', 'is_elite: False']\n", + "Id: 41_59 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_57', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_59', 'origin': '40_57~CUW~40_56#MGNP'} Metrics: ['ELUC: -10.860773745193265', 'NSGA-II_crowding_distance: 0.41061007518783776', 'NSGA-II_rank: 3', 'change: 0.24546775079340075', 'is_elite: False']\n", + "Id: 41_78 Identity: {'ancestor_count': 39, 'ancestor_ids': ['38_42', '40_50'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_78', 'origin': '38_42~CUW~40_50#MGNP'} Metrics: ['ELUC: -11.187189858063995', 'NSGA-II_crowding_distance: 0.09113630729338482', 'NSGA-II_rank: 1', 'change: 0.128226231434445', 'is_elite: False']\n", + "Id: 41_28 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_41', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_28', 'origin': '40_41~CUW~40_41#MGNP'} Metrics: ['ELUC: -11.197556722023569', 'NSGA-II_crowding_distance: 0.03846411640728462', 'NSGA-II_rank: 1', 'change: 0.13257807326779195', 'is_elite: False']\n", + "Id: 38_42 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_42', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -11.338910654843595', 'NSGA-II_crowding_distance: 0.03550441264803529', 'NSGA-II_rank: 1', 'change: 0.1371283178965993', 'is_elite: False']\n", + "Id: 41_21 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_21', 'origin': '40_99~CUW~40_41#MGNP'} Metrics: ['ELUC: -11.530246492953678', 'NSGA-II_crowding_distance: 0.08037402252995075', 'NSGA-II_rank: 1', 'change: 0.13752595082688907', 'is_elite: False']\n", + "Id: 41_89 Identity: {'ancestor_count': 38, 'ancestor_ids': ['2_49', '40_90'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_89', 'origin': '2_49~CUW~40_90#MGNP'} Metrics: ['ELUC: -11.745096876105285', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2889097905368739', 'is_elite: False']\n", + "Id: 41_14 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_14', 'origin': '40_99~CUW~40_41#MGNP'} Metrics: ['ELUC: -12.176625821066095', 'NSGA-II_crowding_distance: 0.18428509212853866', 'NSGA-II_rank: 1', 'change: 0.14689385050636414', 'is_elite: False']\n", + "Id: 38_71 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_71', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -12.882564382626228', 'NSGA-II_crowding_distance: 0.31020351849922295', 'NSGA-II_rank: 1', 'change: 0.16956326408055497', 'is_elite: True']\n", + "Id: 41_86 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_41', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_86', 'origin': '40_41~CUW~40_56#MGNP'} Metrics: ['ELUC: -13.461576115256097', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2715114276790792', 'is_elite: False']\n", + "Id: 41_26 Identity: {'ancestor_count': 39, 'ancestor_ids': ['2_49', '40_41'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_26', 'origin': '2_49~CUW~40_41#MGNP'} Metrics: ['ELUC: -13.642109919873459', 'NSGA-II_crowding_distance: 0.34501883915896525', 'NSGA-II_rank: 3', 'change: 0.268524385938243', 'is_elite: False']\n", + "Id: 41_73 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_56', '2_49'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_73', 'origin': '40_56~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.710764747751222', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2765670128377678', 'is_elite: False']\n", + "Id: 41_80 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_80', 'origin': '40_99~CUW~38_71#MGNP'} Metrics: ['ELUC: -13.850477158014694', 'NSGA-II_crowding_distance: 0.35805936791056714', 'NSGA-II_rank: 1', 'change: 0.21104589433138995', 'is_elite: True']\n", + "Id: 41_25 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '40_50'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_25', 'origin': '40_99~CUW~40_50#MGNP'} Metrics: ['ELUC: -14.62633456720299', 'NSGA-II_crowding_distance: 0.8704246859540727', 'NSGA-II_rank: 2', 'change: 0.24543197661318603', 'is_elite: False']\n", + "Id: 41_82 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_56', '40_15'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_82', 'origin': '40_56~CUW~40_15#MGNP'} Metrics: ['ELUC: -14.782619185953868', 'NSGA-II_crowding_distance: 0.38675337340330074', 'NSGA-II_rank: 2', 'change: 0.2970634839886654', 'is_elite: False']\n", + "Id: 41_85 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_85', 'origin': '40_99~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.024119091557598', 'NSGA-II_crowding_distance: 0.20112057203610004', 'NSGA-II_rank: 1', 'change: 0.24005735651862065', 'is_elite: True']\n", + "Id: 41_43 Identity: {'ancestor_count': 39, 'ancestor_ids': ['36_72', '40_99'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_43', 'origin': '36_72~CUW~40_99#MGNP'} Metrics: ['ELUC: -15.495363801609244', 'NSGA-II_crowding_distance: 0.11169711910347853', 'NSGA-II_rank: 1', 'change: 0.24314155768590592', 'is_elite: False']\n", + "Id: 41_46 Identity: {'ancestor_count': 39, 'ancestor_ids': ['38_71', '40_83'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_46', 'origin': '38_71~CUW~40_83#MGNP'} Metrics: ['ELUC: -16.055031235143797', 'NSGA-II_crowding_distance: 0.2634113854734883', 'NSGA-II_rank: 1', 'change: 0.2558903908481156', 'is_elite: True']\n", + "Id: 41_24 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_24', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.837438063577142', 'NSGA-II_crowding_distance: 0.22242151084708453', 'NSGA-II_rank: 1', 'change: 0.29896223101353264', 'is_elite: True']\n", + "Id: 41_53 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_53', 'origin': '2_49~CUW~38_71#MGNP'} Metrics: ['ELUC: -17.315840322312475', 'NSGA-II_crowding_distance: 0.04246970723794172', 'NSGA-II_rank: 1', 'change: 0.3008596941319452', 'is_elite: False']\n", + "Id: 41_71 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_71', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.37654267594963', 'NSGA-II_crowding_distance: 0.016937894382208767', 'NSGA-II_rank: 1', 'change: 0.3024854737826064', 'is_elite: False']\n", + "Id: 41_40 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_57', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_40', 'origin': '40_57~CUW~40_56#MGNP'} Metrics: ['ELUC: -17.50099450965336', 'NSGA-II_crowding_distance: 0.014346018728133177', 'NSGA-II_rank: 1', 'change: 0.3027714607262556', 'is_elite: False']\n", + "Id: 41_96 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_56', '40_79'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_96', 'origin': '40_56~CUW~40_79#MGNP'} Metrics: ['ELUC: -17.567375779936818', 'NSGA-II_crowding_distance: 0.18497056219381489', 'NSGA-II_rank: 2', 'change: 0.3030607474583597', 'is_elite: False']\n", + "Id: 41_20 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_20', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.57683531238752', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30306268429219063', 'is_elite: False']\n", + "Id: 41_48 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_58', '2_49'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_48', 'origin': '40_58~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597259544680774', 'NSGA-II_crowding_distance: 0.006316855571710503', 'NSGA-II_rank: 1', 'change: 0.30302037278084787', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 40_56 Identity: {'ancestor_count': 38, 'ancestor_ids': ['39_15', '2_49'], 'birth_generation': 40, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '40_56', 'origin': '39_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 41_16 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_42'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_16', 'origin': '2_49~CUW~38_42#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 41_55 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_56', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_55', 'origin': '40_56~CUW~40_56#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 41_66 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_66', 'origin': '2_49~CUW~38_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 41_81 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_41', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_81', 'origin': '40_41~CUW~40_56#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 41.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 42...:\n", + "PopulationResponse:\n", + " Generation: 42\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/42/20240220-004311\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 42 and asking ESP for generation 43...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 42 data persisted.\n", + "Evaluated candidates:\n", + "Id: 42_89 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_46', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_89', 'origin': '41_46~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 42_100 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_100', 'origin': '38_71~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 42_58 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_81', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_58', 'origin': '41_81~CUW~2_49#MGNP'} Metrics: ['ELUC: 22.917604397651246', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3031706256143195', 'is_elite: False']\n", + "Id: 42_66 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_81', '40_58'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_66', 'origin': '41_81~CUW~40_58#MGNP'} Metrics: ['ELUC: 5.856889586116485', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23855946295317593', 'is_elite: False']\n", + "Id: 42_97 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_97', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: 5.467401060454142', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2673996026606493', 'is_elite: False']\n", + "Id: 42_32 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_24', '41_14'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_32', 'origin': '41_24~CUW~41_14#MGNP'} Metrics: ['ELUC: 2.012233861055364', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26778904298128536', 'is_elite: False']\n", + "Id: 42_62 Identity: {'ancestor_count': 39, 'ancestor_ids': ['41_62', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_62', 'origin': '41_62~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.7678397826606476', 'NSGA-II_crowding_distance: 1.0010464585192964', 'NSGA-II_rank: 7', 'change: 0.2507892987328811', 'is_elite: False']\n", + "Id: 42_30 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_46', '41_93'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_30', 'origin': '41_46~CUW~41_93#MGNP'} Metrics: ['ELUC: 0.7603436964090581', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06730851784025536', 'is_elite: False']\n", + "Id: 42_18 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_54'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_18', 'origin': '36_72~CUW~41_54#MGNP'} Metrics: ['ELUC: 0.7313243824905131', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.057881044471578484', 'is_elite: False']\n", + "Id: 42_98 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_46'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_98', 'origin': '36_72~CUW~41_46#MGNP'} Metrics: ['ELUC: 0.4984876148138967', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08044760070758473', 'is_elite: False']\n", + "Id: 42_47 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_47', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.17277215420725464', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.033263074100654516', 'is_elite: False']\n", + "Id: 42_76 Identity: {'ancestor_count': 3, 'ancestor_ids': ['41_24', '36_72'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_76', 'origin': '41_24~CUW~36_72#MGNP'} Metrics: ['ELUC: 0.06189272264811347', 'NSGA-II_crowding_distance: 1.3483666266350913', 'NSGA-II_rank: 7', 'change: 0.27621702531820214', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 42_21 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_21', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.49256216242798356', 'NSGA-II_crowding_distance: 0.1321747551335227', 'NSGA-II_rank: 2', 'change: 0.036595380995427446', 'is_elite: False']\n", + "Id: 42_67 Identity: {'ancestor_count': 40, 'ancestor_ids': ['1_1', '41_85'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_67', 'origin': '1_1~CUW~41_85#MGNP'} Metrics: ['ELUC: -0.5633707185755676', 'NSGA-II_crowding_distance: 0.20418472139674207', 'NSGA-II_rank: 4', 'change: 0.0716656061166447', 'is_elite: False']\n", + "Id: 42_77 Identity: {'ancestor_count': 40, 'ancestor_ids': ['1_1', '41_46'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_77', 'origin': '1_1~CUW~41_46#MGNP'} Metrics: ['ELUC: -0.7434405798606573', 'NSGA-II_crowding_distance: 0.16943146079133176', 'NSGA-II_rank: 2', 'change: 0.05490189350720587', 'is_elite: False']\n", + "Id: 42_35 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_85', '41_93'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_35', 'origin': '41_85~CUW~41_93#MGNP'} Metrics: ['ELUC: -0.8255161861573062', 'NSGA-II_crowding_distance: 0.5297782830985588', 'NSGA-II_rank: 5', 'change: 0.08445632609095374', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.22735277940981372', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 42_95 Identity: {'ancestor_count': 39, 'ancestor_ids': ['1_1', '40_58'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_95', 'origin': '1_1~CUW~40_58#MGNP'} Metrics: ['ELUC: -1.1907454557099555', 'NSGA-II_crowding_distance: 0.34677151815999346', 'NSGA-II_rank: 3', 'change: 0.07138622127456108', 'is_elite: False']\n", + "Id: 42_63 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_56', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_63', 'origin': '41_56~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4635222837545356', 'NSGA-II_crowding_distance: 0.13352082263889484', 'NSGA-II_rank: 4', 'change: 0.08171200122004366', 'is_elite: False']\n", + "Id: 42_28 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_38', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_28', 'origin': '41_38~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6724696092590832', 'NSGA-II_crowding_distance: 0.20392445257711442', 'NSGA-II_rank: 1', 'change: 0.04435278898680633', 'is_elite: False']\n", + "Id: 42_72 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_56', '41_85'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_72', 'origin': '41_56~CUW~41_85#MGNP'} Metrics: ['ELUC: -1.884625826102764', 'NSGA-II_crowding_distance: 0.1609719755988183', 'NSGA-II_rank: 4', 'change: 0.08301104831739411', 'is_elite: False']\n", + "Id: 42_34 Identity: {'ancestor_count': 40, 'ancestor_ids': ['1_1', '41_63'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_34', 'origin': '1_1~CUW~41_63#MGNP'} Metrics: ['ELUC: -2.091382654226903', 'NSGA-II_crowding_distance: 0.2321771872760376', 'NSGA-II_rank: 2', 'change: 0.057854452973172855', 'is_elite: False']\n", + "Id: 42_99 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_99', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -3.0549619917222386', 'NSGA-II_crowding_distance: 0.2115567533455115', 'NSGA-II_rank: 1', 'change: 0.05555365155380673', 'is_elite: True']\n", + "Id: 42_29 Identity: {'ancestor_count': 40, 'ancestor_ids': ['38_71', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_29', 'origin': '38_71~CUW~41_38#MGNP'} Metrics: ['ELUC: -3.1100736338438204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11553240319082143', 'is_elite: False']\n", + "Id: 42_42 Identity: {'ancestor_count': 40, 'ancestor_ids': ['38_71', '41_63'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_42', 'origin': '38_71~CUW~41_63#MGNP'} Metrics: ['ELUC: -3.374022110602951', 'NSGA-II_crowding_distance: 0.2034330242291805', 'NSGA-II_rank: 4', 'change: 0.09078837384637513', 'is_elite: False']\n", + "Id: 42_64 Identity: {'ancestor_count': 40, 'ancestor_ids': ['38_71', '41_93'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_64', 'origin': '38_71~CUW~41_93#MGNP'} Metrics: ['ELUC: -3.6235041015461147', 'NSGA-II_crowding_distance: 0.5883054603250077', 'NSGA-II_rank: 5', 'change: 0.11516978731177874', 'is_elite: False']\n", + "Id: 42_57 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_57', 'origin': '41_80~CUW~41_38#MGNP'} Metrics: ['ELUC: -3.7977821890454835', 'NSGA-II_crowding_distance: 0.08725135237354098', 'NSGA-II_rank: 4', 'change: 0.10174465708657975', 'is_elite: False']\n", + "Id: 42_71 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_14', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_71', 'origin': '41_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.803164893142249', 'NSGA-II_crowding_distance: 0.19375536841133245', 'NSGA-II_rank: 4', 'change: 0.10449398627709039', 'is_elite: False']\n", + "Id: 42_80 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_38', '36_72'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_80', 'origin': '41_38~CUW~36_72#MGNP'} Metrics: ['ELUC: -3.8235268782485154', 'NSGA-II_crowding_distance: 0.2300418997126399', 'NSGA-II_rank: 3', 'change: 0.07549937974575692', 'is_elite: False']\n", + "Id: 42_41 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_47', '41_93'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_41', 'origin': '41_47~CUW~41_93#MGNP'} Metrics: ['ELUC: -3.9688442984569052', 'NSGA-II_crowding_distance: 0.22284700168686963', 'NSGA-II_rank: 2', 'change: 0.06823878474208575', 'is_elite: False']\n", + "Id: 42_17 Identity: {'ancestor_count': 40, 'ancestor_ids': ['1_1', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_17', 'origin': '1_1~CUW~41_38#MGNP'} Metrics: ['ELUC: -4.110044775806266', 'NSGA-II_crowding_distance: 0.283629871071116', 'NSGA-II_rank: 3', 'change: 0.08453009463506957', 'is_elite: False']\n", + "Id: 42_74 Identity: {'ancestor_count': 40, 'ancestor_ids': ['1_1', '41_19'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_74', 'origin': '1_1~CUW~41_19#MGNP'} Metrics: ['ELUC: -4.357633680439235', 'NSGA-II_crowding_distance: 0.1737944558348673', 'NSGA-II_rank: 1', 'change: 0.06190854774102999', 'is_elite: False']\n", + "Id: 42_92 Identity: {'ancestor_count': 40, 'ancestor_ids': ['1_1', '41_80'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_92', 'origin': '1_1~CUW~41_80#MGNP'} Metrics: ['ELUC: -4.418006859466379', 'NSGA-II_crowding_distance: 1.2453503433192907', 'NSGA-II_rank: 6', 'change: 0.19413063969579153', 'is_elite: False']\n", + "Id: 42_44 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_47', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_44', 'origin': '41_47~CUW~41_38#MGNP'} Metrics: ['ELUC: -4.68160334089528', 'NSGA-II_crowding_distance: 0.10259871009672496', 'NSGA-II_rank: 2', 'change: 0.07837463990468609', 'is_elite: False']\n", + "Id: 42_31 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_19', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_31', 'origin': '41_19~CUW~38_71#MGNP'} Metrics: ['ELUC: -4.698209848333897', 'NSGA-II_crowding_distance: 0.1850818445411747', 'NSGA-II_rank: 2', 'change: 0.08475818919316468', 'is_elite: False']\n", + "Id: 42_52 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_52', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -4.838244199120542', 'NSGA-II_crowding_distance: 0.24989613095805252', 'NSGA-II_rank: 1', 'change: 0.07714719544670234', 'is_elite: True']\n", + "Id: 42_70 Identity: {'ancestor_count': 39, 'ancestor_ids': ['38_71', '40_58'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_70', 'origin': '38_71~CUW~40_58#MGNP'} Metrics: ['ELUC: -5.681677754031771', 'NSGA-II_crowding_distance: 0.8798063640593509', 'NSGA-II_rank: 5', 'change: 0.11841257825713453', 'is_elite: False']\n", + "Id: 42_61 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_81'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_61', 'origin': '36_72~CUW~41_81#MGNP'} Metrics: ['ELUC: -5.787267148048133', 'NSGA-II_crowding_distance: 0.6399521832310101', 'NSGA-II_rank: 6', 'change: 0.2605033068228087', 'is_elite: False']\n", + "Id: 42_75 Identity: {'ancestor_count': 40, 'ancestor_ids': ['38_71', '41_63'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_75', 'origin': '38_71~CUW~41_63#MGNP'} Metrics: ['ELUC: -5.823207886247154', 'NSGA-II_crowding_distance: 0.41402629359313364', 'NSGA-II_rank: 4', 'change: 0.11664179718978442', 'is_elite: False']\n", + "Id: 42_88 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_81', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_88', 'origin': '41_81~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.032361965678052', 'NSGA-II_crowding_distance: 0.7546496566807092', 'NSGA-II_rank: 6', 'change: 0.2631022129969237', 'is_elite: False']\n", + "Id: 42_40 Identity: {'ancestor_count': 40, 'ancestor_ids': ['38_71', '41_56'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_40', 'origin': '38_71~CUW~41_56#MGNP'} Metrics: ['ELUC: -6.084316734399821', 'NSGA-II_crowding_distance: 0.2865685217111431', 'NSGA-II_rank: 3', 'change: 0.11075770563080209', 'is_elite: False']\n", + "Id: 42_51 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '41_56'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_51', 'origin': '41_80~CUW~41_56#MGNP'} Metrics: ['ELUC: -6.202784477468875', 'NSGA-II_crowding_distance: 0.2479852830038798', 'NSGA-II_rank: 3', 'change: 0.12287910791120324', 'is_elite: False']\n", + "Id: 42_85 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_38', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_85', 'origin': '41_38~CUW~41_38#MGNP'} Metrics: ['ELUC: -7.172560336852308', 'NSGA-II_crowding_distance: 0.3553833694003627', 'NSGA-II_rank: 2', 'change: 0.0902307548954276', 'is_elite: False']\n", + "Id: 41_38 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_14', '40_90'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_38', 'origin': '40_14~CUW~40_90#MGNP'} Metrics: ['ELUC: -7.210361861732345', 'NSGA-II_crowding_distance: 0.3705086225724993', 'NSGA-II_rank: 1', 'change: 0.088060307771272', 'is_elite: True']\n", + "Id: 42_11 Identity: {'ancestor_count': 40, 'ancestor_ids': ['40_58', '41_85'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_11', 'origin': '40_58~CUW~41_85#MGNP'} Metrics: ['ELUC: -7.52457088310506', 'NSGA-II_crowding_distance: 0.6940446321662015', 'NSGA-II_rank: 4', 'change: 0.14511616254707252', 'is_elite: False']\n", + "Id: 42_46 Identity: {'ancestor_count': 40, 'ancestor_ids': ['40_58', '41_81'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_46', 'origin': '40_58~CUW~41_81#MGNP'} Metrics: ['ELUC: -7.721154735122683', 'NSGA-II_crowding_distance: 0.9748555238211882', 'NSGA-II_rank: 5', 'change: 0.21818879910866404', 'is_elite: False']\n", + "Id: 42_25 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_85', '41_24'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_25', 'origin': '41_85~CUW~41_24#MGNP'} Metrics: ['ELUC: -8.410883877158183', 'NSGA-II_crowding_distance: 0.9989535414807035', 'NSGA-II_rank: 7', 'change: 0.29157073853469545', 'is_elite: False']\n", + "Id: 42_82 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_14', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_82', 'origin': '41_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.581544995253102', 'NSGA-II_crowding_distance: 0.609514695423274', 'NSGA-II_rank: 3', 'change: 0.1341755465897602', 'is_elite: False']\n", + "Id: 42_87 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_58', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_87', 'origin': '40_58~CUW~38_71#MGNP'} Metrics: ['ELUC: -8.618128159290324', 'NSGA-II_crowding_distance: 0.20642101719808253', 'NSGA-II_rank: 2', 'change: 0.12070139166772603', 'is_elite: False']\n", + "Id: 42_50 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_54', '41_56'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_50', 'origin': '41_54~CUW~41_56#MGNP'} Metrics: ['ELUC: -8.79574301818031', 'NSGA-II_crowding_distance: 0.15751227297295697', 'NSGA-II_rank: 2', 'change: 0.12108846457671636', 'is_elite: False']\n", + "Id: 42_33 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_33', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.803745282475063', 'NSGA-II_crowding_distance: 0.3785481054886157', 'NSGA-II_rank: 5', 'change: 0.25597162109642935', 'is_elite: False']\n", + "Id: 42_79 Identity: {'ancestor_count': 39, 'ancestor_ids': ['2_49', '41_62'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_79', 'origin': '2_49~CUW~41_62#MGNP'} Metrics: ['ELUC: -8.810117340343918', 'NSGA-II_crowding_distance: 0.30350312098334903', 'NSGA-II_rank: 5', 'change: 0.27364107714907887', 'is_elite: False']\n", + "Id: 42_86 Identity: {'ancestor_count': 3, 'ancestor_ids': ['41_24', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_86', 'origin': '41_24~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.911635145237275', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.30042927303404204', 'is_elite: False']\n", + "Id: 42_13 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_85', '41_63'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_13', 'origin': '41_85~CUW~41_63#MGNP'} Metrics: ['ELUC: -8.96684809129528', 'NSGA-II_crowding_distance: 0.20296074119142135', 'NSGA-II_rank: 1', 'change: 0.11763503105214736', 'is_elite: False']\n", + "Id: 42_59 Identity: {'ancestor_count': 37, 'ancestor_ids': ['1_1', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_59', 'origin': '1_1~CUW~38_71#MGNP'} Metrics: ['ELUC: -8.96743678922457', 'NSGA-II_crowding_distance: 0.12145614712270972', 'NSGA-II_rank: 1', 'change: 0.11880116684184748', 'is_elite: False']\n", + "Id: 42_36 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_36', 'origin': '41_80~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.16642852838211', 'NSGA-II_crowding_distance: 0.24597621223346', 'NSGA-II_rank: 2', 'change: 0.15478744600571717', 'is_elite: False']\n", + "Id: 42_24 Identity: {'ancestor_count': 40, 'ancestor_ids': ['1_1', '41_80'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_24', 'origin': '1_1~CUW~41_80#MGNP'} Metrics: ['ELUC: -10.114997837216112', 'NSGA-II_crowding_distance: 0.207626780612649', 'NSGA-II_rank: 1', 'change: 0.13439038361604316', 'is_elite: False']\n", + "Id: 42_14 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_14', 'origin': '41_80~CUW~38_71#MGNP'} Metrics: ['ELUC: -10.263052490833308', 'NSGA-II_crowding_distance: 0.6921547788679828', 'NSGA-II_rank: 4', 'change: 0.210795257706261', 'is_elite: False']\n", + "Id: 42_23 Identity: {'ancestor_count': 40, 'ancestor_ids': ['1_1', '41_81'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_23', 'origin': '1_1~CUW~41_81#MGNP'} Metrics: ['ELUC: -10.287316924198068', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2817188419592503', 'is_elite: False']\n", + "Id: 42_91 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_85', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_91', 'origin': '41_85~CUW~38_71#MGNP'} Metrics: ['ELUC: -10.871070547808884', 'NSGA-II_crowding_distance: 0.365894732531297', 'NSGA-II_rank: 2', 'change: 0.15570480294135175', 'is_elite: False']\n", + "Id: 42_65 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '41_47'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_65', 'origin': '41_80~CUW~41_47#MGNP'} Metrics: ['ELUC: -11.010102557653411', 'NSGA-II_crowding_distance: 0.6598913498598649', 'NSGA-II_rank: 3', 'change: 0.19937546474191709', 'is_elite: False']\n", + "Id: 42_22 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_22', 'origin': '2_49~CUW~38_71#MGNP'} Metrics: ['ELUC: -11.16939362294674', 'NSGA-II_crowding_distance: 0.32427401430337166', 'NSGA-II_rank: 4', 'change: 0.25035690049417286', 'is_elite: False']\n", + "Id: 42_94 Identity: {'ancestor_count': 40, 'ancestor_ids': ['2_49', '41_19'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_94', 'origin': '2_49~CUW~41_19#MGNP'} Metrics: ['ELUC: -11.252761678163829', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27441787444031085', 'is_elite: False']\n", + "Id: 42_68 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_14', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_68', 'origin': '41_14~CUW~38_71#MGNP'} Metrics: ['ELUC: -11.553544585784708', 'NSGA-II_crowding_distance: 0.27528643614617077', 'NSGA-II_rank: 1', 'change: 0.13686532482075198', 'is_elite: True']\n", + "Id: 42_19 Identity: {'ancestor_count': 37, 'ancestor_ids': ['2_49', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_19', 'origin': '2_49~CUW~38_71#MGNP'} Metrics: ['ELUC: -12.258960184078395', 'NSGA-II_crowding_distance: 0.44141087816978225', 'NSGA-II_rank: 4', 'change: 0.2559232247233789', 'is_elite: False']\n", + "Id: 42_38 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_81', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_38', 'origin': '41_81~CUW~38_71#MGNP'} Metrics: ['ELUC: -12.465289675682719', 'NSGA-II_crowding_distance: 0.4104686416940449', 'NSGA-II_rank: 3', 'change: 0.23579565075698097', 'is_elite: False']\n", + "Id: 42_20 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '41_80'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_20', 'origin': '41_80~CUW~41_80#MGNP'} Metrics: ['ELUC: -12.852158973421393', 'NSGA-II_crowding_distance: 0.28980151362341555', 'NSGA-II_rank: 2', 'change: 0.1971396959067971', 'is_elite: False']\n", + "Id: 38_71 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_71', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -12.882564382626228', 'NSGA-II_crowding_distance: 0.23234213079219573', 'NSGA-II_rank: 1', 'change: 0.16956326408055497', 'is_elite: True']\n", + "Id: 42_26 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_85', '41_24'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_26', 'origin': '41_85~CUW~41_24#MGNP'} Metrics: ['ELUC: -13.143182513735454', 'NSGA-II_crowding_distance: 0.2184491230961465', 'NSGA-II_rank: 3', 'change: 0.2666095997916853', 'is_elite: False']\n", + "Id: 42_78 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '41_80'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_78', 'origin': '41_80~CUW~41_80#MGNP'} Metrics: ['ELUC: -13.148342726170991', 'NSGA-II_crowding_distance: 0.39192059557375', 'NSGA-II_rank: 2', 'change: 0.19905095751597218', 'is_elite: False']\n", + "Id: 42_60 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_46', '41_14'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_60', 'origin': '41_46~CUW~41_14#MGNP'} Metrics: ['ELUC: -13.399062507495932', 'NSGA-II_crowding_distance: 0.07574056966945376', 'NSGA-II_rank: 1', 'change: 0.1748720308983199', 'is_elite: False']\n", + "Id: 42_84 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_14', '41_46'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_84', 'origin': '41_14~CUW~41_46#MGNP'} Metrics: ['ELUC: -13.535420929774318', 'NSGA-II_crowding_distance: 0.14690946090258514', 'NSGA-II_rank: 1', 'change: 0.18108338534932458', 'is_elite: False']\n", + "Id: 42_90 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_90', 'origin': '41_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.761649843362243', 'NSGA-II_crowding_distance: 0.17680778312461273', 'NSGA-II_rank: 3', 'change: 0.2692835670265131', 'is_elite: False']\n", + "Id: 41_80 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_80', 'origin': '40_99~CUW~38_71#MGNP'} Metrics: ['ELUC: -13.850477158014694', 'NSGA-II_crowding_distance: 0.24222419784895205', 'NSGA-II_rank: 1', 'change: 0.21104589433138995', 'is_elite: True']\n", + "Id: 42_55 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_38', '41_46'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_55', 'origin': '41_38~CUW~41_46#MGNP'} Metrics: ['ELUC: -14.462309825868203', 'NSGA-II_crowding_distance: 0.16398184288328865', 'NSGA-II_rank: 1', 'change: 0.23762809766521387', 'is_elite: False']\n", + "Id: 42_39 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '41_81'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_39', 'origin': '41_80~CUW~41_81#MGNP'} Metrics: ['ELUC: -14.999826911441977', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.29565252124994873', 'is_elite: False']\n", + "Id: 41_85 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '1_1'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_85', 'origin': '40_99~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.024119091557598', 'NSGA-II_crowding_distance: 0.14610500690438172', 'NSGA-II_rank: 1', 'change: 0.24005735651862065', 'is_elite: False']\n", + "Id: 42_15 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '41_24'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_15', 'origin': '38_71~CUW~41_24#MGNP'} Metrics: ['ELUC: -15.148750806042953', 'NSGA-II_crowding_distance: 0.15542383599206677', 'NSGA-II_rank: 3', 'change: 0.28010194449740355', 'is_elite: False']\n", + "Id: 42_53 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_85', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_53', 'origin': '41_85~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.398102573634342', 'NSGA-II_crowding_distance: 0.11473526877533921', 'NSGA-II_rank: 3', 'change: 0.28294540064551865', 'is_elite: False']\n", + "Id: 42_69 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '41_85'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_69', 'origin': '41_80~CUW~41_85#MGNP'} Metrics: ['ELUC: -15.511363222610742', 'NSGA-II_crowding_distance: 0.48449894832621554', 'NSGA-II_rank: 2', 'change: 0.2621807441654424', 'is_elite: False']\n", + "Id: 42_27 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_46', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_27', 'origin': '41_46~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.973167768730525', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29564766316734387', 'is_elite: False']\n", + "Id: 42_16 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_46', '41_14'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_16', 'origin': '41_46~CUW~41_14#MGNP'} Metrics: ['ELUC: -15.976474054009989', 'NSGA-II_crowding_distance: 0.11169711910347853', 'NSGA-II_rank: 1', 'change: 0.25552674211547854', 'is_elite: False']\n", + "Id: 42_45 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_81', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_45', 'origin': '41_81~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.00882671182094', 'NSGA-II_crowding_distance: 0.26233837701534796', 'NSGA-II_rank: 2', 'change: 0.2859734591727973', 'is_elite: False']\n", + "Id: 41_46 Identity: {'ancestor_count': 39, 'ancestor_ids': ['38_71', '40_83'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_46', 'origin': '38_71~CUW~40_83#MGNP'} Metrics: ['ELUC: -16.055031235143797', 'NSGA-II_crowding_distance: 0.06897546010991024', 'NSGA-II_rank: 1', 'change: 0.2558903908481156', 'is_elite: False']\n", + "Id: 42_49 Identity: {'ancestor_count': 40, 'ancestor_ids': ['38_71', '41_46'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_49', 'origin': '38_71~CUW~41_46#MGNP'} Metrics: ['ELUC: -16.443656404078755', 'NSGA-II_crowding_distance: 0.1888529955228212', 'NSGA-II_rank: 1', 'change: 0.2681792537996423', 'is_elite: False']\n", + "Id: 41_24 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_24', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.837438063577142', 'NSGA-II_crowding_distance: 0.17321283816154012', 'NSGA-II_rank: 1', 'change: 0.29896223101353264', 'is_elite: False']\n", + "Id: 42_37 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_81', '41_24'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_37', 'origin': '41_81~CUW~41_24#MGNP'} Metrics: ['ELUC: -17.481402605747633', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3028151254052526', 'is_elite: False']\n", + "Id: 42_96 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_46', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_96', 'origin': '41_46~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.535836602242828', 'NSGA-II_crowding_distance: 0.05682326494118764', 'NSGA-II_rank: 1', 'change: 0.3013274700126493', 'is_elite: False']\n", + "Id: 42_73 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_24', '41_80'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_73', 'origin': '41_24~CUW~41_80#MGNP'} Metrics: ['ELUC: -17.59738819094114', 'NSGA-II_crowding_distance: 0.009174675120811621', 'NSGA-II_rank: 1', 'change: 0.3030204390763277', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 41_81 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_41', '40_56'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_81', 'origin': '40_41~CUW~40_56#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 42_12 Identity: {'ancestor_count': 3, 'ancestor_ids': ['41_24', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_12', 'origin': '41_24~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 42_43 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_38', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_43', 'origin': '41_38~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 42_48 Identity: {'ancestor_count': 40, 'ancestor_ids': ['2_49', '41_47'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_48', 'origin': '2_49~CUW~41_47#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 42_54 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '2_49'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_54', 'origin': '41_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 42_56 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '41_24'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_56', 'origin': '38_71~CUW~41_24#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 42_81 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_81', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 42_83 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_81', '41_81'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_83', 'origin': '41_81~CUW~41_81#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 42_93 Identity: {'ancestor_count': 40, 'ancestor_ids': ['2_49', '41_81'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_93', 'origin': '2_49~CUW~41_81#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 42.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 43...:\n", + "PopulationResponse:\n", + " Generation: 43\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/43/20240220-005025\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 43 and asking ESP for generation 44...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 43 data persisted.\n", + "Evaluated candidates:\n", + "Id: 43_43 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_43', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 43_63 Identity: {'ancestor_count': 41, 'ancestor_ids': ['1_1', '42_93'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_63', 'origin': '1_1~CUW~42_93#MGNP'} Metrics: ['ELUC: 4.395669157735483', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2608493775398007', 'is_elite: False']\n", + "Id: 43_35 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_35', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.037806686232948', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.29227346823770917', 'is_elite: False']\n", + "Id: 43_65 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '42_93'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_65', 'origin': '42_52~CUW~42_93#MGNP'} Metrics: ['ELUC: 3.447084384760831', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.21891988035045726', 'is_elite: False']\n", + "Id: 43_79 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_79', 'origin': '42_68~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.0672414343011147', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.34576543533569765', 'is_elite: False']\n", + "Id: 43_37 Identity: {'ancestor_count': 41, 'ancestor_ids': ['2_49', '42_99'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_37', 'origin': '2_49~CUW~42_99#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 43_12 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_38', '42_93'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_12', 'origin': '41_38~CUW~42_93#MGNP'} Metrics: ['ELUC: 1.8343099545396986', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2596357636589882', 'is_elite: False']\n", + "Id: 43_44 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_44', 'origin': '1_1~CUW~36_72#MGNP'} Metrics: ['ELUC: 1.6385514504860894', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03830422195366433', 'is_elite: False']\n", + "Id: 43_16 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_16', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.6323212011826433', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.034306956015028284', 'is_elite: False']\n", + "Id: 43_26 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_93', '1_1'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_26', 'origin': '42_93~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.0434984662316413', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24909263193679893', 'is_elite: False']\n", + "Id: 43_56 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '1_1'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_56', 'origin': '38_71~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.9581375710635037', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07211108976411322', 'is_elite: False']\n", + "Id: 43_29 Identity: {'ancestor_count': 41, 'ancestor_ids': ['1_1', '42_55'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_29', 'origin': '1_1~CUW~42_55#MGNP'} Metrics: ['ELUC: -0.0040181515793509814', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08447813540339533', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 43_93 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_93', 'origin': '36_72~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.02511708163504285', 'NSGA-II_crowding_distance: 0.25449704758914626', 'NSGA-II_rank: 2', 'change: 0.042919728020441375', 'is_elite: False']\n", + "Id: 43_99 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_99', 'origin': '36_72~CUW~41_80#MGNP'} Metrics: ['ELUC: -0.16541439034828076', 'NSGA-II_crowding_distance: 0.6199449394613866', 'NSGA-II_rank: 6', 'change: 0.11073106676842899', 'is_elite: False']\n", + "Id: 43_66 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_66', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.4221599944895526', 'NSGA-II_crowding_distance: 0.22119369217359508', 'NSGA-II_rank: 5', 'change: 0.08006717689205581', 'is_elite: False']\n", + "Id: 43_45 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_45', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: -0.6440605731291118', 'NSGA-II_crowding_distance: 1.489427298310882', 'NSGA-II_rank: 7', 'change: 0.23485227354239463', 'is_elite: False']\n", + "Id: 43_90 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_80', '42_28'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_90', 'origin': '41_80~CUW~42_28#MGNP'} Metrics: ['ELUC: -0.703906892565433', 'NSGA-II_crowding_distance: 0.5370827207261301', 'NSGA-II_rank: 5', 'change: 0.09120537046464645', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.19285302503568932', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 43_55 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_99', '1_1'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_55', 'origin': '42_99~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.066083047014015', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07156726948729669', 'is_elite: False']\n", + "Id: 43_22 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_22', 'origin': '1_1~CUW~36_72#MGNP'} Metrics: ['ELUC: -1.0708051676684556', 'NSGA-II_crowding_distance: 0.09496105480092012', 'NSGA-II_rank: 1', 'change: 0.04426926211765643', 'is_elite: False']\n", + "Id: 43_23 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '42_28'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_23', 'origin': '42_52~CUW~42_28#MGNP'} Metrics: ['ELUC: -1.101035001254423', 'NSGA-II_crowding_distance: 0.39767874941373915', 'NSGA-II_rank: 3', 'change: 0.05973435877611924', 'is_elite: False']\n", + "Id: 43_17 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_17', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -1.2854840909819947', 'NSGA-II_crowding_distance: 0.1618521897372504', 'NSGA-II_rank: 2', 'change: 0.057274137605700604', 'is_elite: False']\n", + "Id: 43_80 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_28', '1_1'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_80', 'origin': '42_28~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.3122092850272047', 'NSGA-II_crowding_distance: 0.14416397583948737', 'NSGA-II_rank: 2', 'change: 0.06584790762404369', 'is_elite: False']\n", + "Id: 43_86 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_86', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -1.334252314324351', 'NSGA-II_crowding_distance: 0.15066856547301402', 'NSGA-II_rank: 1', 'change: 0.052242375467878625', 'is_elite: False']\n", + "Id: 43_100 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_38', '41_85'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_100', 'origin': '41_38~CUW~41_85#MGNP'} Metrics: ['ELUC: -1.9452427390080296', 'NSGA-II_crowding_distance: 0.4428614664396687', 'NSGA-II_rank: 4', 'change: 0.0860662179802216', 'is_elite: False']\n", + "Id: 43_54 Identity: {'ancestor_count': 41, 'ancestor_ids': ['1_1', '42_93'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_54', 'origin': '1_1~CUW~42_93#MGNP'} Metrics: ['ELUC: -2.219748228880912', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27443385884667454', 'is_elite: False']\n", + "Id: 43_91 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '42_28'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_91', 'origin': '42_68~CUW~42_28#MGNP'} Metrics: ['ELUC: -2.3543158228564596', 'NSGA-II_crowding_distance: 0.2773390511152648', 'NSGA-II_rank: 3', 'change: 0.08291690664361503', 'is_elite: False']\n", + "Id: 43_72 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_72', 'origin': '42_52~CUW~36_72#MGNP'} Metrics: ['ELUC: -3.0209439753404084', 'NSGA-II_crowding_distance: 0.23448792028742835', 'NSGA-II_rank: 2', 'change: 0.06907492956305991', 'is_elite: False']\n", + "Id: 42_99 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_99', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -3.0549619917222386', 'NSGA-II_crowding_distance: 0.1922091635028643', 'NSGA-II_rank: 1', 'change: 0.05555365155380673', 'is_elite: True']\n", + "Id: 43_18 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '1_1'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_18', 'origin': '42_68~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.4383594667931026', 'NSGA-II_crowding_distance: 0.44587904883610363', 'NSGA-II_rank: 4', 'change: 0.10530917966756531', 'is_elite: False']\n", + "Id: 43_60 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_99'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_60', 'origin': '36_72~CUW~42_99#MGNP'} Metrics: ['ELUC: -3.719696401486158', 'NSGA-II_crowding_distance: 0.1737944558348673', 'NSGA-II_rank: 1', 'change: 0.06911158507908226', 'is_elite: False']\n", + "Id: 43_74 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_99', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_74', 'origin': '42_99~CUW~41_80#MGNP'} Metrics: ['ELUC: -3.836441307892933', 'NSGA-II_crowding_distance: 1.0337205975609258', 'NSGA-II_rank: 6', 'change: 0.13014300673519097', 'is_elite: False']\n", + "Id: 43_85 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_38', '42_93'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_85', 'origin': '41_38~CUW~42_93#MGNP'} Metrics: ['ELUC: -4.003179936787225', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2691745859158538', 'is_elite: False']\n", + "Id: 43_33 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_38', '42_93'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_33', 'origin': '41_38~CUW~42_93#MGNP'} Metrics: ['ELUC: -4.088123749172908', 'NSGA-II_crowding_distance: 1.186763058589762', 'NSGA-II_rank: 7', 'change: 0.2479174162454614', 'is_elite: False']\n", + "Id: 43_89 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_24', '42_55'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_89', 'origin': '41_24~CUW~42_55#MGNP'} Metrics: ['ELUC: -4.117996317205583', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2603519557190215', 'is_elite: False']\n", + "Id: 43_58 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_58', 'origin': '42_68~CUW~41_38#MGNP'} Metrics: ['ELUC: -4.179432210581031', 'NSGA-II_crowding_distance: 0.258060884242239', 'NSGA-II_rank: 3', 'change: 0.08647751393177751', 'is_elite: False']\n", + "Id: 43_21 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_24', '42_13'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_21', 'origin': '42_24~CUW~42_13#MGNP'} Metrics: ['ELUC: -4.3698524160329635', 'NSGA-II_crowding_distance: 0.15404774812023692', 'NSGA-II_rank: 2', 'change: 0.08160473812765812', 'is_elite: False']\n", + "Id: 43_15 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '1_1'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_15', 'origin': '41_80~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.6242069219163175', 'NSGA-II_crowding_distance: 0.9066127955381693', 'NSGA-II_rank: 5', 'change: 0.12338789777196002', 'is_elite: False']\n", + "Id: 43_73 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_74', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_73', 'origin': '42_74~CUW~41_38#MGNP'} Metrics: ['ELUC: -4.807109457752589', 'NSGA-II_crowding_distance: 0.08390707783301868', 'NSGA-II_rank: 2', 'change: 0.08268413766499982', 'is_elite: False']\n", + "Id: 42_52 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_52', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -4.838244199120542', 'NSGA-II_crowding_distance: 0.2180320833563806', 'NSGA-II_rank: 1', 'change: 0.07714719544670234', 'is_elite: True']\n", + "Id: 43_57 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_99', '42_24'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_57', 'origin': '42_99~CUW~42_24#MGNP'} Metrics: ['ELUC: -4.883296854436762', 'NSGA-II_crowding_distance: 0.8077222759083175', 'NSGA-II_rank: 4', 'change: 0.11327418028047695', 'is_elite: False']\n", + "Id: 43_31 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_13', '42_99'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_31', 'origin': '42_13~CUW~42_99#MGNP'} Metrics: ['ELUC: -5.451552436539766', 'NSGA-II_crowding_distance: 0.11727475856587616', 'NSGA-II_rank: 2', 'change: 0.08742481313278874', 'is_elite: False']\n", + "Id: 43_47 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_47', 'origin': '42_52~CUW~41_38#MGNP'} Metrics: ['ELUC: -5.8211031726160805', 'NSGA-II_crowding_distance: 0.23631047359483248', 'NSGA-II_rank: 3', 'change: 0.09884219101780625', 'is_elite: False']\n", + "Id: 43_19 Identity: {'ancestor_count': 41, 'ancestor_ids': ['2_49', '42_84'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_19', 'origin': '2_49~CUW~42_84#MGNP'} Metrics: ['ELUC: -6.128795604449294', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26303808764448117', 'is_elite: False']\n", + "Id: 43_69 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_69', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: -6.135017028533638', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.26016559395623035', 'is_elite: False']\n", + "Id: 43_30 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '42_99'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_30', 'origin': '42_68~CUW~42_99#MGNP'} Metrics: ['ELUC: -6.168668588168207', 'NSGA-II_crowding_distance: 0.1859077416969584', 'NSGA-II_rank: 3', 'change: 0.11869001093162254', 'is_elite: False']\n", + "Id: 43_95 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_95', 'origin': '42_52~CUW~41_38#MGNP'} Metrics: ['ELUC: -6.194417984209875', 'NSGA-II_crowding_distance: 0.19593849800417823', 'NSGA-II_rank: 2', 'change: 0.09264183532820645', 'is_elite: False']\n", + "Id: 43_39 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_38', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_39', 'origin': '41_38~CUW~41_38#MGNP'} Metrics: ['ELUC: -6.650475069981064', 'NSGA-II_crowding_distance: 0.17148961736980706', 'NSGA-II_rank: 1', 'change: 0.08443128259480748', 'is_elite: False']\n", + "Id: 43_92 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_92', 'origin': '38_71~CUW~36_72#MGNP'} Metrics: ['ELUC: -6.689790072272191', 'NSGA-II_crowding_distance: 1.1948139532286535', 'NSGA-II_rank: 6', 'change: 0.1837183141386493', 'is_elite: False']\n", + "Id: 43_51 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_49', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_51', 'origin': '42_49~CUW~41_80#MGNP'} Metrics: ['ELUC: -6.891307224077604', 'NSGA-II_crowding_distance: 0.3902734805343795', 'NSGA-II_rank: 3', 'change: 0.1315423114454181', 'is_elite: False']\n", + "Id: 43_48 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_55', '42_52'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_48', 'origin': '42_55~CUW~42_52#MGNP'} Metrics: ['ELUC: -6.929880696403412', 'NSGA-II_crowding_distance: 0.24547006759462886', 'NSGA-II_rank: 2', 'change: 0.1163501399455493', 'is_elite: False']\n", + "Id: 41_38 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_14', '40_90'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_38', 'origin': '40_14~CUW~40_90#MGNP'} Metrics: ['ELUC: -7.210361861732345', 'NSGA-II_crowding_distance: 0.13114684774367372', 'NSGA-II_rank: 1', 'change: 0.088060307771272', 'is_elite: False']\n", + "Id: 43_32 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_80', '42_52'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_32', 'origin': '41_80~CUW~42_52#MGNP'} Metrics: ['ELUC: -7.585461162881958', 'NSGA-II_crowding_distance: 0.978642515818039', 'NSGA-II_rank: 5', 'change: 0.16820102222207103', 'is_elite: False']\n", + "Id: 43_50 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_74', '42_13'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_50', 'origin': '42_74~CUW~42_13#MGNP'} Metrics: ['ELUC: -7.633211401204654', 'NSGA-II_crowding_distance: 0.152690337274196', 'NSGA-II_rank: 1', 'change: 0.10688524088316416', 'is_elite: False']\n", + "Id: 43_41 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_74', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_41', 'origin': '42_74~CUW~41_80#MGNP'} Metrics: ['ELUC: -8.200644554027619', 'NSGA-II_crowding_distance: 0.8862019798706127', 'NSGA-II_rank: 4', 'change: 0.16148984475074582', 'is_elite: False']\n", + "Id: 43_84 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_99', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_84', 'origin': '42_99~CUW~41_80#MGNP'} Metrics: ['ELUC: -8.462815617584628', 'NSGA-II_crowding_distance: 0.3666706047638259', 'NSGA-II_rank: 2', 'change: 0.12278494073675324', 'is_elite: False']\n", + "Id: 43_28 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_28', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.520411889166537', 'NSGA-II_crowding_distance: 0.8291866609567077', 'NSGA-II_rank: 6', 'change: 0.28177886303911387', 'is_elite: False']\n", + "Id: 43_61 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_61', 'origin': '36_72~CUW~42_68#MGNP'} Metrics: ['ELUC: -8.65516379957708', 'NSGA-II_crowding_distance: 0.18869177348848834', 'NSGA-II_rank: 1', 'change: 0.10910096748723958', 'is_elite: True']\n", + "Id: 43_13 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_13', 'origin': '42_52~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.314227071102383', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3036958639709234', 'is_elite: False']\n", + "Id: 43_82 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_28', '42_93'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_82', 'origin': '42_28~CUW~42_93#MGNP'} Metrics: ['ELUC: -9.426167654012557', 'NSGA-II_crowding_distance: 0.8721935122882357', 'NSGA-II_rank: 5', 'change: 0.2545125382525866', 'is_elite: False']\n", + "Id: 43_25 Identity: {'ancestor_count': 41, 'ancestor_ids': ['38_71', '42_24'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_25', 'origin': '38_71~CUW~42_24#MGNP'} Metrics: ['ELUC: -9.621140078373097', 'NSGA-II_crowding_distance: 0.136556618916448', 'NSGA-II_rank: 1', 'change: 0.12945089871037288', 'is_elite: False']\n", + "Id: 43_52 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_80', '42_52'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_52', 'origin': '41_80~CUW~42_52#MGNP'} Metrics: ['ELUC: -9.644006144181935', 'NSGA-II_crowding_distance: 0.13475512469353204', 'NSGA-II_rank: 1', 'change: 0.1330654600046514', 'is_elite: False']\n", + "Id: 43_76 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_80', '42_52'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_76', 'origin': '41_80~CUW~42_52#MGNP'} Metrics: ['ELUC: -9.858188425655056', 'NSGA-II_crowding_distance: 0.5485369147022318', 'NSGA-II_rank: 4', 'change: 0.17799139836429975', 'is_elite: False']\n", + "Id: 43_71 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_24'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_71', 'origin': '36_72~CUW~42_24#MGNP'} Metrics: ['ELUC: -10.461205729349043', 'NSGA-II_crowding_distance: 0.36710922622735764', 'NSGA-II_rank: 3', 'change: 0.1569092315697369', 'is_elite: False']\n", + "Id: 43_36 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_80', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_36', 'origin': '41_80~CUW~42_68#MGNP'} Metrics: ['ELUC: -10.6676587190206', 'NSGA-II_crowding_distance: 0.4897625870121467', 'NSGA-II_rank: 4', 'change: 0.20908374599212634', 'is_elite: False']\n", + "Id: 43_42 Identity: {'ancestor_count': 40, 'ancestor_ids': ['38_71', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_42', 'origin': '38_71~CUW~41_38#MGNP'} Metrics: ['ELUC: -10.772058023614399', 'NSGA-II_crowding_distance: 0.23537344146501987', 'NSGA-II_rank: 3', 'change: 0.16982819946201633', 'is_elite: False']\n", + "Id: 43_83 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_13', '42_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_83', 'origin': '42_13~CUW~42_49#MGNP'} Metrics: ['ELUC: -10.7812052668481', 'NSGA-II_crowding_distance: 0.431957109316319', 'NSGA-II_rank: 2', 'change: 0.15460074765882423', 'is_elite: False']\n", + "Id: 43_14 Identity: {'ancestor_count': 40, 'ancestor_ids': ['2_49', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_14', 'origin': '2_49~CUW~41_38#MGNP'} Metrics: ['ELUC: -11.277906290845625', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2957974584812749', 'is_elite: False']\n", + "Id: 42_68 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_14', '38_71'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_68', 'origin': '41_14~CUW~38_71#MGNP'} Metrics: ['ELUC: -11.553544585784708', 'NSGA-II_crowding_distance: 0.18231710981087307', 'NSGA-II_rank: 1', 'change: 0.13686532482075198', 'is_elite: False']\n", + "Id: 43_94 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_94', 'origin': '41_80~CUW~41_38#MGNP'} Metrics: ['ELUC: -11.647025505950513', 'NSGA-II_crowding_distance: 0.286078197530364', 'NSGA-II_rank: 3', 'change: 0.20082566706239674', 'is_elite: False']\n", + "Id: 43_67 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_28', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_67', 'origin': '42_28~CUW~42_68#MGNP'} Metrics: ['ELUC: -12.04654728588757', 'NSGA-II_crowding_distance: 0.12793402690442746', 'NSGA-II_rank: 1', 'change: 0.14669295896041473', 'is_elite: False']\n", + "Id: 43_75 Identity: {'ancestor_count': 41, 'ancestor_ids': ['38_71', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_75', 'origin': '38_71~CUW~42_68#MGNP'} Metrics: ['ELUC: -12.44307516743134', 'NSGA-II_crowding_distance: 0.1215300679226364', 'NSGA-II_rank: 1', 'change: 0.15994237926374053', 'is_elite: False']\n", + "Id: 43_40 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_13', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_40', 'origin': '42_13~CUW~41_80#MGNP'} Metrics: ['ELUC: -12.613836840692688', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.213680585508159', 'is_elite: False']\n", + "Id: 38_71 Identity: {'ancestor_count': 36, 'ancestor_ids': ['37_96', '37_77'], 'birth_generation': 38, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '38_71', 'origin': '37_96~CUW~37_77#MGNP'} Metrics: ['ELUC: -12.882564382626228', 'NSGA-II_crowding_distance: 0.2072617752010119', 'NSGA-II_rank: 2', 'change: 0.16956326408055497', 'is_elite: False']\n", + "Id: 43_49 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '38_71'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_49', 'origin': '38_71~CUW~38_71#MGNP'} Metrics: ['ELUC: -13.072218409773674', 'NSGA-II_crowding_distance: 0.0683218361229557', 'NSGA-II_rank: 2', 'change: 0.17455283269339467', 'is_elite: False']\n", + "Id: 43_77 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_84', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_77', 'origin': '42_84~CUW~42_68#MGNP'} Metrics: ['ELUC: -13.105878795889087', 'NSGA-II_crowding_distance: 0.09740542317008125', 'NSGA-II_rank: 1', 'change: 0.16497764067811188', 'is_elite: False']\n", + "Id: 43_62 Identity: {'ancestor_count': 37, 'ancestor_ids': ['38_71', '38_71'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_62', 'origin': '38_71~CUW~38_71#MGNP'} Metrics: ['ELUC: -13.217046205476334', 'NSGA-II_crowding_distance: 0.0733785467079426', 'NSGA-II_rank: 1', 'change: 0.17587145976813712', 'is_elite: False']\n", + "Id: 43_87 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_24', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_87', 'origin': '42_24~CUW~41_80#MGNP'} Metrics: ['ELUC: -13.319901752544', 'NSGA-II_crowding_distance: 0.5971683841058762', 'NSGA-II_rank: 3', 'change: 0.20674750781450454', 'is_elite: False']\n", + "Id: 43_70 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_99', '38_71'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_70', 'origin': '42_99~CUW~38_71#MGNP'} Metrics: ['ELUC: -13.406155929018436', 'NSGA-II_crowding_distance: 0.1938181936479858', 'NSGA-II_rank: 2', 'change: 0.17953049259346182', 'is_elite: False']\n", + "Id: 43_46 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_13', '42_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_46', 'origin': '42_13~CUW~42_49#MGNP'} Metrics: ['ELUC: -13.515135120955899', 'NSGA-II_crowding_distance: 0.44202852994366804', 'NSGA-II_rank: 2', 'change: 0.21808637494710073', 'is_elite: False']\n", + "Id: 43_24 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_84', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_24', 'origin': '42_84~CUW~42_68#MGNP'} Metrics: ['ELUC: -13.588655925695251', 'NSGA-II_crowding_distance: 0.1539121416202722', 'NSGA-II_rank: 1', 'change: 0.17867928705962874', 'is_elite: False']\n", + "Id: 41_80 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_80', 'origin': '40_99~CUW~38_71#MGNP'} Metrics: ['ELUC: -13.850477158014694', 'NSGA-II_crowding_distance: 0.2942610201883993', 'NSGA-II_rank: 1', 'change: 0.21104589433138995', 'is_elite: True']\n", + "Id: 43_96 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_93', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_96', 'origin': '42_93~CUW~41_38#MGNP'} Metrics: ['ELUC: -14.245570646405668', 'NSGA-II_crowding_distance: 0.4026285805960134', 'NSGA-II_rank: 2', 'change: 0.2813133953424583', 'is_elite: False']\n", + "Id: 43_11 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_49', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_11', 'origin': '42_49~CUW~36_72#MGNP'} Metrics: ['ELUC: -14.31001311069737', 'NSGA-II_crowding_distance: 0.2893631686391458', 'NSGA-II_rank: 1', 'change: 0.2542385639638753', 'is_elite: True']\n", + "Id: 43_34 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_38', '42_93'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_34', 'origin': '41_38~CUW~42_93#MGNP'} Metrics: ['ELUC: -15.941361943066735', 'NSGA-II_crowding_distance: 0.14223892690768178', 'NSGA-II_rank: 2', 'change: 0.2864755027317501', 'is_elite: False']\n", + "Id: 43_59 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_93', '42_13'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_59', 'origin': '42_93~CUW~42_13#MGNP'} Metrics: ['ELUC: -15.942612644178682', 'NSGA-II_crowding_distance: 0.5051652008893419', 'NSGA-II_rank: 3', 'change: 0.293104859739153', 'is_elite: False']\n", + "Id: 43_68 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_24', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_68', 'origin': '42_24~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.944738988333052', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29981541835902004', 'is_elite: False']\n", + "Id: 43_27 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_93', '42_52'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_27', 'origin': '42_93~CUW~42_52#MGNP'} Metrics: ['ELUC: -15.998206085687848', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2923660113925367', 'is_elite: False']\n", + "Id: 43_97 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_49', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_97', 'origin': '42_49~CUW~41_80#MGNP'} Metrics: ['ELUC: -16.115514716927073', 'NSGA-II_crowding_distance: 0.24754744602667997', 'NSGA-II_rank: 1', 'change: 0.2589470298271311', 'is_elite: True']\n", + "Id: 43_88 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_24', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_88', 'origin': '42_24~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.46158283340879', 'NSGA-II_crowding_distance: 0.17510908523763316', 'NSGA-II_rank: 1', 'change: 0.29158840386913076', 'is_elite: False']\n", + "Id: 43_38 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '41_24'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_38', 'origin': '42_52~CUW~41_24#MGNP'} Metrics: ['ELUC: -17.032644401790154', 'NSGA-II_crowding_distance: 0.09494033462216135', 'NSGA-II_rank: 1', 'change: 0.295631705064245', 'is_elite: False']\n", + "Id: 43_81 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_93', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_81', 'origin': '42_93~CUW~42_68#MGNP'} Metrics: ['ELUC: -17.493851413625862', 'NSGA-II_crowding_distance: 0.05684360307685053', 'NSGA-II_rank: 1', 'change: 0.302398567997217', 'is_elite: False']\n", + "Id: 43_98 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_38', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_98', 'origin': '41_38~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.596845686639465', 'NSGA-II_crowding_distance: 0.007972854817285541', 'NSGA-II_rank: 1', 'change: 0.30301789975444576', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 42_93 Identity: {'ancestor_count': 40, 'ancestor_ids': ['2_49', '41_81'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_93', 'origin': '2_49~CUW~41_81#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 43_20 Identity: {'ancestor_count': 40, 'ancestor_ids': ['2_49', '41_38'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_20', 'origin': '2_49~CUW~41_38#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 43_53 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_53', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 43_64 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_93', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_64', 'origin': '42_93~CUW~41_80#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 43_78 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_93', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_78', 'origin': '42_93~CUW~41_80#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 43.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 44...:\n", + "PopulationResponse:\n", + " Generation: 44\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/44/20240220-005739\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 44 and asking ESP for generation 45...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 44 data persisted.\n", + "Evaluated candidates:\n", + "Id: 44_93 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_93', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: 20.047588678220816', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.29071863176178064', 'is_elite: False']\n", + "Id: 44_62 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_62', 'origin': '42_52~CUW~2_49#MGNP'} Metrics: ['ELUC: 12.991347691522414', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2913703083629575', 'is_elite: False']\n", + "Id: 44_63 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_63', 'origin': '43_11~CUW~2_49#MGNP'} Metrics: ['ELUC: 5.253092801570362', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2715340255225737', 'is_elite: False']\n", + "Id: 44_23 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_23', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.248226593496402', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25690727580723827', 'is_elite: False']\n", + "Id: 44_54 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_52', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_54', 'origin': '43_52~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.0342202114088113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2665805594841371', 'is_elite: False']\n", + "Id: 44_11 Identity: {'ancestor_count': 42, 'ancestor_ids': ['1_1', '43_61'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_11', 'origin': '1_1~CUW~43_61#MGNP'} Metrics: ['ELUC: 1.7078866136578101', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.09937690616475121', 'is_elite: False']\n", + "Id: 44_99 Identity: {'ancestor_count': 41, 'ancestor_ids': ['1_1', '43_86'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_99', 'origin': '1_1~CUW~43_86#MGNP'} Metrics: ['ELUC: 1.0911388794784114', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.047638020745097154', 'is_elite: False']\n", + "Id: 44_86 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_86', 'origin': '42_68~CUW~36_72#MGNP'} Metrics: ['ELUC: 1.0554987003377951', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07817987983001459', 'is_elite: False']\n", + "Id: 44_71 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '1_1'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_71', 'origin': '43_11~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.4930853790969513', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08809440123454543', 'is_elite: False']\n", + "Id: 44_89 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_88', '42_99'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_89', 'origin': '43_88~CUW~42_99#MGNP'} Metrics: ['ELUC: 0.25255072400042056', 'NSGA-II_crowding_distance: 1.2278612571024556', 'NSGA-II_rank: 11', 'change: 0.2687393517607687', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 44_77 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '43_60'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_77', 'origin': '43_11~CUW~43_60#MGNP'} Metrics: ['ELUC: -0.17055695194932088', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.17838221890642567', 'is_elite: False']\n", + "Id: 44_51 Identity: {'ancestor_count': 42, 'ancestor_ids': ['36_72', '43_97'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_51', 'origin': '36_72~CUW~43_97#MGNP'} Metrics: ['ELUC: -0.3416585590869055', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05485208372665936', 'is_elite: False']\n", + "Id: 44_24 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '43_97'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_24', 'origin': '43_78~CUW~43_97#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.8122185076459422', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 44_32 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_25', '42_99'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_32', 'origin': '43_25~CUW~42_99#MGNP'} Metrics: ['ELUC: -0.5769028632214496', 'NSGA-II_crowding_distance: 1.1241311892147496', 'NSGA-II_rank: 6', 'change: 0.11847872463347729', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.27092500809603476', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 44_58 Identity: {'ancestor_count': 41, 'ancestor_ids': ['43_86', '43_86'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_58', 'origin': '43_86~CUW~43_86#MGNP'} Metrics: ['ELUC: -1.7297026083403118', 'NSGA-II_crowding_distance: 0.282809431552568', 'NSGA-II_rank: 2', 'change: 0.053846094678743815', 'is_elite: False']\n", + "Id: 44_48 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_60', '43_78'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_48', 'origin': '43_60~CUW~43_78#MGNP'} Metrics: ['ELUC: -1.7485596280504159', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3202880123111782', 'is_elite: False']\n", + "Id: 44_15 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '43_39'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_15', 'origin': '42_68~CUW~43_39#MGNP'} Metrics: ['ELUC: -1.9186510103143746', 'NSGA-II_crowding_distance: 0.32420253935367604', 'NSGA-II_rank: 5', 'change: 0.08923524086865038', 'is_elite: False']\n", + "Id: 44_45 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_99', '42_99'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_45', 'origin': '42_99~CUW~42_99#MGNP'} Metrics: ['ELUC: -1.9943156903642534', 'NSGA-II_crowding_distance: 0.20392445257711442', 'NSGA-II_rank: 1', 'change: 0.051891943813363046', 'is_elite: False']\n", + "Id: 44_81 Identity: {'ancestor_count': 42, 'ancestor_ids': ['2_49', '43_11'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_81', 'origin': '2_49~CUW~43_11#MGNP'} Metrics: ['ELUC: -2.0093613435391204', 'NSGA-II_crowding_distance: 1.0403846968714692', 'NSGA-II_rank: 7', 'change: 0.2524241796799823', 'is_elite: False']\n", + "Id: 44_94 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_60', '43_88'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_94', 'origin': '43_60~CUW~43_88#MGNP'} Metrics: ['ELUC: -2.0369406733274076', 'NSGA-II_crowding_distance: 1.7089124762408783', 'NSGA-II_rank: 6', 'change: 0.2287018413230652', 'is_elite: False']\n", + "Id: 44_12 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_12', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0394985783929402', 'NSGA-II_crowding_distance: 1.478317091849825', 'NSGA-II_rank: 11', 'change: 0.28728185318818655', 'is_elite: False']\n", + "Id: 44_52 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_52', 'origin': '43_11~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.3156731828719885', 'NSGA-II_crowding_distance: 1.4423114849844005', 'NSGA-II_rank: 5', 'change: 0.1206615735883503', 'is_elite: False']\n", + "Id: 44_78 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_78', 'origin': '42_68~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.32509182748702', 'NSGA-II_crowding_distance: 0.3203770840036488', 'NSGA-II_rank: 4', 'change: 0.08009766905238022', 'is_elite: False']\n", + "Id: 44_87 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_52'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_87', 'origin': '36_72~CUW~42_52#MGNP'} Metrics: ['ELUC: -2.580208592234434', 'NSGA-II_crowding_distance: 0.22863781073010453', 'NSGA-II_rank: 3', 'change: 0.06801864883495196', 'is_elite: False']\n", + "Id: 44_84 Identity: {'ancestor_count': 42, 'ancestor_ids': ['36_72', '43_50'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_84', 'origin': '36_72~CUW~43_50#MGNP'} Metrics: ['ELUC: -2.6100181910920943', 'NSGA-II_crowding_distance: 0.15338170835974008', 'NSGA-II_rank: 3', 'change: 0.07890666206474223', 'is_elite: False']\n", + "Id: 44_64 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_64', 'origin': '42_68~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.6165504282994974', 'NSGA-II_crowding_distance: 0.20740626284756108', 'NSGA-II_rank: 4', 'change: 0.10361531683207396', 'is_elite: False']\n", + "Id: 44_31 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_31', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.688214219728272', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3272481650665728', 'is_elite: False']\n", + "Id: 44_14 Identity: {'ancestor_count': 42, 'ancestor_ids': ['42_99', '43_61'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_14', 'origin': '42_99~CUW~43_61#MGNP'} Metrics: ['ELUC: -2.9163934490994654', 'NSGA-II_crowding_distance: 0.1677439298588708', 'NSGA-II_rank: 3', 'change: 0.10135718762035272', 'is_elite: False']\n", + "Id: 44_30 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_30', 'origin': '41_80~CUW~36_72#MGNP'} Metrics: ['ELUC: -3.0507815082939898', 'NSGA-II_crowding_distance: 0.19417898706600972', 'NSGA-II_rank: 2', 'change: 0.06316903328607525', 'is_elite: False']\n", + "Id: 42_99 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_99', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -3.0549619917222386', 'NSGA-II_crowding_distance: 0.09736511417380139', 'NSGA-II_rank: 1', 'change: 0.05555365155380673', 'is_elite: False']\n", + "Id: 44_92 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_99', '42_99'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_92', 'origin': '42_99~CUW~42_99#MGNP'} Metrics: ['ELUC: -3.081483912652459', 'NSGA-II_crowding_distance: 0.1737944558348673', 'NSGA-II_rank: 1', 'change: 0.06249394427767427', 'is_elite: False']\n", + "Id: 44_53 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_99'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_53', 'origin': '36_72~CUW~42_99#MGNP'} Metrics: ['ELUC: -3.1039692684268987', 'NSGA-II_crowding_distance: 0.1274660487882563', 'NSGA-II_rank: 2', 'change: 0.08461571451477579', 'is_elite: False']\n", + "Id: 44_57 Identity: {'ancestor_count': 42, 'ancestor_ids': ['42_52', '43_61'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_57', 'origin': '42_52~CUW~43_61#MGNP'} Metrics: ['ELUC: -3.1176311484669865', 'NSGA-II_crowding_distance: 0.09416760319652326', 'NSGA-II_rank: 2', 'change: 0.09479475670520877', 'is_elite: False']\n", + "Id: 44_76 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '1_1'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_76', 'origin': '43_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.493577765689014', 'NSGA-II_crowding_distance: 0.25744950905999237', 'NSGA-II_rank: 4', 'change: 0.1119686173765832', 'is_elite: False']\n", + "Id: 44_74 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_74', 'origin': '43_78~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.6504338041922715', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26304550453297926', 'is_elite: False']\n", + "Id: 44_83 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '43_61'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_83', 'origin': '43_11~CUW~43_61#MGNP'} Metrics: ['ELUC: -3.7337112226521674', 'NSGA-II_crowding_distance: 0.30525525848690677', 'NSGA-II_rank: 3', 'change: 0.1043974131713928', 'is_elite: False']\n", + "Id: 44_43 Identity: {'ancestor_count': 41, 'ancestor_ids': ['43_86', '42_52'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_43', 'origin': '43_86~CUW~42_52#MGNP'} Metrics: ['ELUC: -4.102931816294072', 'NSGA-II_crowding_distance: 0.14543711587379649', 'NSGA-II_rank: 2', 'change: 0.09498842003432334', 'is_elite: False']\n", + "Id: 42_52 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_52', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -4.838244199120542', 'NSGA-II_crowding_distance: 0.25408567727523634', 'NSGA-II_rank: 1', 'change: 0.07714719544670234', 'is_elite: True']\n", + "Id: 44_85 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_85', 'origin': '42_52~CUW~42_68#MGNP'} Metrics: ['ELUC: -5.057829789656162', 'NSGA-II_crowding_distance: 0.9125978603291496', 'NSGA-II_rank: 4', 'change: 0.1305482537824181', 'is_elite: False']\n", + "Id: 44_41 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_50', '42_52'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_41', 'origin': '43_50~CUW~42_52#MGNP'} Metrics: ['ELUC: -5.50836035151347', 'NSGA-II_crowding_distance: 0.24518787172770065', 'NSGA-II_rank: 2', 'change: 0.09921486633809862', 'is_elite: False']\n", + "Id: 44_95 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_95', 'origin': '42_68~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.632930932606595', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2740037380586638', 'is_elite: False']\n", + "Id: 44_44 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '42_52'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_44', 'origin': '42_52~CUW~42_52#MGNP'} Metrics: ['ELUC: -5.741565986614954', 'NSGA-II_crowding_distance: 0.3241799546440031', 'NSGA-II_rank: 1', 'change: 0.09316503537103162', 'is_elite: True']\n", + "Id: 44_34 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '43_61'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_34', 'origin': '43_78~CUW~43_61#MGNP'} Metrics: ['ELUC: -6.119820144974055', 'NSGA-II_crowding_distance: 1.7515052803109787', 'NSGA-II_rank: 9', 'change: 0.2627512377007137', 'is_elite: False']\n", + "Id: 44_22 Identity: {'ancestor_count': 42, 'ancestor_ids': ['36_72', '43_52'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_22', 'origin': '36_72~CUW~43_52#MGNP'} Metrics: ['ELUC: -6.666836321007454', 'NSGA-II_crowding_distance: 0.41031666346189444', 'NSGA-II_rank: 3', 'change: 0.12299754758995635', 'is_elite: False']\n", + "Id: 44_56 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_56', 'origin': '42_52~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.794719415510341', 'NSGA-II_crowding_distance: 0.9562402206183286', 'NSGA-II_rank: 9', 'change: 0.2880151974837591', 'is_elite: False']\n", + "Id: 44_18 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_18', 'origin': '43_97~CUW~36_72#MGNP'} Metrics: ['ELUC: -6.908068549275537', 'NSGA-II_crowding_distance: 0.8284888922482705', 'NSGA-II_rank: 3', 'change: 0.16057337405832067', 'is_elite: False']\n", + "Id: 44_91 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_88', '1_1'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_91', 'origin': '43_88~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.052346430506607', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25585453117282986', 'is_elite: False']\n", + "Id: 44_68 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_68', 'origin': '43_78~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.200630055995115', 'NSGA-II_crowding_distance: 0.7802443948575724', 'NSGA-II_rank: 8', 'change: 0.27359103863910017', 'is_elite: False']\n", + "Id: 44_46 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_46', 'origin': '43_11~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.251319721644051', 'NSGA-II_crowding_distance: 1.3637349831307888', 'NSGA-II_rank: 8', 'change: 0.2774213561967925', 'is_elite: False']\n", + "Id: 44_39 Identity: {'ancestor_count': 40, 'ancestor_ids': ['2_49', '41_80'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_39', 'origin': '2_49~CUW~41_80#MGNP'} Metrics: ['ELUC: -7.355623859914998', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.29579980731996325', 'is_elite: False']\n", + "Id: 44_28 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '42_52'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_28', 'origin': '42_68~CUW~42_52#MGNP'} Metrics: ['ELUC: -7.568036379022233', 'NSGA-II_crowding_distance: 0.31603194588493344', 'NSGA-II_rank: 2', 'change: 0.11017480116532476', 'is_elite: False']\n", + "Id: 43_61 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_61', 'origin': '36_72~CUW~42_68#MGNP'} Metrics: ['ELUC: -8.65516379957708', 'NSGA-II_crowding_distance: 0.33805281830283185', 'NSGA-II_rank: 1', 'change: 0.10910096748723958', 'is_elite: True']\n", + "Id: 44_27 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '42_52'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_27', 'origin': '43_61~CUW~42_52#MGNP'} Metrics: ['ELUC: -9.202991732334901', 'NSGA-II_crowding_distance: 0.3422521990619042', 'NSGA-II_rank: 2', 'change: 0.12934655747237092', 'is_elite: False']\n", + "Id: 44_29 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_29', 'origin': '43_78~CUW~36_72#MGNP'} Metrics: ['ELUC: -9.606260437095118', 'NSGA-II_crowding_distance: 0.9890607090970971', 'NSGA-II_rank: 4', 'change: 0.23982394655066738', 'is_elite: False']\n", + "Id: 44_50 Identity: {'ancestor_count': 42, 'ancestor_ids': ['41_80', '43_78'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_50', 'origin': '41_80~CUW~43_78#MGNP'} Metrics: ['ELUC: -9.891974172975912', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2862228904544936', 'is_elite: False']\n", + "Id: 44_26 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_24', '43_39'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_26', 'origin': '43_24~CUW~43_39#MGNP'} Metrics: ['ELUC: -9.901468862276548', 'NSGA-II_crowding_distance: 0.13298055213395837', 'NSGA-II_rank: 1', 'change: 0.12343762888525085', 'is_elite: False']\n", + "Id: 44_17 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_17', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.045836631241311', 'NSGA-II_crowding_distance: 0.9848813881209681', 'NSGA-II_rank: 7', 'change: 0.25337920733459846', 'is_elite: False']\n", + "Id: 44_61 Identity: {'ancestor_count': 42, 'ancestor_ids': ['1_1', '43_88'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_61', 'origin': '1_1~CUW~43_88#MGNP'} Metrics: ['ELUC: -10.08703402065024', 'NSGA-II_crowding_distance: 0.29591385666743125', 'NSGA-II_rank: 7', 'change: 0.2764218032784323', 'is_elite: False']\n", + "Id: 44_25 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '41_80'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_25', 'origin': '43_61~CUW~41_80#MGNP'} Metrics: ['ELUC: -10.10567212791425', 'NSGA-II_crowding_distance: 0.5690962925828528', 'NSGA-II_rank: 2', 'change: 0.16282920375294727', 'is_elite: False']\n", + "Id: 44_69 Identity: {'ancestor_count': 42, 'ancestor_ids': ['42_52', '43_24'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_69', 'origin': '42_52~CUW~43_24#MGNP'} Metrics: ['ELUC: -10.138632748182426', 'NSGA-II_crowding_distance: 0.07430578684653596', 'NSGA-II_rank: 1', 'change: 0.12360447547374774', 'is_elite: False']\n", + "Id: 44_35 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_35', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: -10.459291673278697', 'NSGA-II_crowding_distance: 0.20290010423308968', 'NSGA-II_rank: 7', 'change: 0.2832398408927987', 'is_elite: False']\n", + "Id: 44_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_82', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.538271398633514', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2950094809878158', 'is_elite: False']\n", + "Id: 44_73 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_25', '43_50'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_73', 'origin': '43_25~CUW~43_50#MGNP'} Metrics: ['ELUC: -11.040765829737662', 'NSGA-II_crowding_distance: 0.12910444607974125', 'NSGA-II_rank: 1', 'change: 0.1262745990966918', 'is_elite: False']\n", + "Id: 44_96 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_99', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_96', 'origin': '42_99~CUW~42_68#MGNP'} Metrics: ['ELUC: -11.650327931173862', 'NSGA-II_crowding_distance: 0.13280585628531666', 'NSGA-II_rank: 1', 'change: 0.13647243189918248', 'is_elite: False']\n", + "Id: 44_13 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_88', '43_24'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_13', 'origin': '43_88~CUW~43_24#MGNP'} Metrics: ['ELUC: -12.140015649762564', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.25086348056095015', 'is_elite: False']\n", + "Id: 44_55 Identity: {'ancestor_count': 42, 'ancestor_ids': ['42_68', '43_24'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_55', 'origin': '42_68~CUW~43_24#MGNP'} Metrics: ['ELUC: -12.29454590300388', 'NSGA-II_crowding_distance: 0.1878719230074921', 'NSGA-II_rank: 1', 'change: 0.14462387273240118', 'is_elite: False']\n", + "Id: 44_98 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_80', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_98', 'origin': '41_80~CUW~42_68#MGNP'} Metrics: ['ELUC: -13.0559879976021', 'NSGA-II_crowding_distance: 0.29862487029803453', 'NSGA-II_rank: 1', 'change: 0.16867474237446486', 'is_elite: True']\n", + "Id: 44_33 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_50', '43_11'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_33', 'origin': '43_50~CUW~43_11#MGNP'} Metrics: ['ELUC: -13.162197605419667', 'NSGA-II_crowding_distance: 0.7288089224135046', 'NSGA-II_rank: 3', 'change: 0.2351789987882821', 'is_elite: False']\n", + "Id: 44_88 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '42_99'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_88', 'origin': '43_97~CUW~42_99#MGNP'} Metrics: ['ELUC: -13.276534682932462', 'NSGA-II_crowding_distance: 1.3656341180079004', 'NSGA-II_rank: 5', 'change: 0.24962642847668323', 'is_elite: False']\n", + "Id: 44_37 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '43_11'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_37', 'origin': '43_78~CUW~43_11#MGNP'} Metrics: ['ELUC: -13.310324816801526', 'NSGA-II_crowding_distance: 0.1205988429781274', 'NSGA-II_rank: 5', 'change: 0.26924686574722745', 'is_elite: False']\n", + "Id: 44_16 Identity: {'ancestor_count': 42, 'ancestor_ids': ['36_72', '43_78'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_16', 'origin': '36_72~CUW~43_78#MGNP'} Metrics: ['ELUC: -13.36202273678554', 'NSGA-II_crowding_distance: 0.3101633426384238', 'NSGA-II_rank: 5', 'change: 0.2748161224167069', 'is_elite: False']\n", + "Id: 44_20 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_39', '43_97'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_20', 'origin': '43_39~CUW~43_97#MGNP'} Metrics: ['ELUC: -13.385995883297232', 'NSGA-II_crowding_distance: 0.5020031578516273', 'NSGA-II_rank: 4', 'change: 0.2474082467668329', 'is_elite: False']\n", + "Id: 44_80 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '43_60'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_80', 'origin': '43_11~CUW~43_60#MGNP'} Metrics: ['ELUC: -13.7855307429097', 'NSGA-II_crowding_distance: 0.21999628206035488', 'NSGA-II_rank: 3', 'change: 0.24237465294218466', 'is_elite: False']\n", + "Id: 41_80 Identity: {'ancestor_count': 39, 'ancestor_ids': ['40_99', '38_71'], 'birth_generation': 41, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '41_80', 'origin': '40_99~CUW~38_71#MGNP'} Metrics: ['ELUC: -13.850477158014694', 'NSGA-II_crowding_distance: 0.4766796520932568', 'NSGA-II_rank: 2', 'change: 0.21104589433138995', 'is_elite: False']\n", + "Id: 44_79 Identity: {'ancestor_count': 42, 'ancestor_ids': ['2_49', '43_11'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_79', 'origin': '2_49~CUW~43_11#MGNP'} Metrics: ['ELUC: -14.031205400138298', 'NSGA-II_crowding_distance: 0.4331126978392615', 'NSGA-II_rank: 4', 'change: 0.2966142692266725', 'is_elite: False']\n", + "Id: 44_72 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '43_86'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_72', 'origin': '43_11~CUW~43_86#MGNP'} Metrics: ['ELUC: -14.041864165359359', 'NSGA-II_crowding_distance: 0.19382044541064594', 'NSGA-II_rank: 2', 'change: 0.23066718260552443', 'is_elite: False']\n", + "Id: 44_38 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_38', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -14.25328137071635', 'NSGA-II_crowding_distance: 0.4589394934819968', 'NSGA-II_rank: 3', 'change: 0.2741620140223645', 'is_elite: False']\n", + "Id: 44_100 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_24', '41_80'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_100', 'origin': '43_24~CUW~41_80#MGNP'} Metrics: ['ELUC: -14.272981631961787', 'NSGA-II_crowding_distance: 0.283216433362658', 'NSGA-II_rank: 1', 'change: 0.2001522149761181', 'is_elite: True']\n", + "Id: 43_11 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_49', '36_72'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_11', 'origin': '42_49~CUW~36_72#MGNP'} Metrics: ['ELUC: -14.31001311069737', 'NSGA-II_crowding_distance: 0.2552079106752718', 'NSGA-II_rank: 2', 'change: 0.2542385639638753', 'is_elite: False']\n", + "Id: 44_47 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_47', 'origin': '43_97~CUW~42_68#MGNP'} Metrics: ['ELUC: -14.820926638353868', 'NSGA-II_crowding_distance: 0.30184281457358325', 'NSGA-II_rank: 1', 'change: 0.22322866180314146', 'is_elite: True']\n", + "Id: 44_90 Identity: {'ancestor_count': 42, 'ancestor_ids': ['42_52', '43_78'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_90', 'origin': '42_52~CUW~43_78#MGNP'} Metrics: ['ELUC: -15.540807847409296', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.3066275865818353', 'is_elite: False']\n", + "Id: 44_59 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '43_11'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_59', 'origin': '43_97~CUW~43_11#MGNP'} Metrics: ['ELUC: -15.584490360129434', 'NSGA-II_crowding_distance: 0.2824038099396139', 'NSGA-II_rank: 2', 'change: 0.2747132810301648', 'is_elite: False']\n", + "Id: 44_42 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '1_1'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_42', 'origin': '43_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.0855875492912', 'NSGA-II_crowding_distance: 0.2168345276848025', 'NSGA-II_rank: 2', 'change: 0.3020403930866895', 'is_elite: False']\n", + "Id: 43_97 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_49', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_97', 'origin': '42_49~CUW~41_80#MGNP'} Metrics: ['ELUC: -16.115514716927073', 'NSGA-II_crowding_distance: 0.2123185604747546', 'NSGA-II_rank: 1', 'change: 0.2589470298271311', 'is_elite: False']\n", + "Id: 44_19 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_19', 'origin': '43_11~CUW~42_68#MGNP'} Metrics: ['ELUC: -16.2077640336953', 'NSGA-II_crowding_distance: 0.024367151592422802', 'NSGA-II_rank: 1', 'change: 0.26304473061889055', 'is_elite: False']\n", + "Id: 44_49 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_24', '41_80'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_49', 'origin': '43_24~CUW~41_80#MGNP'} Metrics: ['ELUC: -16.22125033323409', 'NSGA-II_crowding_distance: 0.1511566003755687', 'NSGA-II_rank: 1', 'change: 0.26442327883200684', 'is_elite: False']\n", + "Id: 44_97 Identity: {'ancestor_count': 42, 'ancestor_ids': ['1_1', '43_78'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_97', 'origin': '1_1~CUW~43_78#MGNP'} Metrics: ['ELUC: -16.635741324819232', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.30364344870877286', 'is_elite: False']\n", + "Id: 44_67 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '43_88'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_67', 'origin': '43_78~CUW~43_88#MGNP'} Metrics: ['ELUC: -17.096992393896507', 'NSGA-II_crowding_distance: 0.1657864410807961', 'NSGA-II_rank: 1', 'change: 0.293056012247116', 'is_elite: False']\n", + "Id: 44_70 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_88', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_70', 'origin': '43_88~CUW~42_68#MGNP'} Metrics: ['ELUC: -17.188914000158782', 'NSGA-II_crowding_distance: 0.05485755783398566', 'NSGA-II_rank: 1', 'change: 0.29746870756515936', 'is_elite: False']\n", + "Id: 44_75 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '42_99'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_75', 'origin': '43_78~CUW~42_99#MGNP'} Metrics: ['ELUC: -17.460512109323613', 'NSGA-II_crowding_distance: 0.30967509007339394', 'NSGA-II_rank: 3', 'change: 0.3034016641660485', 'is_elite: False']\n", + "Id: 44_60 Identity: {'ancestor_count': 41, 'ancestor_ids': ['2_49', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_60', 'origin': '2_49~CUW~42_68#MGNP'} Metrics: ['ELUC: -17.5138973740525', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3040106994884846', 'is_elite: False']\n", + "Id: 44_65 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_68', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_65', 'origin': '42_68~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.55078469299221', 'NSGA-II_crowding_distance: 0.03785144616769426', 'NSGA-II_rank: 1', 'change: 0.3017232898098471', 'is_elite: False']\n", + "Id: 44_21 Identity: {'ancestor_count': 40, 'ancestor_ids': ['41_80', '2_49'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_21', 'origin': '41_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.56853499255794', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3029240721594869', 'is_elite: False']\n", + "Id: 44_40 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_78', '43_97'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_40', 'origin': '43_78~CUW~43_97#MGNP'} Metrics: ['ELUC: -17.57079761594343', 'NSGA-II_crowding_distance: 0.006997925744267526', 'NSGA-II_rank: 1', 'change: 0.30228205291426624', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 43_78 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_93', '41_80'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_78', 'origin': '42_93~CUW~41_80#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 44_36 Identity: {'ancestor_count': 42, 'ancestor_ids': ['41_80', '43_78'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_36', 'origin': '41_80~CUW~43_78#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 44_66 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '43_78'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_66', 'origin': '43_11~CUW~43_78#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 44.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 45...:\n", + "PopulationResponse:\n", + " Generation: 45\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/45/20240220-010453\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 45 and asking ESP for generation 46...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 45 data persisted.\n", + "Evaluated candidates:\n", + "Id: 45_17 Identity: {'ancestor_count': 42, 'ancestor_ids': ['2_49', '44_96'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_17', 'origin': '2_49~CUW~44_96#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 45_60 Identity: {'ancestor_count': 42, 'ancestor_ids': ['2_49', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_60', 'origin': '2_49~CUW~43_61#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 45_13 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_13', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 18.493178484183133', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.28578471719349996', 'is_elite: False']\n", + "Id: 45_79 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_79', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: 6.754830225012118', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2656192602058106', 'is_elite: False']\n", + "Id: 45_52 Identity: {'ancestor_count': 42, 'ancestor_ids': ['2_49', '44_98'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_52', 'origin': '2_49~CUW~44_98#MGNP'} Metrics: ['ELUC: 2.468131523088939', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3507092039996995', 'is_elite: False']\n", + "Id: 45_86 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '36_72'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_86', 'origin': '43_61~CUW~36_72#MGNP'} Metrics: ['ELUC: 2.0450701961260007', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08879391698429501', 'is_elite: False']\n", + "Id: 45_27 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_27', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.438090111098011', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03812968321330587', 'is_elite: False']\n", + "Id: 45_46 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_46', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.7183057797943688', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.0235011608921897', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 45_64 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_64', 'origin': '42_52~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 45_89 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_89', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 45_91 Identity: {'ancestor_count': 43, 'ancestor_ids': ['42_52', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_91', 'origin': '42_52~CUW~44_100#MGNP'} Metrics: ['ELUC: -0.6966419588367352', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08663091971820534', 'is_elite: False']\n", + "Id: 45_75 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '42_52'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_75', 'origin': '43_97~CUW~42_52#MGNP'} Metrics: ['ELUC: -0.7286039656760661', 'NSGA-II_crowding_distance: 0.38430665987215984', 'NSGA-II_rank: 4', 'change: 0.10938425840489689', 'is_elite: False']\n", + "Id: 45_35 Identity: {'ancestor_count': 42, 'ancestor_ids': ['1_1', '44_92'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_35', 'origin': '1_1~CUW~44_92#MGNP'} Metrics: ['ELUC: -0.860536158253954', 'NSGA-II_crowding_distance: 0.3592404796479266', 'NSGA-II_rank: 2', 'change: 0.0454045477331367', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.2794330085503943', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 45_70 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_45', '44_45'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_70', 'origin': '44_45~CUW~44_45#MGNP'} Metrics: ['ELUC: -2.0866943078312805', 'NSGA-II_crowding_distance: 0.18083813789267', 'NSGA-II_rank: 1', 'change: 0.05286284793628307', 'is_elite: False']\n", + "Id: 45_29 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_29', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.3720445612261374', 'NSGA-II_crowding_distance: 1.0892180629514998', 'NSGA-II_rank: 6', 'change: 0.25089425487062916', 'is_elite: False']\n", + "Id: 45_96 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_73', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_96', 'origin': '44_73~CUW~44_44#MGNP'} Metrics: ['ELUC: -2.6644945588236006', 'NSGA-II_crowding_distance: 0.12589566977153477', 'NSGA-II_rank: 1', 'change: 0.055291562410766305', 'is_elite: False']\n", + "Id: 45_95 Identity: {'ancestor_count': 42, 'ancestor_ids': ['36_72', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_95', 'origin': '36_72~CUW~44_44#MGNP'} Metrics: ['ELUC: -2.8452106786761653', 'NSGA-II_crowding_distance: 0.33074201102571765', 'NSGA-II_rank: 2', 'change: 0.06953110955137026', 'is_elite: False']\n", + "Id: 45_99 Identity: {'ancestor_count': 42, 'ancestor_ids': ['42_52', '44_92'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_99', 'origin': '42_52~CUW~44_92#MGNP'} Metrics: ['ELUC: -3.6797042640082296', 'NSGA-II_crowding_distance: 0.14189825948542295', 'NSGA-II_rank: 1', 'change: 0.06339344026138556', 'is_elite: False']\n", + "Id: 45_49 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_44', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_49', 'origin': '44_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.699015055118419', 'NSGA-II_crowding_distance: 0.6479634402516086', 'NSGA-II_rank: 3', 'change: 0.0797861743852016', 'is_elite: False']\n", + "Id: 45_62 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_98', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_62', 'origin': '44_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.78839925310471', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2789498345355337', 'is_elite: False']\n", + "Id: 45_42 Identity: {'ancestor_count': 43, 'ancestor_ids': ['1_1', '44_73'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_42', 'origin': '1_1~CUW~44_73#MGNP'} Metrics: ['ELUC: -3.9755386472871446', 'NSGA-II_crowding_distance: 1.775298378042641', 'NSGA-II_rank: 5', 'change: 0.13739463461718002', 'is_elite: False']\n", + "Id: 45_36 Identity: {'ancestor_count': 43, 'ancestor_ids': ['36_72', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_36', 'origin': '36_72~CUW~44_100#MGNP'} Metrics: ['ELUC: -4.459527880359749', 'NSGA-II_crowding_distance: 0.6674164331300603', 'NSGA-II_rank: 4', 'change: 0.11197870974584256', 'is_elite: False']\n", + "Id: 45_24 Identity: {'ancestor_count': 42, 'ancestor_ids': ['42_52', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_24', 'origin': '42_52~CUW~43_61#MGNP'} Metrics: ['ELUC: -4.511668985075157', 'NSGA-II_crowding_distance: 0.12083391790258885', 'NSGA-II_rank: 1', 'change: 0.06628372149626256', 'is_elite: False']\n", + "Id: 42_52 Identity: {'ancestor_count': 40, 'ancestor_ids': ['36_72', '41_38'], 'birth_generation': 42, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '42_52', 'origin': '36_72~CUW~41_38#MGNP'} Metrics: ['ELUC: -4.838244199120542', 'NSGA-II_crowding_distance: 0.24036091576396695', 'NSGA-II_rank: 2', 'change: 0.07714719544670234', 'is_elite: False']\n", + "Id: 45_69 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_52'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_69', 'origin': '36_72~CUW~42_52#MGNP'} Metrics: ['ELUC: -5.032569689271977', 'NSGA-II_crowding_distance: 0.07349487701143104', 'NSGA-II_rank: 1', 'change: 0.07648904532752798', 'is_elite: False']\n", + "Id: 45_63 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_44', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_63', 'origin': '44_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.07583772724814', 'NSGA-II_crowding_distance: 0.09621320332055458', 'NSGA-II_rank: 1', 'change: 0.07863883750370439', 'is_elite: False']\n", + "Id: 45_76 Identity: {'ancestor_count': 42, 'ancestor_ids': ['42_52', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_76', 'origin': '42_52~CUW~44_44#MGNP'} Metrics: ['ELUC: -5.612769272205339', 'NSGA-II_crowding_distance: 0.16384766103904463', 'NSGA-II_rank: 2', 'change: 0.09447932894777916', 'is_elite: False']\n", + "Id: 45_92 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_100', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_92', 'origin': '44_100~CUW~44_44#MGNP'} Metrics: ['ELUC: -5.691250832578751', 'NSGA-II_crowding_distance: 0.3122222188626673', 'NSGA-II_rank: 3', 'change: 0.11054574051486184', 'is_elite: False']\n", + "Id: 44_44 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '42_52'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_44', 'origin': '42_52~CUW~42_52#MGNP'} Metrics: ['ELUC: -5.741565986614954', 'NSGA-II_crowding_distance: 0.15747039165826088', 'NSGA-II_rank: 1', 'change: 0.09316503537103162', 'is_elite: False']\n", + "Id: 45_22 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_44', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_22', 'origin': '44_44~CUW~44_44#MGNP'} Metrics: ['ELUC: -5.97025466993928', 'NSGA-II_crowding_distance: 0.09538124522869529', 'NSGA-II_rank: 2', 'change: 0.1056697370407708', 'is_elite: False']\n", + "Id: 45_68 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_98', '36_72'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_68', 'origin': '44_98~CUW~36_72#MGNP'} Metrics: ['ELUC: -6.617938023202925', 'NSGA-II_crowding_distance: 0.11802033724751894', 'NSGA-II_rank: 2', 'change: 0.1057997991475828', 'is_elite: False']\n", + "Id: 45_50 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_55', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_50', 'origin': '44_55~CUW~44_44#MGNP'} Metrics: ['ELUC: -6.815514236989108', 'NSGA-II_crowding_distance: 0.21912020144250124', 'NSGA-II_rank: 1', 'change: 0.09610164656542818', 'is_elite: True']\n", + "Id: 45_98 Identity: {'ancestor_count': 43, 'ancestor_ids': ['42_52', '44_73'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_98', 'origin': '42_52~CUW~44_73#MGNP'} Metrics: ['ELUC: -6.935433149224622', 'NSGA-II_crowding_distance: 0.5426862635175277', 'NSGA-II_rank: 4', 'change: 0.15840440667264197', 'is_elite: False']\n", + "Id: 45_100 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_100', 'origin': '43_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.9472854417812515', 'NSGA-II_crowding_distance: 0.2042451942772623', 'NSGA-II_rank: 3', 'change: 0.11728478562469745', 'is_elite: False']\n", + "Id: 45_58 Identity: {'ancestor_count': 41, 'ancestor_ids': ['42_52', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_58', 'origin': '42_52~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.099248862309486', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2679188523364539', 'is_elite: False']\n", + "Id: 45_65 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '44_98'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_65', 'origin': '44_66~CUW~44_98#MGNP'} Metrics: ['ELUC: -7.384116188312226', 'NSGA-II_crowding_distance: 1.017961765854463', 'NSGA-II_rank: 8', 'change: 0.27329567527891285', 'is_elite: False']\n", + "Id: 45_61 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_61', 'origin': '43_97~CUW~43_61#MGNP'} Metrics: ['ELUC: -7.666027010321707', 'NSGA-II_crowding_distance: 0.19881045023214772', 'NSGA-II_rank: 3', 'change: 0.1371671735967581', 'is_elite: False']\n", + "Id: 45_16 Identity: {'ancestor_count': 42, 'ancestor_ids': ['36_72', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_16', 'origin': '36_72~CUW~43_61#MGNP'} Metrics: ['ELUC: -7.904101831297425', 'NSGA-II_crowding_distance: 0.18810214506169218', 'NSGA-II_rank: 2', 'change: 0.10914498497723717', 'is_elite: False']\n", + "Id: 45_14 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_61', '44_67'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_14', 'origin': '43_61~CUW~44_67#MGNP'} Metrics: ['ELUC: -7.941514800449941', 'NSGA-II_crowding_distance: 1.6054712952245034', 'NSGA-II_rank: 8', 'change: 0.27917114694614725', 'is_elite: False']\n", + "Id: 45_41 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_47', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_41', 'origin': '44_47~CUW~43_61#MGNP'} Metrics: ['ELUC: -8.087070671930405', 'NSGA-II_crowding_distance: 0.160204948882422', 'NSGA-II_rank: 2', 'change: 0.13595690595988016', 'is_elite: False']\n", + "Id: 45_43 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_43', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.37898159723986', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.29919224611863793', 'is_elite: False']\n", + "Id: 45_11 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_44', '44_66'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_11', 'origin': '44_44~CUW~44_66#MGNP'} Metrics: ['ELUC: -8.428554040840265', 'NSGA-II_crowding_distance: 0.47393023134008705', 'NSGA-II_rank: 4', 'change: 0.16826130671868475', 'is_elite: False']\n", + "Id: 43_61 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_61', 'origin': '36_72~CUW~42_68#MGNP'} Metrics: ['ELUC: -8.65516379957708', 'NSGA-II_crowding_distance: 0.24650395104758777', 'NSGA-II_rank: 1', 'change: 0.10910096748723958', 'is_elite: True']\n", + "Id: 45_31 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_31', 'origin': '43_61~CUW~44_44#MGNP'} Metrics: ['ELUC: -8.976455769202826', 'NSGA-II_crowding_distance: 0.35234221245187025', 'NSGA-II_rank: 3', 'change: 0.14170832905422556', 'is_elite: False']\n", + "Id: 45_39 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_61', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_39', 'origin': '43_61~CUW~44_100#MGNP'} Metrics: ['ELUC: -9.05737937668456', 'NSGA-II_crowding_distance: 0.07390304706533138', 'NSGA-II_rank: 2', 'change: 0.1363247309865242', 'is_elite: False']\n", + "Id: 45_82 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_44', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_82', 'origin': '44_44~CUW~44_100#MGNP'} Metrics: ['ELUC: -9.359781506924001', 'NSGA-II_crowding_distance: 0.05721255015007094', 'NSGA-II_rank: 2', 'change: 0.13719054385027868', 'is_elite: False']\n", + "Id: 45_38 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '44_47'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_38', 'origin': '44_66~CUW~44_47#MGNP'} Metrics: ['ELUC: -9.436799195796507', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.2663820071192147', 'is_elite: False']\n", + "Id: 45_81 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_92', '44_98'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_81', 'origin': '44_92~CUW~44_98#MGNP'} Metrics: ['ELUC: -9.812116202486452', 'NSGA-II_crowding_distance: 0.12709477666564187', 'NSGA-II_rank: 2', 'change: 0.14079824464150498', 'is_elite: False']\n", + "Id: 45_25 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_55', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_25', 'origin': '44_55~CUW~43_61#MGNP'} Metrics: ['ELUC: -9.866687953876475', 'NSGA-II_crowding_distance: 0.22850653600087012', 'NSGA-II_rank: 1', 'change: 0.11787357381367805', 'is_elite: True']\n", + "Id: 45_19 Identity: {'ancestor_count': 43, 'ancestor_ids': ['1_1', '44_66'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_19', 'origin': '1_1~CUW~44_66#MGNP'} Metrics: ['ELUC: -10.240426087490755', 'NSGA-II_crowding_distance: 1.0638320564498818', 'NSGA-II_rank: 6', 'change: 0.25267590471288415', 'is_elite: False']\n", + "Id: 45_20 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_92', '44_55'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_20', 'origin': '44_92~CUW~44_55#MGNP'} Metrics: ['ELUC: -10.680624214471003', 'NSGA-II_crowding_distance: 0.1219151209966925', 'NSGA-II_rank: 2', 'change: 0.15255789152780855', 'is_elite: False']\n", + "Id: 45_93 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_44', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_93', 'origin': '44_44~CUW~44_100#MGNP'} Metrics: ['ELUC: -10.765548578195814', 'NSGA-II_crowding_distance: 0.15150625891089933', 'NSGA-II_rank: 1', 'change: 0.14146834537254427', 'is_elite: False']\n", + "Id: 45_56 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_67', '44_96'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_56', 'origin': '44_67~CUW~44_96#MGNP'} Metrics: ['ELUC: -10.791536101079354', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.268806819850388', 'is_elite: False']\n", + "Id: 45_28 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_26', '44_47'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_28', 'origin': '44_26~CUW~44_47#MGNP'} Metrics: ['ELUC: -10.795179715947132', 'NSGA-II_crowding_distance: 0.08721885151237858', 'NSGA-II_rank: 1', 'change: 0.1473228737270441', 'is_elite: False']\n", + "Id: 45_26 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_47', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_26', 'origin': '44_47~CUW~44_44#MGNP'} Metrics: ['ELUC: -11.14830517181224', 'NSGA-II_crowding_distance: 0.12237214583209673', 'NSGA-II_rank: 2', 'change: 0.15448354887443977', 'is_elite: False']\n", + "Id: 45_21 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '44_55'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_21', 'origin': '44_66~CUW~44_55#MGNP'} Metrics: ['ELUC: -11.556253178110389', 'NSGA-II_crowding_distance: 0.9107819370485003', 'NSGA-II_rank: 6', 'change: 0.2657147071078209', 'is_elite: False']\n", + "Id: 45_45 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_55', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_45', 'origin': '44_55~CUW~43_61#MGNP'} Metrics: ['ELUC: -11.797308332714726', 'NSGA-II_crowding_distance: 0.12146180161610026', 'NSGA-II_rank: 1', 'change: 0.14998322594766694', 'is_elite: False']\n", + "Id: 45_97 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_61', '44_67'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_97', 'origin': '43_61~CUW~44_67#MGNP'} Metrics: ['ELUC: -12.241186501287984', 'NSGA-II_crowding_distance: 1.3394492758126668', 'NSGA-II_rank: 5', 'change: 0.24550646262366282', 'is_elite: False']\n", + "Id: 45_53 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_61', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_53', 'origin': '43_61~CUW~44_100#MGNP'} Metrics: ['ELUC: -12.250830863541808', 'NSGA-II_crowding_distance: 0.8466466753414298', 'NSGA-II_rank: 4', 'change: 0.17937858222701786', 'is_elite: False']\n", + "Id: 45_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_54', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.332622979905032', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29099130542202983', 'is_elite: False']\n", + "Id: 45_74 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_98', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_74', 'origin': '44_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.412190916395359', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28788836468769774', 'is_elite: False']\n", + "Id: 45_77 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_61', '44_47'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_77', 'origin': '43_61~CUW~44_47#MGNP'} Metrics: ['ELUC: -12.571581517086667', 'NSGA-II_crowding_distance: 0.7472568765333611', 'NSGA-II_rank: 3', 'change: 0.1622145548407914', 'is_elite: False']\n", + "Id: 45_37 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_55', '44_55'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_37', 'origin': '44_55~CUW~44_55#MGNP'} Metrics: ['ELUC: -12.596296567929722', 'NSGA-II_crowding_distance: 0.06862072262977212', 'NSGA-II_rank: 1', 'change: 0.15299886045242372', 'is_elite: False']\n", + "Id: 45_15 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_97', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_15', 'origin': '43_97~CUW~44_100#MGNP'} Metrics: ['ELUC: -12.675629385976709', 'NSGA-II_crowding_distance: 0.22586121944932414', 'NSGA-II_rank: 2', 'change: 0.15631618337274641', 'is_elite: False']\n", + "Id: 45_87 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_100', '44_55'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_87', 'origin': '44_100~CUW~44_55#MGNP'} Metrics: ['ELUC: -12.820194506808818', 'NSGA-II_crowding_distance: 0.04465018768716894', 'NSGA-II_rank: 1', 'change: 0.1530994267295484', 'is_elite: False']\n", + "Id: 45_71 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_100', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_71', 'origin': '44_100~CUW~43_61#MGNP'} Metrics: ['ELUC: -12.949440073248805', 'NSGA-II_crowding_distance: 0.06561081107817089', 'NSGA-II_rank: 1', 'change: 0.16032852728810115', 'is_elite: False']\n", + "Id: 44_98 Identity: {'ancestor_count': 41, 'ancestor_ids': ['41_80', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_98', 'origin': '41_80~CUW~42_68#MGNP'} Metrics: ['ELUC: -13.0559879976021', 'NSGA-II_crowding_distance: 0.06865054871882671', 'NSGA-II_rank: 1', 'change: 0.16867474237446486', 'is_elite: False']\n", + "Id: 45_12 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_44', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_12', 'origin': '44_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.080492006997595', 'NSGA-II_crowding_distance: 0.6186737046061831', 'NSGA-II_rank: 4', 'change: 0.2795360699603501', 'is_elite: False']\n", + "Id: 45_88 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_97', '44_73'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_88', 'origin': '43_97~CUW~44_73#MGNP'} Metrics: ['ELUC: -13.260099829055493', 'NSGA-II_crowding_distance: 0.47178057428024545', 'NSGA-II_rank: 2', 'change: 0.18538695305007127', 'is_elite: False']\n", + "Id: 45_90 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_55', '44_47'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_90', 'origin': '44_55~CUW~44_47#MGNP'} Metrics: ['ELUC: -13.379972766723812', 'NSGA-II_crowding_distance: 0.06009281350971653', 'NSGA-II_rank: 1', 'change: 0.1735060486206613', 'is_elite: False']\n", + "Id: 45_40 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_97', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_40', 'origin': '43_97~CUW~44_100#MGNP'} Metrics: ['ELUC: -13.482443585479071', 'NSGA-II_crowding_distance: 0.07639558180872946', 'NSGA-II_rank: 1', 'change: 0.17936801597355473', 'is_elite: False']\n", + "Id: 45_32 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_32', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.5416924711539', 'NSGA-II_crowding_distance: 0.555711038003725', 'NSGA-II_rank: 3', 'change: 0.27615220722938755', 'is_elite: False']\n", + "Id: 45_72 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_98', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_72', 'origin': '44_98~CUW~44_100#MGNP'} Metrics: ['ELUC: -13.819838173332919', 'NSGA-II_crowding_distance: 0.0715047002073487', 'NSGA-II_rank: 1', 'change: 0.18883613620640047', 'is_elite: False']\n", + "Id: 45_55 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_100', '44_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_55', 'origin': '44_100~CUW~44_49#MGNP'} Metrics: ['ELUC: -13.917419227717943', 'NSGA-II_crowding_distance: 0.06369799750910526', 'NSGA-II_rank: 1', 'change: 0.19332175429403703', 'is_elite: False']\n", + "Id: 44_100 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_24', '41_80'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_100', 'origin': '43_24~CUW~41_80#MGNP'} Metrics: ['ELUC: -14.272981631961787', 'NSGA-II_crowding_distance: 0.07600364324560878', 'NSGA-II_rank: 1', 'change: 0.2001522149761181', 'is_elite: False']\n", + "Id: 45_73 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '36_72'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_73', 'origin': '2_49~CUW~36_72#MGNP'} Metrics: ['ELUC: -14.290310958660774', 'NSGA-II_crowding_distance: 0.22636040126888274', 'NSGA-II_rank: 4', 'change: 0.2814115861681302', 'is_elite: False']\n", + "Id: 45_47 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_100', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_47', 'origin': '44_100~CUW~44_100#MGNP'} Metrics: ['ELUC: -14.420537902896426', 'NSGA-II_crowding_distance: 0.10850422429363189', 'NSGA-II_rank: 1', 'change: 0.2074614686868923', 'is_elite: False']\n", + "Id: 45_23 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_23', 'origin': '44_66~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.525873226004174', 'NSGA-II_crowding_distance: 0.4157482700585112', 'NSGA-II_rank: 2', 'change: 0.25995136257180435', 'is_elite: False']\n", + "Id: 45_57 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_98', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_57', 'origin': '44_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.792385657665807', 'NSGA-II_crowding_distance: 0.18229767615700385', 'NSGA-II_rank: 3', 'change: 0.27855120646664866', 'is_elite: False']\n", + "Id: 45_83 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_83', 'origin': '44_66~CUW~44_100#MGNP'} Metrics: ['ELUC: -14.816613131381855', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.3017840663753831', 'is_elite: False']\n", + "Id: 44_47 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_47', 'origin': '43_97~CUW~42_68#MGNP'} Metrics: ['ELUC: -14.820926638353868', 'NSGA-II_crowding_distance: 0.1995994495392831', 'NSGA-II_rank: 1', 'change: 0.22322866180314146', 'is_elite: True']\n", + "Id: 45_66 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '44_92'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_66', 'origin': '44_66~CUW~44_92#MGNP'} Metrics: ['ELUC: -15.383544898372497', 'NSGA-II_crowding_distance: 0.13209879829512103', 'NSGA-II_rank: 2', 'change: 0.26919027652615685', 'is_elite: False']\n", + "Id: 45_34 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '43_97'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_34', 'origin': '44_66~CUW~43_97#MGNP'} Metrics: ['ELUC: -15.536005554752666', 'NSGA-II_crowding_distance: 0.10524980388283915', 'NSGA-II_rank: 2', 'change: 0.28145946604501143', 'is_elite: False']\n", + "Id: 45_51 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '44_98'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_51', 'origin': '44_66~CUW~44_98#MGNP'} Metrics: ['ELUC: -15.589004960133934', 'NSGA-II_crowding_distance: 0.21692093798743894', 'NSGA-II_rank: 3', 'change: 0.29594700552204517', 'is_elite: False']\n", + "Id: 45_80 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '44_98'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_80', 'origin': '43_97~CUW~44_98#MGNP'} Metrics: ['ELUC: -15.66739117157178', 'NSGA-II_crowding_distance: 0.19267904034079864', 'NSGA-II_rank: 1', 'change: 0.24585801202099075', 'is_elite: False']\n", + "Id: 45_78 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_98', '2_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_78', 'origin': '44_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.950484750907497', 'NSGA-II_crowding_distance: 0.13211590444882554', 'NSGA-II_rank: 2', 'change: 0.28995742056164575', 'is_elite: False']\n", + "Id: 45_48 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_49', '44_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_48', 'origin': '44_49~CUW~44_49#MGNP'} Metrics: ['ELUC: -16.083232108807437', 'NSGA-II_crowding_distance: 0.2571310183253688', 'NSGA-II_rank: 1', 'change: 0.2592980806320238', 'is_elite: True']\n", + "Id: 45_59 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_26', '44_67'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_59', 'origin': '44_26~CUW~44_67#MGNP'} Metrics: ['ELUC: -16.73086155653826', 'NSGA-II_crowding_distance: 0.1317250228590209', 'NSGA-II_rank: 2', 'change: 0.30015312409140055', 'is_elite: False']\n", + "Id: 45_33 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '44_100'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_33', 'origin': '44_66~CUW~44_100#MGNP'} Metrics: ['ELUC: -17.160245510231395', 'NSGA-II_crowding_distance: 0.13222717739515458', 'NSGA-II_rank: 3', 'change: 0.30305678528490604', 'is_elite: False']\n", + "Id: 45_44 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_96', '44_66'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_44', 'origin': '44_96~CUW~44_66#MGNP'} Metrics: ['ELUC: -17.210102012949964', 'NSGA-II_crowding_distance: 0.20573788834260448', 'NSGA-II_rank: 1', 'change: 0.296399899171206', 'is_elite: True']\n", + "Id: 45_85 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_92', '44_67'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_85', 'origin': '44_92~CUW~44_67#MGNP'} Metrics: ['ELUC: -17.292660288416673', 'NSGA-II_crowding_distance: 0.035534980353659804', 'NSGA-II_rank: 1', 'change: 0.3001613126007353', 'is_elite: False']\n", + "Id: 45_84 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '44_47'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_84', 'origin': '44_66~CUW~44_47#MGNP'} Metrics: ['ELUC: -17.535249197021155', 'NSGA-II_crowding_distance: 0.05754996771045689', 'NSGA-II_rank: 2', 'change: 0.30259108996036027', 'is_elite: False']\n", + "Id: 45_94 Identity: {'ancestor_count': 43, 'ancestor_ids': ['2_49', '44_67'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_94', 'origin': '2_49~CUW~44_67#MGNP'} Metrics: ['ELUC: -17.54037870412748', 'NSGA-II_crowding_distance: 0.02691371574517335', 'NSGA-II_rank: 1', 'change: 0.30139784815947607', 'is_elite: False']\n", + "Id: 45_18 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_67', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_18', 'origin': '44_67~CUW~44_44#MGNP'} Metrics: ['ELUC: -17.58841498143978', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.303139822149609', 'is_elite: False']\n", + "Id: 45_30 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_44', '44_66'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_30', 'origin': '44_44~CUW~44_66#MGNP'} Metrics: ['ELUC: -17.596801775589828', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030237828796641', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 44_66 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_11', '43_78'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_66', 'origin': '43_11~CUW~43_78#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 45_67 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_67', 'origin': '44_66~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 45.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 46...:\n", + "PopulationResponse:\n", + " Generation: 46\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/46/20240220-011207\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 46 and asking ESP for generation 47...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 46 data persisted.\n", + "Evaluated candidates:\n", + "Id: 46_75 Identity: {'ancestor_count': 44, 'ancestor_ids': ['2_49', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_75', 'origin': '2_49~CUW~45_50#MGNP'} Metrics: ['ELUC: 22.585884097738074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2963765298627137', 'is_elite: False']\n", + "Id: 46_55 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_47', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_55', 'origin': '44_47~CUW~2_49#MGNP'} Metrics: ['ELUC: 22.526693172222256', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28856652132151067', 'is_elite: False']\n", + "Id: 46_25 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_25', 'origin': '45_44~CUW~2_49#MGNP'} Metrics: ['ELUC: 20.924721691759693', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2936344270620872', 'is_elite: False']\n", + "Id: 46_94 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_94', 'origin': '45_25~CUW~2_49#MGNP'} Metrics: ['ELUC: 12.874031194227719', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.255766500052293', 'is_elite: False']\n", + "Id: 46_23 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_23', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: 8.563586245462275', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2794651276803315', 'is_elite: False']\n", + "Id: 46_89 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_89', 'origin': '45_44~CUW~36_72#MGNP'} Metrics: ['ELUC: 8.240194919368612', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.14354129584767314', 'is_elite: False']\n", + "Id: 46_15 Identity: {'ancestor_count': 43, 'ancestor_ids': ['2_49', '45_80'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_15', 'origin': '2_49~CUW~45_80#MGNP'} Metrics: ['ELUC: 6.859724484451395', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.25584579064136664', 'is_elite: False']\n", + "Id: 46_42 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_42', 'origin': '45_25~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.529023141631986', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.35172872014595363', 'is_elite: False']\n", + "Id: 46_62 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_93', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_62', 'origin': '45_93~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.357061637079496', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26351556718276753', 'is_elite: False']\n", + "Id: 46_21 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_70', '45_25'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_21', 'origin': '45_70~CUW~45_25#MGNP'} Metrics: ['ELUC: 1.1496460304239113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.09872116941567084', 'is_elite: False']\n", + "Id: 46_100 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_100', 'origin': '43_61~CUW~36_72#MGNP'} Metrics: ['ELUC: 1.0390616586623576', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08676073537057614', 'is_elite: False']\n", + "Id: 46_87 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_87', 'origin': '1_1~CUW~36_72#MGNP'} Metrics: ['ELUC: 0.7706950256788053', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.04593924989087096', 'is_elite: False']\n", + "Id: 46_26 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_26', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.6116205541520575', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03593853708558111', 'is_elite: False']\n", + "Id: 46_37 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_37', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.43234583095100365', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.035306368471269084', 'is_elite: False']\n", + "Id: 46_35 Identity: {'ancestor_count': 44, 'ancestor_ids': ['1_1', '45_25'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_35', 'origin': '1_1~CUW~45_25#MGNP'} Metrics: ['ELUC: 0.37763857467427153', 'NSGA-II_crowding_distance: 0.3914852507328268', 'NSGA-II_rank: 5', 'change: 0.09661634344180865', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 46_57 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_57', 'origin': '45_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 46_81 Identity: {'ancestor_count': 43, 'ancestor_ids': ['45_99', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_81', 'origin': '45_99~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 46_31 Identity: {'ancestor_count': 44, 'ancestor_ids': ['2_49', '45_48'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_31', 'origin': '2_49~CUW~45_48#MGNP'} Metrics: ['ELUC: -0.5624694969981944', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.23872131092611024', 'is_elite: False']\n", + "Id: 46_64 Identity: {'ancestor_count': 43, 'ancestor_ids': ['45_70', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_64', 'origin': '45_70~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.6429853632932027', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2595798063678481', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.26507042160485506', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 46_13 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '45_70'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_13', 'origin': '45_50~CUW~45_70#MGNP'} Metrics: ['ELUC: -1.1595337072550806', 'NSGA-II_crowding_distance: 0.4068801138936103', 'NSGA-II_rank: 3', 'change: 0.0764431386882548', 'is_elite: False']\n", + "Id: 46_40 Identity: {'ancestor_count': 43, 'ancestor_ids': ['36_72', '44_47'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_40', 'origin': '36_72~CUW~44_47#MGNP'} Metrics: ['ELUC: -1.8444233129086565', 'NSGA-II_crowding_distance: 0.8902223560950752', 'NSGA-II_rank: 5', 'change: 0.12136422606044307', 'is_elite: False']\n", + "Id: 46_12 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_12', 'origin': '36_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0347012122541526', 'NSGA-II_crowding_distance: 0.1500251903247174', 'NSGA-II_rank: 1', 'change: 0.04945971092553649', 'is_elite: False']\n", + "Id: 46_73 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '45_70'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_73', 'origin': '45_50~CUW~45_70#MGNP'} Metrics: ['ELUC: -2.039990166828856', 'NSGA-II_crowding_distance: 0.08651960126906444', 'NSGA-II_rank: 1', 'change: 0.05669569752667199', 'is_elite: False']\n", + "Id: 46_68 Identity: {'ancestor_count': 43, 'ancestor_ids': ['45_99', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_68', 'origin': '45_99~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.363775369967079', 'NSGA-II_crowding_distance: 0.3879920069681599', 'NSGA-II_rank: 2', 'change: 0.05921208183711725', 'is_elite: False']\n", + "Id: 46_59 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_59', 'origin': '45_25~CUW~45_67#MGNP'} Metrics: ['ELUC: -3.031586177144078', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.20175898366048145', 'is_elite: False']\n", + "Id: 46_88 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_96', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_88', 'origin': '45_96~CUW~36_72#MGNP'} Metrics: ['ELUC: -3.126154313358933', 'NSGA-II_crowding_distance: 0.10021481797851481', 'NSGA-II_rank: 1', 'change: 0.05675293632415268', 'is_elite: False']\n", + "Id: 46_79 Identity: {'ancestor_count': 43, 'ancestor_ids': ['45_24', '43_61'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_79', 'origin': '45_24~CUW~43_61#MGNP'} Metrics: ['ELUC: -3.2457125011586716', 'NSGA-II_crowding_distance: 0.12139566644384603', 'NSGA-II_rank: 1', 'change: 0.06613608628296239', 'is_elite: False']\n", + "Id: 46_63 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '45_24'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_63', 'origin': '45_50~CUW~45_24#MGNP'} Metrics: ['ELUC: -3.314912842902637', 'NSGA-II_crowding_distance: 0.5602369908541129', 'NSGA-II_rank: 4', 'change: 0.09008962749832822', 'is_elite: False']\n", + "Id: 46_28 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_28', 'origin': '45_50~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.3499173571546645', 'NSGA-II_crowding_distance: 0.24512413731903743', 'NSGA-II_rank: 3', 'change: 0.08449670128650036', 'is_elite: False']\n", + "Id: 46_84 Identity: {'ancestor_count': 42, 'ancestor_ids': ['44_44', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_84', 'origin': '44_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.588659476162527', 'NSGA-II_crowding_distance: 0.15736300351539245', 'NSGA-II_rank: 2', 'change: 0.07934608444151728', 'is_elite: False']\n", + "Id: 46_52 Identity: {'ancestor_count': 44, 'ancestor_ids': ['36_72', '45_48'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_52', 'origin': '36_72~CUW~45_48#MGNP'} Metrics: ['ELUC: -3.6048643760058106', 'NSGA-II_crowding_distance: 0.49148682050703435', 'NSGA-II_rank: 4', 'change: 0.11446808856268037', 'is_elite: False']\n", + "Id: 46_36 Identity: {'ancestor_count': 44, 'ancestor_ids': ['44_47', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_36', 'origin': '44_47~CUW~45_50#MGNP'} Metrics: ['ELUC: -3.6551172813025317', 'NSGA-II_crowding_distance: 0.12013156358321854', 'NSGA-II_rank: 3', 'change: 0.10402661894699554', 'is_elite: False']\n", + "Id: 46_17 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_96', '45_25'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_17', 'origin': '45_96~CUW~45_25#MGNP'} Metrics: ['ELUC: -3.7532297034686675', 'NSGA-II_crowding_distance: 0.1320880700439577', 'NSGA-II_rank: 2', 'change: 0.08067792476417923', 'is_elite: False']\n", + "Id: 46_58 Identity: {'ancestor_count': 43, 'ancestor_ids': ['45_99', '43_61'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_58', 'origin': '45_99~CUW~43_61#MGNP'} Metrics: ['ELUC: -3.9542865997881522', 'NSGA-II_crowding_distance: 0.23754746012606648', 'NSGA-II_rank: 3', 'change: 0.10749866486346475', 'is_elite: False']\n", + "Id: 46_48 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_93', '45_99'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_48', 'origin': '45_93~CUW~45_99#MGNP'} Metrics: ['ELUC: -3.987707938550348', 'NSGA-II_crowding_distance: 0.13390440221844682', 'NSGA-II_rank: 1', 'change: 0.07835386728981082', 'is_elite: False']\n", + "Id: 46_22 Identity: {'ancestor_count': 42, 'ancestor_ids': ['1_1', '44_44'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_22', 'origin': '1_1~CUW~44_44#MGNP'} Metrics: ['ELUC: -4.385265080428494', 'NSGA-II_crowding_distance: 0.08413283638547947', 'NSGA-II_rank: 1', 'change: 0.08675161731769147', 'is_elite: False']\n", + "Id: 46_69 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_69', 'origin': '45_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.735403761076621', 'NSGA-II_crowding_distance: 0.7822272650036495', 'NSGA-II_rank: 5', 'change: 0.19332302648347902', 'is_elite: False']\n", + "Id: 46_56 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_47', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_56', 'origin': '45_47~CUW~36_72#MGNP'} Metrics: ['ELUC: -4.8504594190618535', 'NSGA-II_crowding_distance: 0.11661303825041258', 'NSGA-II_rank: 1', 'change: 0.08881607221766977', 'is_elite: False']\n", + "Id: 46_66 Identity: {'ancestor_count': 42, 'ancestor_ids': ['1_1', '44_44'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_66', 'origin': '1_1~CUW~44_44#MGNP'} Metrics: ['ELUC: -4.916990097619663', 'NSGA-II_crowding_distance: 0.2742594939911955', 'NSGA-II_rank: 2', 'change: 0.09494485247469413', 'is_elite: False']\n", + "Id: 46_98 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '45_48'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_98', 'origin': '45_50~CUW~45_48#MGNP'} Metrics: ['ELUC: -6.091044156335501', 'NSGA-II_crowding_distance: 0.5679165096635121', 'NSGA-II_rank: 4', 'change: 0.16655543519939978', 'is_elite: False']\n", + "Id: 46_96 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_93', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_96', 'origin': '45_93~CUW~45_50#MGNP'} Metrics: ['ELUC: -6.216219267688328', 'NSGA-II_crowding_distance: 0.1361802782761288', 'NSGA-II_rank: 1', 'change: 0.09047449233792075', 'is_elite: False']\n", + "Id: 46_50 Identity: {'ancestor_count': 44, 'ancestor_ids': ['1_1', '45_44'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_50', 'origin': '1_1~CUW~45_44#MGNP'} Metrics: ['ELUC: -6.801406403107257', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.19791736901711765', 'is_elite: False']\n", + "Id: 45_50 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_55', '44_44'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_50', 'origin': '44_55~CUW~44_44#MGNP'} Metrics: ['ELUC: -6.815514236989108', 'NSGA-II_crowding_distance: 0.1427431991361422', 'NSGA-II_rank: 1', 'change: 0.09610164656542818', 'is_elite: False']\n", + "Id: 46_19 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_93', '44_44'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_19', 'origin': '45_93~CUW~44_44#MGNP'} Metrics: ['ELUC: -6.842748860773981', 'NSGA-II_crowding_distance: 0.4098556992447552', 'NSGA-II_rank: 3', 'change: 0.11896664807091825', 'is_elite: False']\n", + "Id: 46_61 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_61', 'origin': '45_50~CUW~45_50#MGNP'} Metrics: ['ELUC: -7.0239370794519695', 'NSGA-II_crowding_distance: 0.2069141509832824', 'NSGA-II_rank: 2', 'change: 0.10541243935575827', 'is_elite: False']\n", + "Id: 46_34 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_34', 'origin': '45_50~CUW~45_67#MGNP'} Metrics: ['ELUC: -7.138277628624603', 'NSGA-II_crowding_distance: 0.6263355595298304', 'NSGA-II_rank: 5', 'change: 0.19634164952504835', 'is_elite: False']\n", + "Id: 46_47 Identity: {'ancestor_count': 43, 'ancestor_ids': ['45_80', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_47', 'origin': '45_80~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.516479146393241', 'NSGA-II_crowding_distance: 0.35223911912220773', 'NSGA-II_rank: 3', 'change: 0.16297762001492505', 'is_elite: False']\n", + "Id: 46_93 Identity: {'ancestor_count': 44, 'ancestor_ids': ['44_44', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_93', 'origin': '44_44~CUW~45_50#MGNP'} Metrics: ['ELUC: -7.589458095541426', 'NSGA-II_crowding_distance: 0.17041206394450456', 'NSGA-II_rank: 2', 'change: 0.11054664709092482', 'is_elite: False']\n", + "Id: 46_44 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '43_61'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_44', 'origin': '43_61~CUW~43_61#MGNP'} Metrics: ['ELUC: -7.997490038679059', 'NSGA-II_crowding_distance: 0.14819719700819994', 'NSGA-II_rank: 1', 'change: 0.10283716792434477', 'is_elite: False']\n", + "Id: 46_32 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '43_61'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_32', 'origin': '45_50~CUW~43_61#MGNP'} Metrics: ['ELUC: -8.037048773858476', 'NSGA-II_crowding_distance: 0.18272977490716844', 'NSGA-II_rank: 2', 'change: 0.13599733110864037', 'is_elite: False']\n", + "Id: 46_71 Identity: {'ancestor_count': 44, 'ancestor_ids': ['36_72', '45_44'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_71', 'origin': '36_72~CUW~45_44#MGNP'} Metrics: ['ELUC: -8.248563635809738', 'NSGA-II_crowding_distance: 0.7383162313702716', 'NSGA-II_rank: 5', 'change: 0.26241437724201694', 'is_elite: False']\n", + "Id: 46_38 Identity: {'ancestor_count': 44, 'ancestor_ids': ['43_61', '45_44'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_38', 'origin': '43_61~CUW~45_44#MGNP'} Metrics: ['ELUC: -8.260843637703303', 'NSGA-II_crowding_distance: 0.8792737502529997', 'NSGA-II_rank: 4', 'change: 0.18054472673964006', 'is_elite: False']\n", + "Id: 46_92 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_93', '43_61'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_92', 'origin': '45_93~CUW~43_61#MGNP'} Metrics: ['ELUC: -8.28205639061523', 'NSGA-II_crowding_distance: 0.08561684163973729', 'NSGA-II_rank: 2', 'change: 0.14922087948435903', 'is_elite: False']\n", + "Id: 43_61 Identity: {'ancestor_count': 41, 'ancestor_ids': ['36_72', '42_68'], 'birth_generation': 43, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '43_61', 'origin': '36_72~CUW~42_68#MGNP'} Metrics: ['ELUC: -8.65516379957708', 'NSGA-II_crowding_distance: 0.15670496918713883', 'NSGA-II_rank: 1', 'change: 0.10910096748723958', 'is_elite: False']\n", + "Id: 46_72 Identity: {'ancestor_count': 43, 'ancestor_ids': ['45_99', '45_80'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_72', 'origin': '45_99~CUW~45_80#MGNP'} Metrics: ['ELUC: -8.662032299973802', 'NSGA-II_crowding_distance: 0.18496253532470758', 'NSGA-II_rank: 2', 'change: 0.14963183915498282', 'is_elite: False']\n", + "Id: 45_25 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_55', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_25', 'origin': '44_55~CUW~43_61#MGNP'} Metrics: ['ELUC: -9.866687953876475', 'NSGA-II_crowding_distance: 0.16806978483125556', 'NSGA-II_rank: 1', 'change: 0.11787357381367805', 'is_elite: True']\n", + "Id: 46_90 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_47', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_90', 'origin': '45_47~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.002507567614193', 'NSGA-II_crowding_distance: 0.3496456143236333', 'NSGA-II_rank: 3', 'change: 0.1651391791896766', 'is_elite: False']\n", + "Id: 46_14 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_14', 'origin': '45_25~CUW~45_50#MGNP'} Metrics: ['ELUC: -10.835497310177685', 'NSGA-II_crowding_distance: 0.2846478032678085', 'NSGA-II_rank: 1', 'change: 0.12224831415675627', 'is_elite: True']\n", + "Id: 46_30 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_47', '43_61'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_30', 'origin': '45_47~CUW~43_61#MGNP'} Metrics: ['ELUC: -11.099588193763879', 'NSGA-II_crowding_distance: 0.2353651439960301', 'NSGA-II_rank: 2', 'change: 0.15676864254505946', 'is_elite: False']\n", + "Id: 46_24 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_47', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_24', 'origin': '45_47~CUW~36_72#MGNP'} Metrics: ['ELUC: -11.320689670175822', 'NSGA-II_crowding_distance: 0.15804927048211498', 'NSGA-II_rank: 2', 'change: 0.17307141712218083', 'is_elite: False']\n", + "Id: 46_60 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_48', '45_25'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_60', 'origin': '45_48~CUW~45_25#MGNP'} Metrics: ['ELUC: -11.558882070373876', 'NSGA-II_crowding_distance: 0.565940191208036', 'NSGA-II_rank: 3', 'change: 0.19492348602635726', 'is_elite: False']\n", + "Id: 46_45 Identity: {'ancestor_count': 44, 'ancestor_ids': ['1_1', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_45', 'origin': '1_1~CUW~45_67#MGNP'} Metrics: ['ELUC: -12.2375198510551', 'NSGA-II_crowding_distance: 0.38300395673198373', 'NSGA-II_rank: 5', 'change: 0.26583016479164584', 'is_elite: False']\n", + "Id: 46_27 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '44_47'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_27', 'origin': '45_44~CUW~44_47#MGNP'} Metrics: ['ELUC: -12.39759712942885', 'NSGA-II_crowding_distance: 0.2906338059687299', 'NSGA-II_rank: 2', 'change: 0.17978385213641573', 'is_elite: False']\n", + "Id: 46_82 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_93', '45_25'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_82', 'origin': '45_93~CUW~45_25#MGNP'} Metrics: ['ELUC: -12.632129553403198', 'NSGA-II_crowding_distance: 0.31145522620755206', 'NSGA-II_rank: 1', 'change: 0.15587573858982978', 'is_elite: True']\n", + "Id: 46_41 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_61', '44_47'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_41', 'origin': '43_61~CUW~44_47#MGNP'} Metrics: ['ELUC: -12.838321815123214', 'NSGA-II_crowding_distance: 0.27850065542345315', 'NSGA-II_rank: 1', 'change: 0.18119106362699797', 'is_elite: True']\n", + "Id: 46_91 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_48', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_91', 'origin': '45_48~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.968362593120975', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29415962307862337', 'is_elite: False']\n", + "Id: 46_99 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_45', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_99', 'origin': '45_45~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.409026085684857', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.26707204573567106', 'is_elite: False']\n", + "Id: 46_78 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '1_1'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_78', 'origin': '45_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.56005556221206', 'NSGA-II_crowding_distance: 0.7490710686278308', 'NSGA-II_rank: 4', 'change: 0.2648516503430346', 'is_elite: False']\n", + "Id: 46_33 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_48', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_33', 'origin': '45_48~CUW~45_50#MGNP'} Metrics: ['ELUC: -13.703907889897916', 'NSGA-II_crowding_distance: 0.27210514020692333', 'NSGA-II_rank: 2', 'change: 0.2154483800555438', 'is_elite: False']\n", + "Id: 46_67 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_50', '45_80'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_67', 'origin': '45_50~CUW~45_80#MGNP'} Metrics: ['ELUC: -13.86706244958924', 'NSGA-II_crowding_distance: 0.10590689459302056', 'NSGA-II_rank: 2', 'change: 0.23083313598051014', 'is_elite: False']\n", + "Id: 46_11 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '45_44'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_11', 'origin': '45_25~CUW~45_44#MGNP'} Metrics: ['ELUC: -13.967452868497823', 'NSGA-II_crowding_distance: 0.09671347890878815', 'NSGA-II_rank: 2', 'change: 0.23992171525012818', 'is_elite: False']\n", + "Id: 46_20 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_67', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_20', 'origin': '45_67~CUW~45_50#MGNP'} Metrics: ['ELUC: -13.979032152443427', 'NSGA-II_crowding_distance: 0.17016789853789005', 'NSGA-II_rank: 4', 'change: 0.2742059375342183', 'is_elite: False']\n", + "Id: 46_54 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_47', '45_80'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_54', 'origin': '44_47~CUW~45_80#MGNP'} Metrics: ['ELUC: -14.19030554600271', 'NSGA-II_crowding_distance: 0.25364834354504207', 'NSGA-II_rank: 1', 'change: 0.21253140083225908', 'is_elite: True']\n", + "Id: 46_77 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_77', 'origin': '45_44~CUW~36_72#MGNP'} Metrics: ['ELUC: -14.242082643785881', 'NSGA-II_crowding_distance: 0.4435674641211821', 'NSGA-II_rank: 3', 'change: 0.2521575372159085', 'is_elite: False']\n", + "Id: 46_16 Identity: {'ancestor_count': 44, 'ancestor_ids': ['43_61', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_16', 'origin': '43_61~CUW~45_67#MGNP'} Metrics: ['ELUC: -14.401092068701837', 'NSGA-II_crowding_distance: 0.1669662978602814', 'NSGA-II_rank: 3', 'change: 0.2704937715072363', 'is_elite: False']\n", + "Id: 46_53 Identity: {'ancestor_count': 44, 'ancestor_ids': ['36_72', '45_48'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_53', 'origin': '36_72~CUW~45_48#MGNP'} Metrics: ['ELUC: -14.52435227949992', 'NSGA-II_crowding_distance: 0.23849835218243542', 'NSGA-II_rank: 2', 'change: 0.2469618303317467', 'is_elite: False']\n", + "Id: 44_47 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_97', '42_68'], 'birth_generation': 44, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '44_47', 'origin': '43_97~CUW~42_68#MGNP'} Metrics: ['ELUC: -14.820926638353868', 'NSGA-II_crowding_distance: 0.15549602679667224', 'NSGA-II_rank: 1', 'change: 0.22322866180314146', 'is_elite: False']\n", + "Id: 46_49 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '45_45'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_49', 'origin': '45_44~CUW~45_45#MGNP'} Metrics: ['ELUC: -14.857558761442567', 'NSGA-II_crowding_distance: 0.12277543085454398', 'NSGA-II_rank: 4', 'change: 0.2861520552921618', 'is_elite: False']\n", + "Id: 46_85 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_80', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_85', 'origin': '45_80~CUW~45_67#MGNP'} Metrics: ['ELUC: -14.989991803925937', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2884230128087769', 'is_elite: False']\n", + "Id: 46_51 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_48', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_51', 'origin': '45_48~CUW~36_72#MGNP'} Metrics: ['ELUC: -15.325508310824558', 'NSGA-II_crowding_distance: 0.18358876256276974', 'NSGA-II_rank: 1', 'change: 0.23966320914988926', 'is_elite: True']\n", + "Id: 46_70 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_67', '45_48'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_70', 'origin': '45_67~CUW~45_48#MGNP'} Metrics: ['ELUC: -15.69612590424096', 'NSGA-II_crowding_distance: 0.2699195448336005', 'NSGA-II_rank: 3', 'change: 0.27471425582345077', 'is_elite: False']\n", + "Id: 46_76 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_76', 'origin': '45_25~CUW~45_67#MGNP'} Metrics: ['ELUC: -15.967524075271626', 'NSGA-II_crowding_distance: 0.2540746057579207', 'NSGA-II_rank: 2', 'change: 0.27403446193819253', 'is_elite: False']\n", + "Id: 46_18 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_48', '45_48'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_18', 'origin': '45_48~CUW~45_48#MGNP'} Metrics: ['ELUC: -16.02189314738255', 'NSGA-II_crowding_distance: 0.10890115539732662', 'NSGA-II_rank: 1', 'change: 0.2576266854036774', 'is_elite: False']\n", + "Id: 45_48 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_49', '44_49'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_48', 'origin': '44_49~CUW~44_49#MGNP'} Metrics: ['ELUC: -16.083232108807437', 'NSGA-II_crowding_distance: 0.12860639414898506', 'NSGA-II_rank: 1', 'change: 0.2592980806320238', 'is_elite: False']\n", + "Id: 46_83 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_83', 'origin': '45_25~CUW~45_67#MGNP'} Metrics: ['ELUC: -16.130672571950697', 'NSGA-II_crowding_distance: 0.15794270794488857', 'NSGA-II_rank: 2', 'change: 0.29113141738438486', 'is_elite: False']\n", + "Id: 46_39 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_80', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_39', 'origin': '45_80~CUW~45_67#MGNP'} Metrics: ['ELUC: -16.839921537358236', 'NSGA-II_crowding_distance: 0.15255799719925875', 'NSGA-II_rank: 1', 'change: 0.282117773475648', 'is_elite: False']\n", + "Id: 46_97 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '2_49'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_97', 'origin': '43_61~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.91016417845592', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30453032865715707', 'is_elite: False']\n", + "Id: 46_80 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '44_47'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_80', 'origin': '45_44~CUW~44_47#MGNP'} Metrics: ['ELUC: -17.080842724211053', 'NSGA-II_crowding_distance: 0.06892003475291308', 'NSGA-II_rank: 1', 'change: 0.2878882275707209', 'is_elite: False']\n", + "Id: 46_43 Identity: {'ancestor_count': 44, 'ancestor_ids': ['36_72', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_43', 'origin': '36_72~CUW~45_67#MGNP'} Metrics: ['ELUC: -17.081414571484945', 'NSGA-II_crowding_distance: 0.12437096641697676', 'NSGA-II_rank: 2', 'change: 0.2997699862422951', 'is_elite: False']\n", + "Id: 45_44 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_96', '44_66'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_44', 'origin': '44_96~CUW~44_66#MGNP'} Metrics: ['ELUC: -17.210102012949964', 'NSGA-II_crowding_distance: 0.053987515753183654', 'NSGA-II_rank: 1', 'change: 0.296399899171206', 'is_elite: False']\n", + "Id: 46_95 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_44', '44_47'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_95', 'origin': '45_44~CUW~44_47#MGNP'} Metrics: ['ELUC: -17.335551116477916', 'NSGA-II_crowding_distance: 0.0277633743320004', 'NSGA-II_rank: 1', 'change: 0.29967441921611687', 'is_elite: False']\n", + "Id: 46_46 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_80', '45_67'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_46', 'origin': '45_80~CUW~45_67#MGNP'} Metrics: ['ELUC: -17.489581387328997', 'NSGA-II_crowding_distance: 0.024898663996884163', 'NSGA-II_rank: 1', 'change: 0.2999410202378972', 'is_elite: False']\n", + "Id: 46_65 Identity: {'ancestor_count': 43, 'ancestor_ids': ['2_49', '45_70'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_65', 'origin': '2_49~CUW~45_70#MGNP'} Metrics: ['ELUC: -17.533850942243962', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3035426967756976', 'is_elite: False']\n", + "Id: 46_86 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_67', '45_80'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_86', 'origin': '45_67~CUW~45_80#MGNP'} Metrics: ['ELUC: -17.578592953368897', 'NSGA-II_crowding_distance: 0.01645207863190818', 'NSGA-II_rank: 1', 'change: 0.3029791308007254', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 45_67 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_66', '1_1'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_67', 'origin': '44_66~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 46_29 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_67', '45_44'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_29', 'origin': '45_67~CUW~45_44#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 46_74 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_67', '43_61'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_74', 'origin': '45_67~CUW~43_61#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 46.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 47...:\n", + "PopulationResponse:\n", + " Generation: 47\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/47/20240220-011921\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 47 and asking ESP for generation 48...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 47 data persisted.\n", + "Evaluated candidates:\n", + "Id: 47_29 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_29', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.3961935574731609', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03901563285696545', 'is_elite: False']\n", + "Id: 47_96 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '36_72'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_96', 'origin': '36_72~CUW~36_72#MGNP'} Metrics: ['ELUC: 0.2171610249196229', 'NSGA-II_crowding_distance: 0.10096347518984261', 'NSGA-II_rank: 3', 'change: 0.04614025508519922', 'is_elite: False']\n", + "Id: 47_74 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_74', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.0621927243981663', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2723050195314089', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 47_36 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_36', 'origin': '46_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.4752928184555698', 'NSGA-II_crowding_distance: 0.18896646493632466', 'NSGA-II_rank: 3', 'change: 0.048110224863141815', 'is_elite: False']\n", + "Id: 47_86 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_41', '46_12'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_86', 'origin': '46_41~CUW~46_12#MGNP'} Metrics: ['ELUC: -0.538668509537824', 'NSGA-II_crowding_distance: 0.3528640930497475', 'NSGA-II_rank: 3', 'change: 0.07555379649065022', 'is_elite: False']\n", + "Id: 47_87 Identity: {'ancestor_count': 4, 'ancestor_ids': ['46_12', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_87', 'origin': '46_12~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6669779912895506', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03735351031208716', 'is_elite: False']\n", + "Id: 47_66 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '2_49'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_66', 'origin': '36_72~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.9019333627929744', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2305763028974049', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.21300579589861054', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: True']\n", + "Id: 47_43 Identity: {'ancestor_count': 4, 'ancestor_ids': ['46_12', '36_72'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_43', 'origin': '46_12~CUW~36_72#MGNP'} Metrics: ['ELUC: -1.1369319366255757', 'NSGA-II_crowding_distance: 0.1847217390025965', 'NSGA-II_rank: 1', 'change: 0.049160208178667425', 'is_elite: True']\n", + "Id: 47_18 Identity: {'ancestor_count': 44, 'ancestor_ids': ['2_49', '45_50'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_18', 'origin': '2_49~CUW~45_50#MGNP'} Metrics: ['ELUC: -1.7725262326656404', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26910552882345035', 'is_elite: False']\n", + "Id: 47_62 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_12'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_62', 'origin': '46_82~CUW~46_12#MGNP'} Metrics: ['ELUC: -1.9711709478009365', 'NSGA-II_crowding_distance: 0.23544798036305764', 'NSGA-II_rank: 1', 'change: 0.06821625777257528', 'is_elite: True']\n", + "Id: 47_70 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_74', '36_72'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_70', 'origin': '46_74~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.33338314309874', 'NSGA-II_crowding_distance: 0.5426062990366867', 'NSGA-II_rank: 8', 'change: 0.23686529207486287', 'is_elite: False']\n", + "Id: 47_93 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_48', '36_72'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_93', 'origin': '46_48~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.474960945137256', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09619121879474045', 'is_elite: False']\n", + "Id: 47_92 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '2_49'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_92', 'origin': '46_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.5654794912161862', 'NSGA-II_crowding_distance: 1.2412949256532892', 'NSGA-II_rank: 8', 'change: 0.2538857657095457', 'is_elite: False']\n", + "Id: 47_44 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '46_12'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_44', 'origin': '46_14~CUW~46_12#MGNP'} Metrics: ['ELUC: -2.8483546181749575', 'NSGA-II_crowding_distance: 0.1970410862809004', 'NSGA-II_rank: 4', 'change: 0.11298353154154915', 'is_elite: False']\n", + "Id: 47_89 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '46_12'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_89', 'origin': '45_25~CUW~46_12#MGNP'} Metrics: ['ELUC: -3.2197787144674765', 'NSGA-II_crowding_distance: 0.3373460122191236', 'NSGA-II_rank: 3', 'change: 0.0841616736754697', 'is_elite: False']\n", + "Id: 47_35 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_12', '45_25'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_35', 'origin': '46_12~CUW~45_25#MGNP'} Metrics: ['ELUC: -3.54351259697733', 'NSGA-II_crowding_distance: 0.5124504016566123', 'NSGA-II_rank: 4', 'change: 0.1170248039878072', 'is_elite: False']\n", + "Id: 47_81 Identity: {'ancestor_count': 4, 'ancestor_ids': ['46_12', '46_12'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_81', 'origin': '46_12~CUW~46_12#MGNP'} Metrics: ['ELUC: -3.6696209284653976', 'NSGA-II_crowding_distance: 0.19507677223147207', 'NSGA-II_rank: 1', 'change: 0.07643212572826882', 'is_elite: True']\n", + "Id: 47_63 Identity: {'ancestor_count': 43, 'ancestor_ids': ['1_1', '44_47'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_63', 'origin': '1_1~CUW~44_47#MGNP'} Metrics: ['ELUC: -3.892805958861006', 'NSGA-II_crowding_distance: 0.20359019841371842', 'NSGA-II_rank: 3', 'change: 0.09967978035076178', 'is_elite: False']\n", + "Id: 47_94 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '46_48'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_94', 'origin': '46_14~CUW~46_48#MGNP'} Metrics: ['ELUC: -4.279958035999793', 'NSGA-II_crowding_distance: 0.41135303635102327', 'NSGA-II_rank: 3', 'change: 0.11237069872347444', 'is_elite: False']\n", + "Id: 47_85 Identity: {'ancestor_count': 44, 'ancestor_ids': ['36_72', '45_50'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_85', 'origin': '36_72~CUW~45_50#MGNP'} Metrics: ['ELUC: -4.601728210789532', 'NSGA-II_crowding_distance: 0.5148257847774902', 'NSGA-II_rank: 2', 'change: 0.08203868707821697', 'is_elite: False']\n", + "Id: 47_24 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '36_72'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_24', 'origin': '43_61~CUW~36_72#MGNP'} Metrics: ['ELUC: -4.604222883003917', 'NSGA-II_crowding_distance: 0.1283705164405167', 'NSGA-II_rank: 1', 'change: 0.08173911643590218', 'is_elite: False']\n", + "Id: 47_77 Identity: {'ancestor_count': 45, 'ancestor_ids': ['43_61', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_77', 'origin': '43_61~CUW~46_74#MGNP'} Metrics: ['ELUC: -4.790500098601896', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15657418820783137', 'is_elite: False']\n", + "Id: 47_15 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_74', '46_14'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_15', 'origin': '46_74~CUW~46_14#MGNP'} Metrics: ['ELUC: -4.992927340558375', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.20427435615765036', 'is_elite: False']\n", + "Id: 47_37 Identity: {'ancestor_count': 45, 'ancestor_ids': ['1_1', '46_51'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_37', 'origin': '1_1~CUW~46_51#MGNP'} Metrics: ['ELUC: -5.04647801781839', 'NSGA-II_crowding_distance: 0.2242397254904101', 'NSGA-II_rank: 2', 'change: 0.10441555440456807', 'is_elite: False']\n", + "Id: 47_45 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_54', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_45', 'origin': '46_54~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.302301526782616', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.1492923173889629', 'is_elite: False']\n", + "Id: 47_60 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_48', '36_72'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_60', 'origin': '46_48~CUW~36_72#MGNP'} Metrics: ['ELUC: -5.433493026734568', 'NSGA-II_crowding_distance: 0.1264132729996003', 'NSGA-II_rank: 1', 'change: 0.08480157394036315', 'is_elite: False']\n", + "Id: 47_61 Identity: {'ancestor_count': 42, 'ancestor_ids': ['36_72', '43_61'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_61', 'origin': '36_72~CUW~43_61#MGNP'} Metrics: ['ELUC: -6.033098771153534', 'NSGA-II_crowding_distance: 0.19725649116195476', 'NSGA-II_rank: 1', 'change: 0.09520955574441171', 'is_elite: True']\n", + "Id: 47_91 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_48', '44_47'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_91', 'origin': '46_48~CUW~44_47#MGNP'} Metrics: ['ELUC: -6.577783602325289', 'NSGA-II_crowding_distance: 0.23114551503465994', 'NSGA-II_rank: 2', 'change: 0.1101152200179727', 'is_elite: False']\n", + "Id: 47_76 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_76', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.792604272866411', 'NSGA-II_crowding_distance: 1.4573937009633133', 'NSGA-II_rank: 8', 'change: 0.2830721443326994', 'is_elite: False']\n", + "Id: 47_48 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_48', 'origin': '45_25~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.3080800442895955', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.1393571151342439', 'is_elite: False']\n", + "Id: 47_42 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '46_44'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_42', 'origin': '46_14~CUW~46_44#MGNP'} Metrics: ['ELUC: -7.417857746525274', 'NSGA-II_crowding_distance: 0.15900798789454296', 'NSGA-II_rank: 1', 'change: 0.1099832341062262', 'is_elite: False']\n", + "Id: 47_46 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_41', '43_61'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_46', 'origin': '46_41~CUW~43_61#MGNP'} Metrics: ['ELUC: -7.826710380327595', 'NSGA-II_crowding_distance: 0.1999117746177589', 'NSGA-II_rank: 5', 'change: 0.14561886829343537', 'is_elite: False']\n", + "Id: 47_39 Identity: {'ancestor_count': 44, 'ancestor_ids': ['43_61', '45_50'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_39', 'origin': '43_61~CUW~45_50#MGNP'} Metrics: ['ELUC: -7.886937698402816', 'NSGA-II_crowding_distance: 0.5209833020726153', 'NSGA-II_rank: 4', 'change: 0.1307241861939502', 'is_elite: False']\n", + "Id: 47_84 Identity: {'ancestor_count': 44, 'ancestor_ids': ['2_49', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_84', 'origin': '2_49~CUW~46_41#MGNP'} Metrics: ['ELUC: -7.912886114155466', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.30691864273223485', 'is_elite: False']\n", + "Id: 47_55 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '46_54'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_55', 'origin': '45_25~CUW~46_54#MGNP'} Metrics: ['ELUC: -7.954325254485958', 'NSGA-II_crowding_distance: 0.08105008186134366', 'NSGA-II_rank: 1', 'change: 0.1100501902570355', 'is_elite: False']\n", + "Id: 47_54 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_74', '46_12'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_54', 'origin': '46_74~CUW~46_12#MGNP'} Metrics: ['ELUC: -8.076829847016194', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.20904526825675854', 'is_elite: False']\n", + "Id: 47_53 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_74', '43_61'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_53', 'origin': '46_74~CUW~43_61#MGNP'} Metrics: ['ELUC: -8.096628530892508', 'NSGA-II_crowding_distance: 0.13745442481435993', 'NSGA-II_rank: 5', 'change: 0.15331444122676002', 'is_elite: False']\n", + "Id: 47_13 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_12', '46_54'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_13', 'origin': '46_12~CUW~46_54#MGNP'} Metrics: ['ELUC: -8.108427591459947', 'NSGA-II_crowding_distance: 0.26463429018769624', 'NSGA-II_rank: 5', 'change: 0.16100812904129294', 'is_elite: False']\n", + "Id: 47_64 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_44', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_64', 'origin': '46_44~CUW~46_82#MGNP'} Metrics: ['ELUC: -8.280249449151036', 'NSGA-II_crowding_distance: 0.2032105480491242', 'NSGA-II_rank: 2', 'change: 0.11355574208569084', 'is_elite: False']\n", + "Id: 47_83 Identity: {'ancestor_count': 44, 'ancestor_ids': ['1_1', '46_54'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_83', 'origin': '1_1~CUW~46_54#MGNP'} Metrics: ['ELUC: -8.501708032362828', 'NSGA-II_crowding_distance: 0.26715485203779943', 'NSGA-II_rank: 4', 'change: 0.13771042903356645', 'is_elite: False']\n", + "Id: 47_65 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_44', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_65', 'origin': '46_44~CUW~46_41#MGNP'} Metrics: ['ELUC: -8.660868763136543', 'NSGA-II_crowding_distance: 0.3521137500915605', 'NSGA-II_rank: 3', 'change: 0.11949829561871443', 'is_elite: False']\n", + "Id: 47_95 Identity: {'ancestor_count': 42, 'ancestor_ids': ['43_61', '43_61'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_95', 'origin': '43_61~CUW~43_61#MGNP'} Metrics: ['ELUC: -8.697966746626335', 'NSGA-II_crowding_distance: 0.13498584496716082', 'NSGA-II_rank: 1', 'change: 0.11244292806160151', 'is_elite: False']\n", + "Id: 47_33 Identity: {'ancestor_count': 45, 'ancestor_ids': ['45_50', '46_51'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_33', 'origin': '45_50~CUW~46_51#MGNP'} Metrics: ['ELUC: -8.755737075814677', 'NSGA-II_crowding_distance: 1.5346918841255972', 'NSGA-II_rank: 6', 'change: 0.17578205663949417', 'is_elite: False']\n", + "Id: 47_16 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_16', 'origin': '46_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.003640684243454', 'NSGA-II_crowding_distance: 0.16150102598893723', 'NSGA-II_rank: 3', 'change: 0.12024205375767451', 'is_elite: False']\n", + "Id: 47_30 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_74', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_30', 'origin': '46_74~CUW~46_41#MGNP'} Metrics: ['ELUC: -9.281004901786085', 'NSGA-II_crowding_distance: 0.9117392877150783', 'NSGA-II_rank: 6', 'change: 0.20795843978964043', 'is_elite: False']\n", + "Id: 47_68 Identity: {'ancestor_count': 45, 'ancestor_ids': ['43_61', '46_14'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_68', 'origin': '43_61~CUW~46_14#MGNP'} Metrics: ['ELUC: -9.401999710299908', 'NSGA-II_crowding_distance: 0.15577654754576603', 'NSGA-II_rank: 2', 'change: 0.11846080565160677', 'is_elite: False']\n", + "Id: 47_17 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_96', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_17', 'origin': '46_96~CUW~46_74#MGNP'} Metrics: ['ELUC: -9.49389180405559', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.24949391003567498', 'is_elite: False']\n", + "Id: 47_47 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_48', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_47', 'origin': '45_48~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.578129183781346', 'NSGA-II_crowding_distance: 1.7495856743415659', 'NSGA-II_rank: 5', 'change: 0.16205756321795767', 'is_elite: False']\n", + "Id: 45_25 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_55', '43_61'], 'birth_generation': 45, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '45_25', 'origin': '44_55~CUW~43_61#MGNP'} Metrics: ['ELUC: -9.866687953876475', 'NSGA-II_crowding_distance: 0.10279207971907155', 'NSGA-II_rank: 1', 'change: 0.11787357381367805', 'is_elite: False']\n", + "Id: 47_97 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_54', '46_44'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_97', 'origin': '46_54~CUW~46_44#MGNP'} Metrics: ['ELUC: -9.896679706971724', 'NSGA-II_crowding_distance: 0.2052662889898799', 'NSGA-II_rank: 4', 'change: 0.14992394721380617', 'is_elite: False']\n", + "Id: 47_25 Identity: {'ancestor_count': 45, 'ancestor_ids': ['43_61', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_25', 'origin': '43_61~CUW~46_82#MGNP'} Metrics: ['ELUC: -10.006085207931186', 'NSGA-II_crowding_distance: 0.06976303079186774', 'NSGA-II_rank: 1', 'change: 0.12091462045542013', 'is_elite: False']\n", + "Id: 47_67 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_51', '1_1'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_67', 'origin': '46_51~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.06069224051923', 'NSGA-II_crowding_distance: 0.6342958353022375', 'NSGA-II_rank: 4', 'change: 0.1522234777136629', 'is_elite: False']\n", + "Id: 47_11 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_48'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_11', 'origin': '46_82~CUW~46_48#MGNP'} Metrics: ['ELUC: -10.093426115913822', 'NSGA-II_crowding_distance: 0.18400975951699816', 'NSGA-II_rank: 3', 'change: 0.13350051037490374', 'is_elite: False']\n", + "Id: 47_100 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '46_14'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_100', 'origin': '46_14~CUW~46_14#MGNP'} Metrics: ['ELUC: -10.261775819410731', 'NSGA-II_crowding_distance: 0.10743597944442371', 'NSGA-II_rank: 2', 'change: 0.12298834420000405', 'is_elite: False']\n", + "Id: 47_12 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_96', '46_44'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_12', 'origin': '46_96~CUW~46_44#MGNP'} Metrics: ['ELUC: -10.346105958579416', 'NSGA-II_crowding_distance: 0.09178088408327204', 'NSGA-II_rank: 3', 'change: 0.14029797845254183', 'is_elite: False']\n", + "Id: 47_82 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '46_96'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_82', 'origin': '46_14~CUW~46_96#MGNP'} Metrics: ['ELUC: -10.55314477430221', 'NSGA-II_crowding_distance: 0.17543758731282486', 'NSGA-II_rank: 3', 'change: 0.146475466815191', 'is_elite: False']\n", + "Id: 47_72 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_72', 'origin': '46_14~CUW~46_82#MGNP'} Metrics: ['ELUC: -10.77135775683421', 'NSGA-II_crowding_distance: 0.20354826886797223', 'NSGA-II_rank: 2', 'change: 0.12492097208290603', 'is_elite: False']\n", + "Id: 46_14 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_14', 'origin': '45_25~CUW~45_50#MGNP'} Metrics: ['ELUC: -10.835497310177685', 'NSGA-II_crowding_distance: 0.26034026052850595', 'NSGA-II_rank: 1', 'change: 0.12224831415675627', 'is_elite: True']\n", + "Id: 47_32 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '46_54'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_32', 'origin': '46_14~CUW~46_54#MGNP'} Metrics: ['ELUC: -10.9690475094767', 'NSGA-II_crowding_distance: 0.4936601496003779', 'NSGA-II_rank: 3', 'change: 0.1687209560997434', 'is_elite: False']\n", + "Id: 47_23 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_23', 'origin': '46_14~CUW~46_41#MGNP'} Metrics: ['ELUC: -11.649948896857957', 'NSGA-II_crowding_distance: 0.20068020809992565', 'NSGA-II_rank: 2', 'change: 0.1551835184689114', 'is_elite: False']\n", + "Id: 47_73 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '43_61'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_73', 'origin': '46_82~CUW~43_61#MGNP'} Metrics: ['ELUC: -11.722085387596005', 'NSGA-II_crowding_distance: 0.13590793104615548', 'NSGA-II_rank: 2', 'change: 0.16357605572573664', 'is_elite: False']\n", + "Id: 47_41 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_74', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_41', 'origin': '46_74~CUW~46_41#MGNP'} Metrics: ['ELUC: -12.052961608115282', 'NSGA-II_crowding_distance: 0.8555198344251032', 'NSGA-II_rank: 4', 'change: 0.23768939680879195', 'is_elite: False']\n", + "Id: 47_88 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_51', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_88', 'origin': '46_51~CUW~46_82#MGNP'} Metrics: ['ELUC: -12.161690184351249', 'NSGA-II_crowding_distance: 0.6200783650781063', 'NSGA-II_rank: 3', 'change: 0.22849775968993083', 'is_elite: False']\n", + "Id: 47_31 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_41', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_31', 'origin': '46_41~CUW~46_41#MGNP'} Metrics: ['ELUC: -12.394967787467257', 'NSGA-II_crowding_distance: 0.28018261466765365', 'NSGA-II_rank: 2', 'change: 0.17968868228086518', 'is_elite: False']\n", + "Id: 47_71 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_71', 'origin': '46_82~CUW~46_82#MGNP'} Metrics: ['ELUC: -12.588030833841653', 'NSGA-II_crowding_distance: 0.21488477247594076', 'NSGA-II_rank: 1', 'change: 0.15477793940682558', 'is_elite: True']\n", + "Id: 46_82 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_93', '45_25'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_82', 'origin': '45_93~CUW~45_25#MGNP'} Metrics: ['ELUC: -12.632129553403198', 'NSGA-II_crowding_distance: 0.042249408493562346', 'NSGA-II_rank: 1', 'change: 0.15587573858982978', 'is_elite: False']\n", + "Id: 47_56 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_56', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.68560768779302', 'NSGA-II_crowding_distance: 0.46800804559503045', 'NSGA-II_rank: 4', 'change: 0.2751698273410019', 'is_elite: False']\n", + "Id: 47_57 Identity: {'ancestor_count': 45, 'ancestor_ids': ['44_47', '46_96'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_57', 'origin': '44_47~CUW~46_96#MGNP'} Metrics: ['ELUC: -12.791234953722627', 'NSGA-II_crowding_distance: 0.09657045373161129', 'NSGA-II_rank: 1', 'change: 0.16393578481138205', 'is_elite: False']\n", + "Id: 46_41 Identity: {'ancestor_count': 43, 'ancestor_ids': ['43_61', '44_47'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_41', 'origin': '43_61~CUW~44_47#MGNP'} Metrics: ['ELUC: -12.838321815123214', 'NSGA-II_crowding_distance: 0.09299464024428097', 'NSGA-II_rank: 1', 'change: 0.18119106362699797', 'is_elite: False']\n", + "Id: 47_79 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_41', '46_51'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_79', 'origin': '46_41~CUW~46_51#MGNP'} Metrics: ['ELUC: -13.11090723941241', 'NSGA-II_crowding_distance: 0.05335875112575418', 'NSGA-II_rank: 1', 'change: 0.18625837581551655', 'is_elite: False']\n", + "Id: 47_58 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_54'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_58', 'origin': '46_82~CUW~46_54#MGNP'} Metrics: ['ELUC: -13.17768952740914', 'NSGA-II_crowding_distance: 0.10374335765440496', 'NSGA-II_rank: 1', 'change: 0.19135295116997988', 'is_elite: False']\n", + "Id: 47_38 Identity: {'ancestor_count': 44, 'ancestor_ids': ['44_47', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_38', 'origin': '44_47~CUW~46_41#MGNP'} Metrics: ['ELUC: -13.469075279711893', 'NSGA-II_crowding_distance: 0.4002152756296323', 'NSGA-II_rank: 2', 'change: 0.21060271441717512', 'is_elite: False']\n", + "Id: 47_78 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '44_47'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_78', 'origin': '46_82~CUW~44_47#MGNP'} Metrics: ['ELUC: -14.100419981410525', 'NSGA-II_crowding_distance: 0.09243307708598995', 'NSGA-II_rank: 1', 'change: 0.20042074558608453', 'is_elite: False']\n", + "Id: 47_50 Identity: {'ancestor_count': 44, 'ancestor_ids': ['46_41', '46_54'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_50', 'origin': '46_41~CUW~46_54#MGNP'} Metrics: ['ELUC: -14.145543055176518', 'NSGA-II_crowding_distance: 0.0457006013529141', 'NSGA-II_rank: 1', 'change: 0.20250814881579815', 'is_elite: False']\n", + "Id: 46_54 Identity: {'ancestor_count': 43, 'ancestor_ids': ['44_47', '45_80'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_54', 'origin': '44_47~CUW~45_80#MGNP'} Metrics: ['ELUC: -14.19030554600271', 'NSGA-II_crowding_distance: 0.10728566700466804', 'NSGA-II_rank: 1', 'change: 0.21253140083225908', 'is_elite: False']\n", + "Id: 47_99 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_99', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.391993748274091', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.29689540814524684', 'is_elite: False']\n", + "Id: 47_49 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_51', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_49', 'origin': '46_51~CUW~46_74#MGNP'} Metrics: ['ELUC: -14.45385518062961', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2893841739952273', 'is_elite: False']\n", + "Id: 47_26 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_26', 'origin': '46_82~CUW~46_74#MGNP'} Metrics: ['ELUC: -14.48087242771317', 'NSGA-II_crowding_distance: 0.2698903576223013', 'NSGA-II_rank: 3', 'change: 0.25063365996665227', 'is_elite: False']\n", + "Id: 47_28 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_51', '46_54'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_28', 'origin': '46_51~CUW~46_54#MGNP'} Metrics: ['ELUC: -14.490299544583847', 'NSGA-II_crowding_distance: 0.14242947695749053', 'NSGA-II_rank: 1', 'change: 0.2286691770535056', 'is_elite: False']\n", + "Id: 47_59 Identity: {'ancestor_count': 45, 'ancestor_ids': ['43_61', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_59', 'origin': '43_61~CUW~46_74#MGNP'} Metrics: ['ELUC: -14.597997659891089', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2512984017118914', 'is_elite: False']\n", + "Id: 46_51 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_48', '36_72'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_51', 'origin': '45_48~CUW~36_72#MGNP'} Metrics: ['ELUC: -15.325508310824558', 'NSGA-II_crowding_distance: 0.29859812835655625', 'NSGA-II_rank: 2', 'change: 0.23966320914988926', 'is_elite: False']\n", + "Id: 47_14 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_41', '46_51'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_14', 'origin': '46_41~CUW~46_51#MGNP'} Metrics: ['ELUC: -15.331255189527939', 'NSGA-II_crowding_distance: 0.11679367655408143', 'NSGA-II_rank: 1', 'change: 0.23566691557153663', 'is_elite: False']\n", + "Id: 47_75 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_75', 'origin': '46_82~CUW~46_74#MGNP'} Metrics: ['ELUC: -15.50857842689449', 'NSGA-II_crowding_distance: 0.35858067709832386', 'NSGA-II_rank: 2', 'change: 0.2577805755303368', 'is_elite: False']\n", + "Id: 47_69 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_54', '46_39'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_69', 'origin': '46_54~CUW~46_39#MGNP'} Metrics: ['ELUC: -15.600290274652576', 'NSGA-II_crowding_distance: 0.08116525081842073', 'NSGA-II_rank: 1', 'change: 0.24468092256419538', 'is_elite: False']\n", + "Id: 47_27 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_39', '45_25'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_27', 'origin': '46_39~CUW~45_25#MGNP'} Metrics: ['ELUC: -15.650003299671152', 'NSGA-II_crowding_distance: 0.08277721345729597', 'NSGA-II_rank: 1', 'change: 0.2544755639401839', 'is_elite: False']\n", + "Id: 47_20 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_74', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_20', 'origin': '46_74~CUW~46_82#MGNP'} Metrics: ['ELUC: -16.01710542503076', 'NSGA-II_crowding_distance: 0.05622165118638134', 'NSGA-II_rank: 1', 'change: 0.2623063167667892', 'is_elite: False']\n", + "Id: 47_19 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_51', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_19', 'origin': '46_51~CUW~46_82#MGNP'} Metrics: ['ELUC: -16.15073345047956', 'NSGA-II_crowding_distance: 0.06057417516042883', 'NSGA-II_rank: 1', 'change: 0.26275330675129294', 'is_elite: False']\n", + "Id: 47_52 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_39', '44_47'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_52', 'origin': '46_39~CUW~44_47#MGNP'} Metrics: ['ELUC: -16.384640370412093', 'NSGA-II_crowding_distance: 0.1566102385785349', 'NSGA-II_rank: 1', 'change: 0.2741431194156034', 'is_elite: False']\n", + "Id: 47_51 Identity: {'ancestor_count': 45, 'ancestor_ids': ['1_1', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_51', 'origin': '1_1~CUW~46_74#MGNP'} Metrics: ['ELUC: -17.04733021980626', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30835200701248644', 'is_elite: False']\n", + "Id: 47_80 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_39', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_80', 'origin': '46_39~CUW~46_74#MGNP'} Metrics: ['ELUC: -17.212232312166087', 'NSGA-II_crowding_distance: 0.15664862640452476', 'NSGA-II_rank: 1', 'change: 0.2914683489831015', 'is_elite: False']\n", + "Id: 47_40 Identity: {'ancestor_count': 45, 'ancestor_ids': ['45_50', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_40', 'origin': '45_50~CUW~46_74#MGNP'} Metrics: ['ELUC: -17.490059187216623', 'NSGA-II_crowding_distance: 0.060621825581457345', 'NSGA-II_rank: 1', 'change: 0.30212428054612034', 'is_elite: False']\n", + "Id: 47_98 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_39', '46_74'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_98', 'origin': '46_39~CUW~46_74#MGNP'} Metrics: ['ELUC: -17.59738598680002', 'NSGA-II_crowding_distance: 0.009107801180875404', 'NSGA-II_rank: 1', 'change: 0.30302037419068867', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 46_74 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_67', '43_61'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_74', 'origin': '45_67~CUW~43_61#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 47_21 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_51', '2_49'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_21', 'origin': '46_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 47_22 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_22', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 47_34 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_74', '2_49'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_34', 'origin': '46_74~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 47_90 Identity: {'ancestor_count': 44, 'ancestor_ids': ['2_49', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_90', 'origin': '2_49~CUW~46_41#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 47.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 48...:\n", + "PopulationResponse:\n", + " Generation: 48\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/48/20240220-012635\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 48 and asking ESP for generation 49...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 48 data persisted.\n", + "Evaluated candidates:\n", + "Id: 48_16 Identity: {'ancestor_count': 5, 'ancestor_ids': ['47_81', '2_49'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_16', 'origin': '47_81~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 48_76 Identity: {'ancestor_count': 46, 'ancestor_ids': ['2_49', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_76', 'origin': '2_49~CUW~47_71#MGNP'} Metrics: ['ELUC: 20.12153313812551', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2883782784736177', 'is_elite: False']\n", + "Id: 48_99 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '2_49'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_99', 'origin': '47_28~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.382070705860372', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2706347869556255', 'is_elite: False']\n", + "Id: 48_81 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_90', '36_72'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_81', 'origin': '47_90~CUW~36_72#MGNP'} Metrics: ['ELUC: 1.0920335198781232', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2647951674282997', 'is_elite: False']\n", + "Id: 48_97 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_61', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_97', 'origin': '47_61~CUW~47_71#MGNP'} Metrics: ['ELUC: 0.07566635836834362', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.12276046526498968', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 48_25 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_62', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_25', 'origin': '47_62~CUW~47_62#MGNP'} Metrics: ['ELUC: -0.8348698486087415', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06272859819227601', 'is_elite: False']\n", + "Id: 48_88 Identity: {'ancestor_count': 5, 'ancestor_ids': ['36_72', '47_81'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_88', 'origin': '36_72~CUW~47_81#MGNP'} Metrics: ['ELUC: -0.8712989670846958', 'NSGA-II_crowding_distance: 0.1395971379315889', 'NSGA-II_rank: 1', 'change: 0.028358494304072848', 'is_elite: False']\n", + "Id: 36_72 Identity: {'ancestor_count': 2, 'ancestor_ids': ['35_90', '1_1'], 'birth_generation': 36, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '36_72', 'origin': '35_90~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9948657309454719', 'NSGA-II_crowding_distance: 0.11475483174690654', 'NSGA-II_rank: 1', 'change: 0.029667607889921236', 'is_elite: False']\n", + "Id: 47_43 Identity: {'ancestor_count': 4, 'ancestor_ids': ['46_12', '36_72'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_43', 'origin': '46_12~CUW~36_72#MGNP'} Metrics: ['ELUC: -1.1369319366255757', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.049160208178667425', 'is_elite: False']\n", + "Id: 48_51 Identity: {'ancestor_count': 3, 'ancestor_ids': ['36_72', '1_1'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_51', 'origin': '36_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4008046126627391', 'NSGA-II_crowding_distance: 0.12580513344085337', 'NSGA-II_rank: 2', 'change: 0.06168523932300393', 'is_elite: False']\n", + "Id: 48_90 Identity: {'ancestor_count': 46, 'ancestor_ids': ['2_49', '47_42'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_90', 'origin': '2_49~CUW~47_42#MGNP'} Metrics: ['ELUC: -1.4625646605841258', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.22010180527132167', 'is_elite: False']\n", + "Id: 48_63 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '47_81'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_63', 'origin': '2_49~CUW~47_81#MGNP'} Metrics: ['ELUC: -1.5197828446113821', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.336271591870316', 'is_elite: False']\n", + "Id: 48_33 Identity: {'ancestor_count': 43, 'ancestor_ids': ['1_1', '47_61'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_33', 'origin': '1_1~CUW~47_61#MGNP'} Metrics: ['ELUC: -1.9092272222433186', 'NSGA-II_crowding_distance: 0.17246718589963697', 'NSGA-II_rank: 1', 'change: 0.04498481636779864', 'is_elite: False']\n", + "Id: 47_62 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_12'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_62', 'origin': '46_82~CUW~46_12#MGNP'} Metrics: ['ELUC: -1.9711709478009365', 'NSGA-II_crowding_distance: 0.13737438934367152', 'NSGA-II_rank: 2', 'change: 0.06821625777257528', 'is_elite: False']\n", + "Id: 48_52 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_43', '46_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_52', 'origin': '47_43~CUW~46_14#MGNP'} Metrics: ['ELUC: -2.4680024943730774', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.10796430151866622', 'is_elite: False']\n", + "Id: 48_14 Identity: {'ancestor_count': 46, 'ancestor_ids': ['36_72', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_14', 'origin': '36_72~CUW~47_62#MGNP'} Metrics: ['ELUC: -2.4704694193774923', 'NSGA-II_crowding_distance: 0.22329500136085262', 'NSGA-II_rank: 2', 'change: 0.0800414664622628', 'is_elite: False']\n", + "Id: 48_17 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_80', '2_49'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_17', 'origin': '47_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.52781849543345', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2584307284310937', 'is_elite: False']\n", + "Id: 48_21 Identity: {'ancestor_count': 43, 'ancestor_ids': ['47_95', '36_72'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_21', 'origin': '47_95~CUW~36_72#MGNP'} Metrics: ['ELUC: -2.652432801386815', 'NSGA-II_crowding_distance: 0.13422363280427746', 'NSGA-II_rank: 1', 'change: 0.052998548628708814', 'is_elite: False']\n", + "Id: 48_53 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_61', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_53', 'origin': '47_61~CUW~47_62#MGNP'} Metrics: ['ELUC: -2.747936545586301', 'NSGA-II_crowding_distance: 0.10189019515372544', 'NSGA-II_rank: 1', 'change: 0.07080100145838027', 'is_elite: False']\n", + "Id: 48_32 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '1_1'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_32', 'origin': '47_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.892181292424806', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09672232637713749', 'is_elite: False']\n", + "Id: 48_43 Identity: {'ancestor_count': 43, 'ancestor_ids': ['1_1', '47_95'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_43', 'origin': '1_1~CUW~47_95#MGNP'} Metrics: ['ELUC: -3.1964948653888565', 'NSGA-II_crowding_distance: 0.07129350235002617', 'NSGA-II_rank: 1', 'change: 0.07416741128712884', 'is_elite: False']\n", + "Id: 48_93 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_93', 'origin': '47_71~CUW~47_62#MGNP'} Metrics: ['ELUC: -3.4601681618351043', 'NSGA-II_crowding_distance: 0.2673101696400021', 'NSGA-II_rank: 4', 'change: 0.10836279016801868', 'is_elite: False']\n", + "Id: 47_81 Identity: {'ancestor_count': 4, 'ancestor_ids': ['46_12', '46_12'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_81', 'origin': '46_12~CUW~46_12#MGNP'} Metrics: ['ELUC: -3.6696209284653976', 'NSGA-II_crowding_distance: 0.13547384471366247', 'NSGA-II_rank: 1', 'change: 0.07643212572826882', 'is_elite: False']\n", + "Id: 48_49 Identity: {'ancestor_count': 46, 'ancestor_ids': ['36_72', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_49', 'origin': '36_72~CUW~47_71#MGNP'} Metrics: ['ELUC: -3.977943065611233', 'NSGA-II_crowding_distance: 0.22869348436259934', 'NSGA-II_rank: 4', 'change: 0.12226949409932285', 'is_elite: False']\n", + "Id: 48_19 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_60', '47_24'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_19', 'origin': '47_60~CUW~47_24#MGNP'} Metrics: ['ELUC: -4.074096836153961', 'NSGA-II_crowding_distance: 0.3521299556045414', 'NSGA-II_rank: 3', 'change: 0.0963019556467212', 'is_elite: False']\n", + "Id: 48_18 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_60', '47_43'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_18', 'origin': '47_60~CUW~47_43#MGNP'} Metrics: ['ELUC: -4.153817017971149', 'NSGA-II_crowding_distance: 0.09746807753734393', 'NSGA-II_rank: 3', 'change: 0.09819779772506476', 'is_elite: False']\n", + "Id: 48_28 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_60', '47_43'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_28', 'origin': '47_60~CUW~47_43#MGNP'} Metrics: ['ELUC: -4.220134630137661', 'NSGA-II_crowding_distance: 0.18132495882905858', 'NSGA-II_rank: 2', 'change: 0.09016886578979974', 'is_elite: False']\n", + "Id: 48_60 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_60', '47_61'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_60', 'origin': '47_60~CUW~47_61#MGNP'} Metrics: ['ELUC: -4.376499003886085', 'NSGA-II_crowding_distance: 0.4244764177907444', 'NSGA-II_rank: 5', 'change: 0.12478400705773551', 'is_elite: False']\n", + "Id: 48_47 Identity: {'ancestor_count': 43, 'ancestor_ids': ['47_61', '36_72'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_47', 'origin': '47_61~CUW~36_72#MGNP'} Metrics: ['ELUC: -4.390684488671986', 'NSGA-II_crowding_distance: 0.06784385359045272', 'NSGA-II_rank: 2', 'change: 0.09641607450518633', 'is_elite: False']\n", + "Id: 48_70 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_81', '47_90'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_70', 'origin': '47_81~CUW~47_90#MGNP'} Metrics: ['ELUC: -4.494972015378406', 'NSGA-II_crowding_distance: 1.0569368949323579', 'NSGA-II_rank: 8', 'change: 0.24846825107408257', 'is_elite: False']\n", + "Id: 48_31 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_14', '47_61'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_31', 'origin': '46_14~CUW~47_61#MGNP'} Metrics: ['ELUC: -4.541841948392124', 'NSGA-II_crowding_distance: 0.05802657962892881', 'NSGA-II_rank: 2', 'change: 0.1024258976100676', 'is_elite: False']\n", + "Id: 48_66 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_62', '47_24'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_66', 'origin': '47_62~CUW~47_24#MGNP'} Metrics: ['ELUC: -4.661237235582274', 'NSGA-II_crowding_distance: 0.1973551459035896', 'NSGA-II_rank: 1', 'change: 0.08973265802141134', 'is_elite: True']\n", + "Id: 48_61 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '36_72'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_61', 'origin': '47_71~CUW~36_72#MGNP'} Metrics: ['ELUC: -4.679679199750292', 'NSGA-II_crowding_distance: 0.25876545172126575', 'NSGA-II_rank: 3', 'change: 0.11141208638868284', 'is_elite: False']\n", + "Id: 48_45 Identity: {'ancestor_count': 5, 'ancestor_ids': ['47_43', '2_49'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_45', 'origin': '47_43~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.768862750402148', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2849939644976732', 'is_elite: False']\n", + "Id: 48_48 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_42', '47_61'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_48', 'origin': '47_42~CUW~47_61#MGNP'} Metrics: ['ELUC: -4.814788753472159', 'NSGA-II_crowding_distance: 0.5507992783564297', 'NSGA-II_rank: 4', 'change: 0.12440675715248703', 'is_elite: False']\n", + "Id: 48_89 Identity: {'ancestor_count': 43, 'ancestor_ids': ['47_61', '47_43'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_89', 'origin': '47_61~CUW~47_43#MGNP'} Metrics: ['ELUC: -4.853585172799042', 'NSGA-II_crowding_distance: 0.26279711976158304', 'NSGA-II_rank: 2', 'change: 0.10399854035871882', 'is_elite: False']\n", + "Id: 48_98 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '47_43'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_98', 'origin': '47_71~CUW~47_43#MGNP'} Metrics: ['ELUC: -5.451042836462468', 'NSGA-II_crowding_distance: 0.3484144728811319', 'NSGA-II_rank: 5', 'change: 0.13456095851851682', 'is_elite: False']\n", + "Id: 48_55 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_80', '2_49'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_55', 'origin': '47_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.587406670955896', 'NSGA-II_crowding_distance: 1.088761250569842', 'NSGA-II_rank: 8', 'change: 0.26821583059923987', 'is_elite: False']\n", + "Id: 47_61 Identity: {'ancestor_count': 42, 'ancestor_ids': ['36_72', '43_61'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_61', 'origin': '36_72~CUW~43_61#MGNP'} Metrics: ['ELUC: -6.033098771153534', 'NSGA-II_crowding_distance: 0.15775359911534048', 'NSGA-II_rank: 1', 'change: 0.09520955574441171', 'is_elite: False']\n", + "Id: 48_64 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_61', '47_42'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_64', 'origin': '47_61~CUW~47_42#MGNP'} Metrics: ['ELUC: -6.626887644541615', 'NSGA-II_crowding_distance: 0.13316915636028911', 'NSGA-II_rank: 1', 'change: 0.10344512316924791', 'is_elite: False']\n", + "Id: 48_79 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_80', '47_95'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_79', 'origin': '47_80~CUW~47_95#MGNP'} Metrics: ['ELUC: -6.662731415433178', 'NSGA-II_crowding_distance: 1.2284796262132631', 'NSGA-II_rank: 6', 'change: 0.17370978394356565', 'is_elite: False']\n", + "Id: 48_46 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_24', '47_52'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_46', 'origin': '47_24~CUW~47_52#MGNP'} Metrics: ['ELUC: -6.701189010965053', 'NSGA-II_crowding_distance: 0.3453694870700852', 'NSGA-II_rank: 3', 'change: 0.12242993552185978', 'is_elite: False']\n", + "Id: 48_39 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_52', '47_24'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_39', 'origin': '47_52~CUW~47_24#MGNP'} Metrics: ['ELUC: -7.129634693236048', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.21231408916541517', 'is_elite: False']\n", + "Id: 48_50 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_42', '47_81'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_50', 'origin': '47_42~CUW~47_81#MGNP'} Metrics: ['ELUC: -7.254445044464425', 'NSGA-II_crowding_distance: 0.42543805260522194', 'NSGA-II_rank: 5', 'change: 0.14017670728104611', 'is_elite: False']\n", + "Id: 48_12 Identity: {'ancestor_count': 43, 'ancestor_ids': ['47_81', '47_24'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_12', 'origin': '47_81~CUW~47_24#MGNP'} Metrics: ['ELUC: -7.381511205727811', 'NSGA-II_crowding_distance: 0.2682867437858424', 'NSGA-II_rank: 1', 'change: 0.11206128969207478', 'is_elite: True']\n", + "Id: 48_35 Identity: {'ancestor_count': 43, 'ancestor_ids': ['47_43', '47_95'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_35', 'origin': '47_43~CUW~47_95#MGNP'} Metrics: ['ELUC: -7.741868988476156', 'NSGA-II_crowding_distance: 0.3600700237118835', 'NSGA-II_rank: 2', 'change: 0.11971421122509009', 'is_elite: False']\n", + "Id: 48_29 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '36_72'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_29', 'origin': '47_28~CUW~36_72#MGNP'} Metrics: ['ELUC: -8.416988233803869', 'NSGA-II_crowding_distance: 0.8914699747877581', 'NSGA-II_rank: 6', 'change: 0.21198691970869582', 'is_elite: False']\n", + "Id: 48_57 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_57', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.756751948584649', 'NSGA-II_crowding_distance: 0.8369538479146632', 'NSGA-II_rank: 8', 'change: 0.29790719079662153', 'is_elite: False']\n", + "Id: 48_42 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '47_81'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_42', 'origin': '47_28~CUW~47_81#MGNP'} Metrics: ['ELUC: -9.006456205011615', 'NSGA-II_crowding_distance: 0.7455982218603707', 'NSGA-II_rank: 5', 'change: 0.15273818894661437', 'is_elite: False']\n", + "Id: 48_86 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_42', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_86', 'origin': '47_42~CUW~47_71#MGNP'} Metrics: ['ELUC: -9.259472340531786', 'NSGA-II_crowding_distance: 0.20443074128730002', 'NSGA-II_rank: 3', 'change: 0.12381000883526651', 'is_elite: False']\n", + "Id: 48_82 Identity: {'ancestor_count': 43, 'ancestor_ids': ['2_49', '47_61'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_82', 'origin': '2_49~CUW~47_61#MGNP'} Metrics: ['ELUC: -9.47282958737382', 'NSGA-II_crowding_distance: 0.2181673678833831', 'NSGA-II_rank: 8', 'change: 0.30029935291487214', 'is_elite: False']\n", + "Id: 48_23 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_81', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_23', 'origin': '47_81~CUW~47_71#MGNP'} Metrics: ['ELUC: -9.499376400641133', 'NSGA-II_crowding_distance: 1.1218906375010458', 'NSGA-II_rank: 4', 'change: 0.13006860653398772', 'is_elite: False']\n", + "Id: 48_54 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_62', '2_49'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_54', 'origin': '47_62~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.529908371477228', 'NSGA-II_crowding_distance: 0.7715203737867369', 'NSGA-II_rank: 6', 'change: 0.2785403471422614', 'is_elite: False']\n", + "Id: 48_95 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_61', '46_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_95', 'origin': '47_61~CUW~46_14#MGNP'} Metrics: ['ELUC: -9.666608894262293', 'NSGA-II_crowding_distance: 0.2482517654026718', 'NSGA-II_rank: 3', 'change: 0.12546555543824228', 'is_elite: False']\n", + "Id: 48_40 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_61', '46_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_40', 'origin': '47_61~CUW~46_14#MGNP'} Metrics: ['ELUC: -9.683133431704839', 'NSGA-II_crowding_distance: 0.16825984187593931', 'NSGA-II_rank: 2', 'change: 0.12080942053170404', 'is_elite: False']\n", + "Id: 48_38 Identity: {'ancestor_count': 46, 'ancestor_ids': ['2_49', '47_42'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_38', 'origin': '2_49~CUW~47_42#MGNP'} Metrics: ['ELUC: -9.686826154314907', 'NSGA-II_crowding_distance: 1.4963635843839147', 'NSGA-II_rank: 7', 'change: 0.28361608603369953', 'is_elite: False']\n", + "Id: 48_24 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_24', 'origin': '47_28~CUW~47_62#MGNP'} Metrics: ['ELUC: -9.802101065859404', 'NSGA-II_crowding_distance: 0.8390885473214682', 'NSGA-II_rank: 5', 'change: 0.22725382130731453', 'is_elite: False']\n", + "Id: 48_80 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_62', '46_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_80', 'origin': '47_62~CUW~46_14#MGNP'} Metrics: ['ELUC: -9.894139949756822', 'NSGA-II_crowding_distance: 0.2126617230209111', 'NSGA-II_rank: 2', 'change: 0.12918556728515554', 'is_elite: False']\n", + "Id: 48_37 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_52', '47_90'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_37', 'origin': '47_52~CUW~47_90#MGNP'} Metrics: ['ELUC: -9.97394707059871', 'NSGA-II_crowding_distance: 0.6074548367866859', 'NSGA-II_rank: 7', 'change: 0.2873467525110944', 'is_elite: False']\n", + "Id: 48_11 Identity: {'ancestor_count': 45, 'ancestor_ids': ['36_72', '47_90'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_11', 'origin': '36_72~CUW~47_90#MGNP'} Metrics: ['ELUC: -10.049483647087673', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.30355002087605376', 'is_elite: False']\n", + "Id: 48_77 Identity: {'ancestor_count': 46, 'ancestor_ids': ['1_1', '47_28'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_77', 'origin': '1_1~CUW~47_28#MGNP'} Metrics: ['ELUC: -10.458324146540328', 'NSGA-II_crowding_distance: 0.9962466095689766', 'NSGA-II_rank: 4', 'change: 0.2167906489263665', 'is_elite: False']\n", + "Id: 48_91 Identity: {'ancestor_count': 46, 'ancestor_ids': ['46_14', '47_42'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_91', 'origin': '46_14~CUW~47_42#MGNP'} Metrics: ['ELUC: -10.478688532030786', 'NSGA-II_crowding_distance: 0.23058770729328243', 'NSGA-II_rank: 1', 'change: 0.11812966051473663', 'is_elite: True']\n", + "Id: 48_87 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '47_43'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_87', 'origin': '47_28~CUW~47_43#MGNP'} Metrics: ['ELUC: -10.547129120641236', 'NSGA-II_crowding_distance: 0.24361028817634783', 'NSGA-II_rank: 3', 'change: 0.16660212053590992', 'is_elite: False']\n", + "Id: 48_83 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_61', '47_58'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_83', 'origin': '47_61~CUW~47_58#MGNP'} Metrics: ['ELUC: -10.779446159008756', 'NSGA-II_crowding_distance: 0.5059426358007426', 'NSGA-II_rank: 3', 'change: 0.17000576847963778', 'is_elite: False']\n", + "Id: 46_14 Identity: {'ancestor_count': 44, 'ancestor_ids': ['45_25', '45_50'], 'birth_generation': 46, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '46_14', 'origin': '45_25~CUW~45_50#MGNP'} Metrics: ['ELUC: -10.835497310177685', 'NSGA-II_crowding_distance: 0.07736415387971127', 'NSGA-II_rank: 1', 'change: 0.12224831415675627', 'is_elite: False']\n", + "Id: 48_67 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_90', '46_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_67', 'origin': '47_90~CUW~46_14#MGNP'} Metrics: ['ELUC: -10.93547218797624', 'NSGA-II_crowding_distance: 0.635583533556156', 'NSGA-II_rank: 5', 'change: 0.26479768292737926', 'is_elite: False']\n", + "Id: 48_73 Identity: {'ancestor_count': 46, 'ancestor_ids': ['46_14', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_73', 'origin': '46_14~CUW~47_71#MGNP'} Metrics: ['ELUC: -11.040527754653919', 'NSGA-II_crowding_distance: 0.06579440800514547', 'NSGA-II_rank: 1', 'change: 0.13167881517505534', 'is_elite: False']\n", + "Id: 48_85 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_95', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_85', 'origin': '47_95~CUW~47_71#MGNP'} Metrics: ['ELUC: -11.188962671062894', 'NSGA-II_crowding_distance: 0.21662310152602432', 'NSGA-II_rank: 2', 'change: 0.15154431309560865', 'is_elite: False']\n", + "Id: 48_58 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_60', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_58', 'origin': '47_60~CUW~47_71#MGNP'} Metrics: ['ELUC: -11.353524979839301', 'NSGA-II_crowding_distance: 0.18826521555658826', 'NSGA-II_rank: 2', 'change: 0.16164401351100893', 'is_elite: False']\n", + "Id: 48_44 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_80', '1_1'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_44', 'origin': '47_80~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.36627911354872', 'NSGA-II_crowding_distance: 0.4704872199558291', 'NSGA-II_rank: 2', 'change: 0.19661142946107418', 'is_elite: False']\n", + "Id: 48_78 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '46_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_78', 'origin': '47_71~CUW~46_14#MGNP'} Metrics: ['ELUC: -11.36715621239843', 'NSGA-II_crowding_distance: 0.09463355479105952', 'NSGA-II_rank: 1', 'change: 0.13285748382498075', 'is_elite: False']\n", + "Id: 48_56 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '46_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_56', 'origin': '47_71~CUW~46_14#MGNP'} Metrics: ['ELUC: -11.775183451662624', 'NSGA-II_crowding_distance: 0.12326282791446874', 'NSGA-II_rank: 1', 'change: 0.14744802538108676', 'is_elite: False']\n", + "Id: 48_15 Identity: {'ancestor_count': 45, 'ancestor_ids': ['1_1', '47_90'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_15', 'origin': '1_1~CUW~47_90#MGNP'} Metrics: ['ELUC: -12.08232447473486', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29368849687156307', 'is_elite: False']\n", + "Id: 48_26 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_80', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_26', 'origin': '47_80~CUW~47_62#MGNP'} Metrics: ['ELUC: -12.10727334812429', 'NSGA-II_crowding_distance: 0.5209937274311744', 'NSGA-II_rank: 4', 'change: 0.24492423649428283', 'is_elite: False']\n", + "Id: 48_92 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '47_71'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_92', 'origin': '47_71~CUW~47_71#MGNP'} Metrics: ['ELUC: -12.41728627726866', 'NSGA-II_crowding_distance: 0.07079679070249337', 'NSGA-II_rank: 1', 'change: 0.15181533386806484', 'is_elite: False']\n", + "Id: 47_71 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_71', 'origin': '46_82~CUW~46_82#MGNP'} Metrics: ['ELUC: -12.588030833841653', 'NSGA-II_crowding_distance: 0.3598192180789327', 'NSGA-II_rank: 1', 'change: 0.15477793940682558', 'is_elite: True']\n", + "Id: 48_62 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_90', '36_72'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_62', 'origin': '47_90~CUW~36_72#MGNP'} Metrics: ['ELUC: -12.809550846887854', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2794688313640283', 'is_elite: False']\n", + "Id: 48_94 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_42', '2_49'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_94', 'origin': '47_42~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.674988610231113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.275979025545051', 'is_elite: False']\n", + "Id: 48_27 Identity: {'ancestor_count': 46, 'ancestor_ids': ['36_72', '47_52'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_27', 'origin': '36_72~CUW~47_52#MGNP'} Metrics: ['ELUC: -13.86188587284659', 'NSGA-II_crowding_distance: 0.5345182208655878', 'NSGA-II_rank: 3', 'change: 0.2421415425578931', 'is_elite: False']\n", + "Id: 48_84 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_62', '47_52'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_84', 'origin': '47_62~CUW~47_52#MGNP'} Metrics: ['ELUC: -13.953635945076206', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.24775232392823215', 'is_elite: False']\n", + "Id: 48_59 Identity: {'ancestor_count': 46, 'ancestor_ids': ['36_72', '47_80'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_59', 'origin': '36_72~CUW~47_80#MGNP'} Metrics: ['ELUC: -14.46865614026115', 'NSGA-II_crowding_distance: 0.2996807649933155', 'NSGA-II_rank: 3', 'change: 0.24664663022535793', 'is_elite: False']\n", + "Id: 48_20 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '47_42'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_20', 'origin': '47_28~CUW~47_42#MGNP'} Metrics: ['ELUC: -14.529289378758577', 'NSGA-II_crowding_distance: 0.5779511296814603', 'NSGA-II_rank: 2', 'change: 0.23204674730135424', 'is_elite: False']\n", + "Id: 48_100 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '47_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_100', 'origin': '47_28~CUW~47_14#MGNP'} Metrics: ['ELUC: -14.792601254512524', 'NSGA-II_crowding_distance: 0.403117673596949', 'NSGA-II_rank: 1', 'change: 0.21886754258634622', 'is_elite: True']\n", + "Id: 48_75 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_90', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_75', 'origin': '47_90~CUW~47_62#MGNP'} Metrics: ['ELUC: -15.200755304885096', 'NSGA-II_crowding_distance: 0.3538522550521598', 'NSGA-II_rank: 2', 'change: 0.28412488991911206', 'is_elite: False']\n", + "Id: 48_41 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '47_28'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_41', 'origin': '47_71~CUW~47_28#MGNP'} Metrics: ['ELUC: -15.285347924936387', 'NSGA-II_crowding_distance: 0.1512941554043136', 'NSGA-II_rank: 1', 'change: 0.22928496721569938', 'is_elite: False']\n", + "Id: 48_34 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_62', '47_80'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_34', 'origin': '47_62~CUW~47_80#MGNP'} Metrics: ['ELUC: -15.2993869093206', 'NSGA-II_crowding_distance: 0.24313228299213518', 'NSGA-II_rank: 1', 'change: 0.25541003813671254', 'is_elite: True']\n", + "Id: 48_22 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_22', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.381209721771183', 'NSGA-II_crowding_distance: 0.4065453423449571', 'NSGA-II_rank: 3', 'change: 0.29439182528211594', 'is_elite: False']\n", + "Id: 48_65 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_90', '2_49'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_65', 'origin': '47_90~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.219058277628044', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.32278120304940233', 'is_elite: False']\n", + "Id: 48_69 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_90', '47_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_69', 'origin': '47_90~CUW~47_14#MGNP'} Metrics: ['ELUC: -16.598312985140467', 'NSGA-II_crowding_distance: 0.21894585638909297', 'NSGA-II_rank: 2', 'change: 0.28993256829089137', 'is_elite: False']\n", + "Id: 48_30 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '47_52'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_30', 'origin': '47_71~CUW~47_52#MGNP'} Metrics: ['ELUC: -16.7411889017413', 'NSGA-II_crowding_distance: 0.2811532440183174', 'NSGA-II_rank: 1', 'change: 0.27712415208538177', 'is_elite: True']\n", + "Id: 48_74 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_90', '46_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_74', 'origin': '47_90~CUW~46_14#MGNP'} Metrics: ['ELUC: -17.536986141768054', 'NSGA-II_crowding_distance: 0.13340987265572318', 'NSGA-II_rank: 1', 'change: 0.3013271519446376', 'is_elite: False']\n", + "Id: 48_72 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '47_90'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_72', 'origin': '47_28~CUW~47_90#MGNP'} Metrics: ['ELUC: -17.57133473436918', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030939752704111', 'is_elite: False']\n", + "Id: 48_71 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_90', '47_28'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_71', 'origin': '47_90~CUW~47_28#MGNP'} Metrics: ['ELUC: -17.581732703803702', 'NSGA-II_crowding_distance: 0.00901324439412722', 'NSGA-II_rank: 1', 'change: 0.3026663976135942', 'is_elite: False']\n", + "Id: 48_68 Identity: {'ancestor_count': 46, 'ancestor_ids': ['2_49', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_68', 'origin': '2_49~CUW~47_62#MGNP'} Metrics: ['ELUC: -17.596242108788147', 'NSGA-II_crowding_distance: 0.0020577583432163623', 'NSGA-II_rank: 1', 'change: 0.3030109111849263', 'is_elite: False']\n", + "Id: 48_96 Identity: {'ancestor_count': 45, 'ancestor_ids': ['47_24', '47_90'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_96', 'origin': '47_24~CUW~47_90#MGNP'} Metrics: ['ELUC: -17.597169860725163', 'NSGA-II_crowding_distance: 9.711636586549435e-05', 'NSGA-II_rank: 1', 'change: 0.30301841353458214', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 47_90 Identity: {'ancestor_count': 44, 'ancestor_ids': ['2_49', '46_41'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_90', 'origin': '2_49~CUW~46_41#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 48_13 Identity: {'ancestor_count': 46, 'ancestor_ids': ['2_49', '47_52'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_13', 'origin': '2_49~CUW~47_52#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 48_36 Identity: {'ancestor_count': 46, 'ancestor_ids': ['2_49', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_36', 'origin': '2_49~CUW~47_62#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 48.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 49...:\n", + "PopulationResponse:\n", + " Generation: 49\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/49/20240220-013347\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 49 and asking ESP for generation 50...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 49 data persisted.\n", + "Evaluated candidates:\n", + "Id: 49_80 Identity: {'ancestor_count': 44, 'ancestor_ids': ['2_49', '48_12'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_80', 'origin': '2_49~CUW~48_12#MGNP'} Metrics: ['ELUC: 22.02819993526842', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2948096579611956', 'is_elite: False']\n", + "Id: 49_66 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '48_91'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_66', 'origin': '48_36~CUW~48_91#MGNP'} Metrics: ['ELUC: 17.816295576153088', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27077127096249104', 'is_elite: False']\n", + "Id: 49_47 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '2_49'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_47', 'origin': '47_71~CUW~2_49#MGNP'} Metrics: ['ELUC: 13.713346389565144', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2934857438837233', 'is_elite: False']\n", + "Id: 49_40 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_12', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_40', 'origin': '48_12~CUW~48_36#MGNP'} Metrics: ['ELUC: 9.431267516683539', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2602763385539144', 'is_elite: False']\n", + "Id: 49_65 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_21', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_65', 'origin': '48_21~CUW~48_36#MGNP'} Metrics: ['ELUC: 8.488387061512325', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25482651029683584', 'is_elite: False']\n", + "Id: 49_100 Identity: {'ancestor_count': 43, 'ancestor_ids': ['2_49', '47_61'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_100', 'origin': '2_49~CUW~47_61#MGNP'} Metrics: ['ELUC: 5.339243630325403', 'NSGA-II_crowding_distance: 0.9036620269502387', 'NSGA-II_rank: 9', 'change: 0.2591042536365209', 'is_elite: False']\n", + "Id: 49_87 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_87', 'origin': '2_49~CUW~48_100#MGNP'} Metrics: ['ELUC: 5.064113073117383', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.2649667566980752', 'is_elite: False']\n", + "Id: 49_79 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_66', '2_49'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_79', 'origin': '48_66~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.743493691514092', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.235260740553593', 'is_elite: False']\n", + "Id: 49_93 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_93', 'origin': '48_91~CUW~1_1#MGNP'} Metrics: ['ELUC: 3.9350783729261836', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0843128811575912', 'is_elite: False']\n", + "Id: 49_22 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_66'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_22', 'origin': '2_49~CUW~48_66#MGNP'} Metrics: ['ELUC: 3.5878427155370707', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3049919408687795', 'is_elite: False']\n", + "Id: 49_91 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_66', '2_49'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_91', 'origin': '48_66~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.28374357079051', 'NSGA-II_crowding_distance: 1.5517692555913636', 'NSGA-II_rank: 9', 'change: 0.26371784111530117', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 49_28 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_28', 'origin': '2_49~CUW~48_36#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.6970411864984674', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 49_11 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_30', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_11', 'origin': '48_30~CUW~48_36#MGNP'} Metrics: ['ELUC: -0.6169371898327836', 'NSGA-II_crowding_distance: 0.9592752536194735', 'NSGA-II_rank: 8', 'change: 0.2390359612562667', 'is_elite: False']\n", + "Id: 49_71 Identity: {'ancestor_count': 46, 'ancestor_ids': ['48_88', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_71', 'origin': '48_88~CUW~47_71#MGNP'} Metrics: ['ELUC: -0.6182476626518175', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10935660520041501', 'is_elite: False']\n", + "Id: 49_63 Identity: {'ancestor_count': 43, 'ancestor_ids': ['47_61', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_63', 'origin': '47_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9906048229866278', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.10048695445327852', 'is_elite: False']\n", + "Id: 49_18 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_18', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.0652539250109134', 'NSGA-II_crowding_distance: 0.18438584697236177', 'NSGA-II_rank: 1', 'change: 0.03555034540236855', 'is_elite: False']\n", + "Id: 49_85 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_85', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1175026563574462', 'NSGA-II_crowding_distance: 0.11649798148182233', 'NSGA-II_rank: 1', 'change: 0.04095037410621707', 'is_elite: False']\n", + "Id: 49_99 Identity: {'ancestor_count': 44, 'ancestor_ids': ['48_12', '48_88'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_99', 'origin': '48_12~CUW~48_88#MGNP'} Metrics: ['ELUC: -1.508487321654485', 'NSGA-II_crowding_distance: 0.4849488713080279', 'NSGA-II_rank: 5', 'change: 0.10340160799707991', 'is_elite: False']\n", + "Id: 49_17 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_41', '48_21'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_17', 'origin': '48_41~CUW~48_21#MGNP'} Metrics: ['ELUC: -1.7060793409147592', 'NSGA-II_crowding_distance: 0.4217123368196395', 'NSGA-II_rank: 3', 'change: 0.08648340486217533', 'is_elite: False']\n", + "Id: 49_52 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_52', 'origin': '48_36~CUW~48_100#MGNP'} Metrics: ['ELUC: -1.901383119890741', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.20282862880902555', 'is_elite: False']\n", + "Id: 49_35 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_64', '48_74'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_35', 'origin': '48_64~CUW~48_74#MGNP'} Metrics: ['ELUC: -2.1095812768490347', 'NSGA-II_crowding_distance: 0.5975667787442718', 'NSGA-II_rank: 5', 'change: 0.17109043776931607', 'is_elite: False']\n", + "Id: 49_72 Identity: {'ancestor_count': 44, 'ancestor_ids': ['48_33', '47_61'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_72', 'origin': '48_33~CUW~47_61#MGNP'} Metrics: ['ELUC: -2.3030656944177794', 'NSGA-II_crowding_distance: 0.12741179552284987', 'NSGA-II_rank: 1', 'change: 0.049304699665344724', 'is_elite: False']\n", + "Id: 49_84 Identity: {'ancestor_count': 43, 'ancestor_ids': ['47_61', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_84', 'origin': '47_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.4656025895776086', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.07930798480925988', 'is_elite: False']\n", + "Id: 49_59 Identity: {'ancestor_count': 44, 'ancestor_ids': ['48_21', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_59', 'origin': '48_21~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.4662785601721766', 'NSGA-II_crowding_distance: 0.2317252553617255', 'NSGA-II_rank: 1', 'change: 0.05607807170136564', 'is_elite: False']\n", + "Id: 49_24 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_66', '48_34'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_24', 'origin': '48_66~CUW~48_34#MGNP'} Metrics: ['ELUC: -2.561594031600294', 'NSGA-II_crowding_distance: 0.11497226586293977', 'NSGA-II_rank: 2', 'change: 0.08044716950532292', 'is_elite: False']\n", + "Id: 49_25 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_66'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_25', 'origin': '48_91~CUW~48_66#MGNP'} Metrics: ['ELUC: -2.6662207452942863', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.10044858257964726', 'is_elite: False']\n", + "Id: 49_58 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '48_66'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_58', 'origin': '1_1~CUW~48_66#MGNP'} Metrics: ['ELUC: -2.8285629564587578', 'NSGA-II_crowding_distance: 0.22281607193545336', 'NSGA-II_rank: 3', 'change: 0.09690634941522837', 'is_elite: False']\n", + "Id: 49_67 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_34', '48_21'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_67', 'origin': '48_34~CUW~48_21#MGNP'} Metrics: ['ELUC: -3.001093457905959', 'NSGA-II_crowding_distance: 0.4388372440168231', 'NSGA-II_rank: 4', 'change: 0.11442465617937991', 'is_elite: False']\n", + "Id: 49_62 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_30', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_62', 'origin': '48_30~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.554777583170682', 'NSGA-II_crowding_distance: 0.49866586415444075', 'NSGA-II_rank: 5', 'change: 0.18001775720850005', 'is_elite: False']\n", + "Id: 49_20 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_20', 'origin': '48_91~CUW~48_36#MGNP'} Metrics: ['ELUC: -3.5755938958198983', 'NSGA-II_crowding_distance: 1.0384195642786205', 'NSGA-II_rank: 7', 'change: 0.20451335862858386', 'is_elite: False']\n", + "Id: 49_44 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_44', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.69034554293036', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27738208623462457', 'is_elite: False']\n", + "Id: 49_21 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_21', 'origin': '48_36~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.7875526496101917', 'NSGA-II_crowding_distance: 1.3029588135015326', 'NSGA-II_rank: 8', 'change: 0.26494844426085334', 'is_elite: False']\n", + "Id: 49_81 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_66', '48_21'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_81', 'origin': '48_66~CUW~48_21#MGNP'} Metrics: ['ELUC: -3.9203589296349683', 'NSGA-II_crowding_distance: 0.20546838926425293', 'NSGA-II_rank: 2', 'change: 0.0831212630098087', 'is_elite: False']\n", + "Id: 49_14 Identity: {'ancestor_count': 44, 'ancestor_ids': ['1_1', '48_12'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_14', 'origin': '1_1~CUW~48_12#MGNP'} Metrics: ['ELUC: -3.998416667139558', 'NSGA-II_crowding_distance: 0.1966866672162053', 'NSGA-II_rank: 3', 'change: 0.10636161556399182', 'is_elite: False']\n", + "Id: 49_97 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '48_91'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_97', 'origin': '48_36~CUW~48_91#MGNP'} Metrics: ['ELUC: -4.015987016274696', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2796314742608959', 'is_elite: False']\n", + "Id: 49_29 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_100', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_29', 'origin': '48_100~CUW~48_36#MGNP'} Metrics: ['ELUC: -4.244416856001512', 'NSGA-II_crowding_distance: 1.1322721522794423', 'NSGA-II_rank: 7', 'change: 0.2546687668052957', 'is_elite: False']\n", + "Id: 49_77 Identity: {'ancestor_count': 46, 'ancestor_ids': ['48_33', '48_74'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_77', 'origin': '48_33~CUW~48_74#MGNP'} Metrics: ['ELUC: -4.589905593304371', 'NSGA-II_crowding_distance: 0.3820675274099704', 'NSGA-II_rank: 4', 'change: 0.14438071941615566', 'is_elite: False']\n", + "Id: 49_13 Identity: {'ancestor_count': 46, 'ancestor_ids': ['1_1', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_13', 'origin': '1_1~CUW~47_71#MGNP'} Metrics: ['ELUC: -4.620414695037546', 'NSGA-II_crowding_distance: 0.23763072120340215', 'NSGA-II_rank: 1', 'change: 0.07912022504967431', 'is_elite: True']\n", + "Id: 48_66 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_62', '47_24'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_66', 'origin': '47_62~CUW~47_24#MGNP'} Metrics: ['ELUC: -4.661237235582274', 'NSGA-II_crowding_distance: 0.11447538059907356', 'NSGA-II_rank: 1', 'change: 0.08973265802141134', 'is_elite: False']\n", + "Id: 49_36 Identity: {'ancestor_count': 43, 'ancestor_ids': ['1_1', '47_61'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_36', 'origin': '1_1~CUW~47_61#MGNP'} Metrics: ['ELUC: -4.682766039045246', 'NSGA-II_crowding_distance: 0.2692967472532118', 'NSGA-II_rank: 2', 'change: 0.09441507527402798', 'is_elite: False']\n", + "Id: 49_88 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_41', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_88', 'origin': '48_41~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.089490722796759', 'NSGA-II_crowding_distance: 0.2110772614686646', 'NSGA-II_rank: 3', 'change: 0.11200315080438518', 'is_elite: False']\n", + "Id: 49_51 Identity: {'ancestor_count': 46, 'ancestor_ids': ['48_74', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_51', 'origin': '48_74~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.097126136329205', 'NSGA-II_crowding_distance: 1.2784060139383004', 'NSGA-II_rank: 6', 'change: 0.188805697963128', 'is_elite: False']\n", + "Id: 49_37 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_33', '48_30'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_37', 'origin': '48_33~CUW~48_30#MGNP'} Metrics: ['ELUC: -5.111974621542592', 'NSGA-II_crowding_distance: 0.6076818842999401', 'NSGA-II_rank: 4', 'change: 0.14532308053147783', 'is_elite: False']\n", + "Id: 49_33 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_33', '48_66'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_33', 'origin': '48_33~CUW~48_66#MGNP'} Metrics: ['ELUC: -5.8465534007842805', 'NSGA-II_crowding_distance: 0.2354838455201964', 'NSGA-II_rank: 1', 'change: 0.09246917577174277', 'is_elite: True']\n", + "Id: 49_19 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_66', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_19', 'origin': '48_66~CUW~48_36#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.9615804357213794', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 49_45 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_45', 'origin': '48_36~CUW~47_71#MGNP'} Metrics: ['ELUC: -6.076441042648916', 'NSGA-II_crowding_distance: 1.0800651237545995', 'NSGA-II_rank: 6', 'change: 0.25845243042926414', 'is_elite: False']\n", + "Id: 49_43 Identity: {'ancestor_count': 46, 'ancestor_ids': ['48_33', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_43', 'origin': '48_33~CUW~47_71#MGNP'} Metrics: ['ELUC: -6.434446995805381', 'NSGA-II_crowding_distance: 0.2608528745612192', 'NSGA-II_rank: 2', 'change: 0.10540388707542926', 'is_elite: False']\n", + "Id: 49_31 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '2_49'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_31', 'origin': '48_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.525178664321204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.30033009817205947', 'is_elite: False']\n", + "Id: 49_30 Identity: {'ancestor_count': 44, 'ancestor_ids': ['48_12', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_30', 'origin': '48_12~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.730964473253864', 'NSGA-II_crowding_distance: 0.16538678206345964', 'NSGA-II_rank: 3', 'change: 0.11940269496044886', 'is_elite: False']\n", + "Id: 49_15 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_33', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_15', 'origin': '48_33~CUW~48_100#MGNP'} Metrics: ['ELUC: -6.938021622723658', 'NSGA-II_crowding_distance: 0.40689377906289886', 'NSGA-II_rank: 5', 'change: 0.18647699815876242', 'is_elite: False']\n", + "Id: 49_70 Identity: {'ancestor_count': 44, 'ancestor_ids': ['47_61', '48_12'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_70', 'origin': '47_61~CUW~48_12#MGNP'} Metrics: ['ELUC: -6.9821179431061555', 'NSGA-II_crowding_distance: 0.14820762382427846', 'NSGA-II_rank: 3', 'change: 0.1247853019892874', 'is_elite: False']\n", + "Id: 49_98 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_30', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_98', 'origin': '48_30~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.9918664270694295', 'NSGA-II_crowding_distance: 0.15035706602920929', 'NSGA-II_rank: 3', 'change: 0.14566913809967338', 'is_elite: False']\n", + "Id: 49_50 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '48_30'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_50', 'origin': '1_1~CUW~48_30#MGNP'} Metrics: ['ELUC: -7.3231819659221555', 'NSGA-II_crowding_distance: 0.5945420173243923', 'NSGA-II_rank: 5', 'change: 0.19523954705875773', 'is_elite: False']\n", + "Id: 48_12 Identity: {'ancestor_count': 43, 'ancestor_ids': ['47_81', '47_24'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_12', 'origin': '47_81~CUW~47_24#MGNP'} Metrics: ['ELUC: -7.381511205727811', 'NSGA-II_crowding_distance: 0.27284608643554636', 'NSGA-II_rank: 2', 'change: 0.11206128969207478', 'is_elite: False']\n", + "Id: 49_64 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_100', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_64', 'origin': '48_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.4142089931282005', 'NSGA-II_crowding_distance: 0.15161323425707174', 'NSGA-II_rank: 3', 'change: 0.14970489555766953', 'is_elite: False']\n", + "Id: 49_34 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_41', '48_88'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_34', 'origin': '48_41~CUW~48_88#MGNP'} Metrics: ['ELUC: -7.945641163428854', 'NSGA-II_crowding_distance: 0.34945386459073974', 'NSGA-II_rank: 1', 'change: 0.10425844281622342', 'is_elite: True']\n", + "Id: 49_86 Identity: {'ancestor_count': 47, 'ancestor_ids': ['47_71', '48_66'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_86', 'origin': '47_71~CUW~48_66#MGNP'} Metrics: ['ELUC: -8.25179288191266', 'NSGA-II_crowding_distance: 0.3871518509993108', 'NSGA-II_rank: 2', 'change: 0.13888799671533886', 'is_elite: False']\n", + "Id: 49_42 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_30', '48_64'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_42', 'origin': '48_30~CUW~48_64#MGNP'} Metrics: ['ELUC: -8.386898972655105', 'NSGA-II_crowding_distance: 0.8447404208134605', 'NSGA-II_rank: 4', 'change: 0.18611435733600534', 'is_elite: False']\n", + "Id: 49_94 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_64', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_94', 'origin': '48_64~CUW~48_100#MGNP'} Metrics: ['ELUC: -9.224341029749878', 'NSGA-II_crowding_distance: 0.23681999831448014', 'NSGA-II_rank: 3', 'change: 0.1522524253883248', 'is_elite: False']\n", + "Id: 49_41 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_100', '48_91'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_41', 'origin': '48_100~CUW~48_91#MGNP'} Metrics: ['ELUC: -9.455127289027475', 'NSGA-II_crowding_distance: 0.6377386747238893', 'NSGA-II_rank: 4', 'change: 0.2190993306177414', 'is_elite: False']\n", + "Id: 49_12 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_12', 'origin': '48_91~CUW~48_36#MGNP'} Metrics: ['ELUC: -10.194919838790721', 'NSGA-II_crowding_distance: 0.7078660260582073', 'NSGA-II_rank: 5', 'change: 0.2437113522707296', 'is_elite: False']\n", + "Id: 49_68 Identity: {'ancestor_count': 47, 'ancestor_ids': ['47_71', '48_91'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_68', 'origin': '47_71~CUW~48_91#MGNP'} Metrics: ['ELUC: -10.336531873215481', 'NSGA-II_crowding_distance: 0.454408270138159', 'NSGA-II_rank: 3', 'change: 0.165817340508942', 'is_elite: False']\n", + "Id: 48_91 Identity: {'ancestor_count': 46, 'ancestor_ids': ['46_14', '47_42'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_91', 'origin': '46_14~CUW~47_42#MGNP'} Metrics: ['ELUC: -10.478688532030786', 'NSGA-II_crowding_distance: 0.31656137996328537', 'NSGA-II_rank: 1', 'change: 0.11812966051473663', 'is_elite: True']\n", + "Id: 49_16 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_74', '48_30'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_16', 'origin': '48_74~CUW~48_30#MGNP'} Metrics: ['ELUC: -10.942611446462138', 'NSGA-II_crowding_distance: 0.4115120268028981', 'NSGA-II_rank: 3', 'change: 0.22330782405184985', 'is_elite: False']\n", + "Id: 49_60 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_12'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_60', 'origin': '48_91~CUW~48_12#MGNP'} Metrics: ['ELUC: -11.04843732453195', 'NSGA-II_crowding_distance: 0.37605693014585884', 'NSGA-II_rank: 2', 'change: 0.14331001757176492', 'is_elite: False']\n", + "Id: 49_26 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_34', '48_56'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_26', 'origin': '48_34~CUW~48_56#MGNP'} Metrics: ['ELUC: -11.294082923389096', 'NSGA-II_crowding_distance: 0.29017402964388256', 'NSGA-II_rank: 2', 'change: 0.17700571930629944', 'is_elite: False']\n", + "Id: 49_96 Identity: {'ancestor_count': 46, 'ancestor_ids': ['48_12', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_96', 'origin': '48_12~CUW~47_71#MGNP'} Metrics: ['ELUC: -11.34285255212047', 'NSGA-II_crowding_distance: 0.24279449937326414', 'NSGA-II_rank: 1', 'change: 0.14106157965097307', 'is_elite: True']\n", + "Id: 49_74 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_74', 'origin': '1_1~CUW~48_36#MGNP'} Metrics: ['ELUC: -11.726974477035805', 'NSGA-II_crowding_distance: 0.2952141091023487', 'NSGA-II_rank: 5', 'change: 0.25519880550734925', 'is_elite: False']\n", + "Id: 49_75 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_88', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_75', 'origin': '48_88~CUW~48_36#MGNP'} Metrics: ['ELUC: -11.761791765981538', 'NSGA-II_crowding_distance: 0.2272215147707462', 'NSGA-II_rank: 5', 'change: 0.272913159904409', 'is_elite: False']\n", + "Id: 49_56 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_30', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_56', 'origin': '48_30~CUW~48_36#MGNP'} Metrics: ['ELUC: -11.774797722446444', 'NSGA-II_crowding_distance: 0.7215939860616996', 'NSGA-II_rank: 6', 'change: 0.2831573018004749', 'is_elite: False']\n", + "Id: 49_57 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_74'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_57', 'origin': '48_91~CUW~48_74#MGNP'} Metrics: ['ELUC: -12.245633772263638', 'NSGA-II_crowding_distance: 0.6604304250295828', 'NSGA-II_rank: 4', 'change: 0.23203723195637282', 'is_elite: False']\n", + "Id: 49_89 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_34', '48_41'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_89', 'origin': '48_34~CUW~48_41#MGNP'} Metrics: ['ELUC: -12.30019419378225', 'NSGA-II_crowding_distance: 0.4235783704870941', 'NSGA-II_rank: 2', 'change: 0.18909805289903628', 'is_elite: False']\n", + "Id: 49_48 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_100', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_48', 'origin': '48_100~CUW~47_71#MGNP'} Metrics: ['ELUC: -12.326220131203577', 'NSGA-II_crowding_distance: 0.32680439527534355', 'NSGA-II_rank: 3', 'change: 0.22568967139267948', 'is_elite: False']\n", + "Id: 49_73 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '48_88'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_73', 'origin': '2_49~CUW~48_88#MGNP'} Metrics: ['ELUC: -12.510886088801747', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29130273450640176', 'is_elite: False']\n", + "Id: 47_71 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_71', 'origin': '46_82~CUW~46_82#MGNP'} Metrics: ['ELUC: -12.588030833841653', 'NSGA-II_crowding_distance: 0.3036904111949445', 'NSGA-II_rank: 1', 'change: 0.15477793940682558', 'is_elite: True']\n", + "Id: 49_55 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_55', 'origin': '2_49~CUW~48_100#MGNP'} Metrics: ['ELUC: -12.656763407153496', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28197178315664423', 'is_elite: False']\n", + "Id: 49_32 Identity: {'ancestor_count': 44, 'ancestor_ids': ['2_49', '48_12'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_32', 'origin': '2_49~CUW~48_12#MGNP'} Metrics: ['ELUC: -12.988651864414507', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2744526970312711', 'is_elite: False']\n", + "Id: 49_39 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_64', '2_49'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_39', 'origin': '48_64~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.179948453598186', 'NSGA-II_crowding_distance: 0.4175251227541079', 'NSGA-II_rank: 3', 'change: 0.264072620029054', 'is_elite: False']\n", + "Id: 49_27 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_27', 'origin': '47_71~CUW~47_71#MGNP'} Metrics: ['ELUC: -13.977088904948522', 'NSGA-II_crowding_distance: 0.3092035934017102', 'NSGA-II_rank: 1', 'change: 0.18697222772583444', 'is_elite: True']\n", + "Id: 49_23 Identity: {'ancestor_count': 47, 'ancestor_ids': ['47_81', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_23', 'origin': '47_81~CUW~48_100#MGNP'} Metrics: ['ELUC: -14.475844763571303', 'NSGA-II_crowding_distance: 0.154657040417364', 'NSGA-II_rank: 1', 'change: 0.21500061673082732', 'is_elite: False']\n", + "Id: 48_100 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_28', '47_14'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_100', 'origin': '47_28~CUW~47_14#MGNP'} Metrics: ['ELUC: -14.792601254512524', 'NSGA-II_crowding_distance: 0.6946495928670278', 'NSGA-II_rank: 2', 'change: 0.21886754258634622', 'is_elite: False']\n", + "Id: 49_38 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_100', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_38', 'origin': '48_100~CUW~48_100#MGNP'} Metrics: ['ELUC: -14.825647475527203', 'NSGA-II_crowding_distance: 0.04070810006917179', 'NSGA-II_rank: 1', 'change: 0.21871814151604516', 'is_elite: False']\n", + "Id: 49_78 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_100', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_78', 'origin': '48_100~CUW~48_100#MGNP'} Metrics: ['ELUC: -14.837807606780094', 'NSGA-II_crowding_distance: 0.14991535442728565', 'NSGA-II_rank: 1', 'change: 0.22100438559136487', 'is_elite: False']\n", + "Id: 49_95 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_91'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_95', 'origin': '2_49~CUW~48_91#MGNP'} Metrics: ['ELUC: -14.996832859923874', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.27970911782301', 'is_elite: False']\n", + "Id: 48_34 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_62', '47_80'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_34', 'origin': '47_62~CUW~47_80#MGNP'} Metrics: ['ELUC: -15.2993869093206', 'NSGA-II_crowding_distance: 0.23498999441271884', 'NSGA-II_rank: 1', 'change: 0.25541003813671254', 'is_elite: False']\n", + "Id: 49_69 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_30'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_69', 'origin': '48_91~CUW~48_30#MGNP'} Metrics: ['ELUC: -16.11001954131717', 'NSGA-II_crowding_distance: 0.15453335843408023', 'NSGA-II_rank: 1', 'change: 0.26953033444080776', 'is_elite: False']\n", + "Id: 48_30 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '47_52'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_30', 'origin': '47_71~CUW~47_52#MGNP'} Metrics: ['ELUC: -16.7411889017413', 'NSGA-II_crowding_distance: 0.5432495998153491', 'NSGA-II_rank: 2', 'change: 0.27712415208538177', 'is_elite: False']\n", + "Id: 49_83 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_30', '48_30'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_83', 'origin': '48_30~CUW~48_30#MGNP'} Metrics: ['ELUC: -16.741512840082127', 'NSGA-II_crowding_distance: 0.18586000729176444', 'NSGA-II_rank: 1', 'change: 0.2770460269587684', 'is_elite: False']\n", + "Id: 49_49 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_49', 'origin': '2_49~CUW~48_100#MGNP'} Metrics: ['ELUC: -17.338021790850433', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3015716881239094', 'is_elite: False']\n", + "Id: 49_54 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '48_88'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_54', 'origin': '2_49~CUW~48_88#MGNP'} Metrics: ['ELUC: -17.512618599187878', 'NSGA-II_crowding_distance: 0.12959428783478508', 'NSGA-II_rank: 1', 'change: 0.3011842803618463', 'is_elite: False']\n", + "Id: 49_90 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '48_100'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_90', 'origin': '48_36~CUW~48_100#MGNP'} Metrics: ['ELUC: -17.542271232956466', 'NSGA-II_crowding_distance: 0.010975042157349051', 'NSGA-II_rank: 1', 'change: 0.30212495766361885', 'is_elite: False']\n", + "Id: 49_61 Identity: {'ancestor_count': 47, 'ancestor_ids': ['47_71', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_61', 'origin': '47_71~CUW~48_36#MGNP'} Metrics: ['ELUC: -17.597387663375198', 'NSGA-II_crowding_distance: 0.006135958509444832', 'NSGA-II_rank: 1', 'change: 0.3030204312135429', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 48_36 Identity: {'ancestor_count': 46, 'ancestor_ids': ['2_49', '47_62'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_36', 'origin': '2_49~CUW~47_62#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 49_46 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '1_1'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_46', 'origin': '48_36~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 49_53 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '48_30'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_53', 'origin': '48_36~CUW~48_30#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 49_76 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_76', 'origin': '48_36~CUW~48_36#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 49_82 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '2_49'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_82', 'origin': '48_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 49_92 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_92', 'origin': '48_36~CUW~48_36#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 49.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 50...:\n", + "PopulationResponse:\n", + " Generation: 50\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/50/20240220-014101\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 50 and asking ESP for generation 51...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 50 data persisted.\n", + "Evaluated candidates:\n", + "Id: 50_42 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_42', 'origin': '2_49~CUW~49_13#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 50_74 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_91'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_74', 'origin': '2_49~CUW~48_91#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 50_12 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_92', '48_91'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_12', 'origin': '49_92~CUW~48_91#MGNP'} Metrics: ['ELUC: 18.45643506523985', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.25950842280234027', 'is_elite: False']\n", + "Id: 50_48 Identity: {'ancestor_count': 45, 'ancestor_ids': ['2_49', '49_59'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_48', 'origin': '2_49~CUW~49_59#MGNP'} Metrics: ['ELUC: 14.604899789258905', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.2779511509152731', 'is_elite: False']\n", + "Id: 50_60 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_92', '49_23'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_60', 'origin': '49_92~CUW~49_23#MGNP'} Metrics: ['ELUC: 13.842827259203613', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.246372920579903', 'is_elite: False']\n", + "Id: 50_33 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '2_49'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_33', 'origin': '47_71~CUW~2_49#MGNP'} Metrics: ['ELUC: 6.307245108782006', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2835487864084532', 'is_elite: False']\n", + "Id: 50_39 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_13', '49_92'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_39', 'origin': '49_13~CUW~49_92#MGNP'} Metrics: ['ELUC: 5.7210638356814725', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.19626962997773276', 'is_elite: False']\n", + "Id: 50_80 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '49_69'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_80', 'origin': '2_49~CUW~49_69#MGNP'} Metrics: ['ELUC: 0.08260253263673381', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.26641355596091143', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 50_47 Identity: {'ancestor_count': 45, 'ancestor_ids': ['1_1', '49_59'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_47', 'origin': '1_1~CUW~49_59#MGNP'} Metrics: ['ELUC: -0.4856057141579346', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.05027425780338399', 'is_elite: False']\n", + "Id: 50_95 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '49_83'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_95', 'origin': '2_49~CUW~49_83#MGNP'} Metrics: ['ELUC: -0.5728578440409001', 'NSGA-II_crowding_distance: 1.421443566538485', 'NSGA-II_rank: 9', 'change: 0.2387690692474381', 'is_elite: False']\n", + "Id: 50_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_89', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8753352639217634', 'NSGA-II_crowding_distance: 0.25435601573782374', 'NSGA-II_rank: 1', 'change: 0.027764991111589848', 'is_elite: True']\n", + "Id: 50_79 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_33', '2_49'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_79', 'origin': '49_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.9689654391215364', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27055378829265914', 'is_elite: False']\n", + "Id: 50_14 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '48_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_14', 'origin': '1_1~CUW~48_34#MGNP'} Metrics: ['ELUC: -1.1805503906799333', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10461521767917184', 'is_elite: False']\n", + "Id: 50_84 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_84', 'origin': '48_91~CUW~49_13#MGNP'} Metrics: ['ELUC: -1.2279294181827836', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06213953353936763', 'is_elite: False']\n", + "Id: 50_20 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_18', '49_96'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_20', 'origin': '49_18~CUW~49_96#MGNP'} Metrics: ['ELUC: -1.8271377539042613', 'NSGA-II_crowding_distance: 0.17374856880809952', 'NSGA-II_rank: 2', 'change: 0.060625234984245456', 'is_elite: False']\n", + "Id: 50_58 Identity: {'ancestor_count': 46, 'ancestor_ids': ['1_1', '47_71'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_58', 'origin': '1_1~CUW~47_71#MGNP'} Metrics: ['ELUC: -1.8331372474370364', 'NSGA-II_crowding_distance: 0.29642862512657964', 'NSGA-II_rank: 6', 'change: 0.11192662499406154', 'is_elite: False']\n", + "Id: 50_96 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_13', '49_18'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_96', 'origin': '49_13~CUW~49_18#MGNP'} Metrics: ['ELUC: -1.8350769722987856', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08440598570013998', 'is_elite: False']\n", + "Id: 50_75 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_59', '48_91'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_75', 'origin': '49_59~CUW~48_91#MGNP'} Metrics: ['ELUC: -2.028763785651738', 'NSGA-II_crowding_distance: 0.22774469582140422', 'NSGA-II_rank: 3', 'change: 0.07092027243083443', 'is_elite: False']\n", + "Id: 50_66 Identity: {'ancestor_count': 2, 'ancestor_ids': ['49_18', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_66', 'origin': '49_18~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0675029680998858', 'NSGA-II_crowding_distance: 0.16524106988053514', 'NSGA-II_rank: 1', 'change: 0.04570611508692108', 'is_elite: False']\n", + "Id: 50_18 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '49_33'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_18', 'origin': '49_34~CUW~49_33#MGNP'} Metrics: ['ELUC: -2.149153038506714', 'NSGA-II_crowding_distance: 0.23661616027680882', 'NSGA-II_rank: 2', 'change: 0.06959495830192398', 'is_elite: False']\n", + "Id: 50_43 Identity: {'ancestor_count': 2, 'ancestor_ids': ['49_18', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_43', 'origin': '49_18~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2968258372216726', 'NSGA-II_crowding_distance: 0.21461742044075566', 'NSGA-II_rank: 1', 'change: 0.05294611077647936', 'is_elite: True']\n", + "Id: 50_24 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_54', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_24', 'origin': '49_54~CUW~49_13#MGNP'} Metrics: ['ELUC: -2.3140310621497493', 'NSGA-II_crowding_distance: 0.8722058938195072', 'NSGA-II_rank: 9', 'change: 0.2592145992536874', 'is_elite: False']\n", + "Id: 50_53 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '49_27'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_53', 'origin': '1_1~CUW~49_27#MGNP'} Metrics: ['ELUC: -2.5234743459493094', 'NSGA-II_crowding_distance: 0.810072683174921', 'NSGA-II_rank: 5', 'change: 0.09086130356923398', 'is_elite: False']\n", + "Id: 50_16 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_16', 'origin': '1_1~CUW~49_13#MGNP'} Metrics: ['ELUC: -2.6205193306353833', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08162521124571624', 'is_elite: False']\n", + "Id: 50_31 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_13', '49_59'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_31', 'origin': '49_13~CUW~49_59#MGNP'} Metrics: ['ELUC: -2.7670568386900563', 'NSGA-II_crowding_distance: 0.2579839172447756', 'NSGA-II_rank: 3', 'change: 0.08099644102561437', 'is_elite: False']\n", + "Id: 50_35 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '49_59'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_35', 'origin': '47_71~CUW~49_59#MGNP'} Metrics: ['ELUC: -3.161489307087968', 'NSGA-II_crowding_distance: 0.29312254540564325', 'NSGA-II_rank: 6', 'change: 0.12712749106961896', 'is_elite: False']\n", + "Id: 50_57 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_33', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_57', 'origin': '49_33~CUW~49_13#MGNP'} Metrics: ['ELUC: -3.190016432344776', 'NSGA-II_crowding_distance: 0.789235003461294', 'NSGA-II_rank: 4', 'change: 0.08858733221016929', 'is_elite: False']\n", + "Id: 50_32 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_32', 'origin': '47_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.0849800025963034', 'NSGA-II_crowding_distance: 0.5451447813093391', 'NSGA-II_rank: 6', 'change: 0.12841696811623385', 'is_elite: False']\n", + "Id: 50_97 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_33', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_97', 'origin': '49_33~CUW~49_13#MGNP'} Metrics: ['ELUC: -4.314650212497812', 'NSGA-II_crowding_distance: 0.23163920916156513', 'NSGA-II_rank: 3', 'change: 0.0846977791830507', 'is_elite: False']\n", + "Id: 50_30 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_30', 'origin': '1_1~CUW~49_13#MGNP'} Metrics: ['ELUC: -4.477716577019264', 'NSGA-II_crowding_distance: 0.2251405413581633', 'NSGA-II_rank: 1', 'change: 0.06884110276893476', 'is_elite: True']\n", + "Id: 50_70 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_18', '49_33'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_70', 'origin': '49_18~CUW~49_33#MGNP'} Metrics: ['ELUC: -4.597949714983377', 'NSGA-II_crowding_distance: 0.44331803059893354', 'NSGA-II_rank: 3', 'change: 0.09646466489054287', 'is_elite: False']\n", + "Id: 49_13 Identity: {'ancestor_count': 46, 'ancestor_ids': ['1_1', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_13', 'origin': '1_1~CUW~47_71#MGNP'} Metrics: ['ELUC: -4.620414695037546', 'NSGA-II_crowding_distance: 0.2222577269821134', 'NSGA-II_rank: 2', 'change: 0.07912022504967431', 'is_elite: False']\n", + "Id: 50_52 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_33', '49_18'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_52', 'origin': '49_33~CUW~49_18#MGNP'} Metrics: ['ELUC: -4.707790441630643', 'NSGA-II_crowding_distance: 0.1688985364783615', 'NSGA-II_rank: 2', 'change: 0.08793226957711509', 'is_elite: False']\n", + "Id: 50_99 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '49_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_99', 'origin': '1_1~CUW~49_34#MGNP'} Metrics: ['ELUC: -4.813522763472291', 'NSGA-II_crowding_distance: 0.15246924900568454', 'NSGA-II_rank: 1', 'change: 0.07741390851605262', 'is_elite: False']\n", + "Id: 50_21 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '49_69'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_21', 'origin': '1_1~CUW~49_69#MGNP'} Metrics: ['ELUC: -5.3946647887667325', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.15878836586796904', 'is_elite: False']\n", + "Id: 50_19 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_33', '49_92'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_19', 'origin': '49_33~CUW~49_92#MGNP'} Metrics: ['ELUC: -5.679841473667236', 'NSGA-II_crowding_distance: 1.1709768406732728', 'NSGA-II_rank: 8', 'change: 0.21632071502768463', 'is_elite: False']\n", + "Id: 50_44 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '49_96'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_44', 'origin': '1_1~CUW~49_96#MGNP'} Metrics: ['ELUC: -5.788990326844902', 'NSGA-II_crowding_distance: 0.109210956274643', 'NSGA-II_rank: 1', 'change: 0.09208180917244647', 'is_elite: False']\n", + "Id: 49_33 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_33', '48_66'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_33', 'origin': '48_33~CUW~48_66#MGNP'} Metrics: ['ELUC: -5.8465534007842805', 'NSGA-II_crowding_distance: 0.03742288263547046', 'NSGA-II_rank: 1', 'change: 0.09246917577174277', 'is_elite: False']\n", + "Id: 50_91 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_13', '49_33'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_91', 'origin': '49_13~CUW~49_33#MGNP'} Metrics: ['ELUC: -6.022700640406868', 'NSGA-II_crowding_distance: 0.18854731700195176', 'NSGA-II_rank: 2', 'change: 0.10108304814914805', 'is_elite: False']\n", + "Id: 50_77 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_33', '49_33'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_77', 'origin': '49_33~CUW~49_33#MGNP'} Metrics: ['ELUC: -6.1683100155899435', 'NSGA-II_crowding_distance: 0.15889736720975328', 'NSGA-II_rank: 1', 'change: 0.09681079134632688', 'is_elite: False']\n", + "Id: 50_29 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_13', '48_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_29', 'origin': '49_13~CUW~48_34#MGNP'} Metrics: ['ELUC: -6.284395479831954', 'NSGA-II_crowding_distance: 0.2630757933996615', 'NSGA-II_rank: 2', 'change: 0.11228449858011491', 'is_elite: False']\n", + "Id: 50_22 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_92', '48_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_22', 'origin': '49_92~CUW~48_34#MGNP'} Metrics: ['ELUC: -6.338773730854725', 'NSGA-II_crowding_distance: 0.5785564334615152', 'NSGA-II_rank: 9', 'change: 0.27233150231156295', 'is_elite: False']\n", + "Id: 50_87 Identity: {'ancestor_count': 2, 'ancestor_ids': ['49_18', '2_49'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_87', 'origin': '49_18~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.810288409910404', 'NSGA-II_crowding_distance: 1.079030756645758', 'NSGA-II_rank: 8', 'change: 0.22416187667773518', 'is_elite: False']\n", + "Id: 50_92 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '49_96'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_92', 'origin': '49_34~CUW~49_96#MGNP'} Metrics: ['ELUC: -7.20685900187046', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.13857891481691148', 'is_elite: False']\n", + "Id: 50_13 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_91'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_13', 'origin': '2_49~CUW~48_91#MGNP'} Metrics: ['ELUC: -7.219680590172462', 'NSGA-II_crowding_distance: 0.829023159326727', 'NSGA-II_rank: 8', 'change: 0.2651420346972141', 'is_elite: False']\n", + "Id: 50_46 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_54', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_46', 'origin': '49_54~CUW~49_13#MGNP'} Metrics: ['ELUC: -7.242484490862618', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2747916991499036', 'is_elite: False']\n", + "Id: 50_63 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '49_18'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_63', 'origin': '48_91~CUW~49_18#MGNP'} Metrics: ['ELUC: -7.3451371451596525', 'NSGA-II_crowding_distance: 1.232229432212418', 'NSGA-II_rank: 7', 'change: 0.1401359446788887', 'is_elite: False']\n", + "Id: 50_50 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_33', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_50', 'origin': '49_33~CUW~49_13#MGNP'} Metrics: ['ELUC: -7.373573365059396', 'NSGA-II_crowding_distance: 0.4895424232735864', 'NSGA-II_rank: 3', 'change: 0.12052409825060119', 'is_elite: False']\n", + "Id: 50_59 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_59', 'origin': '2_49~CUW~49_13#MGNP'} Metrics: ['ELUC: -7.754334647312338', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.27326737140627855', 'is_elite: False']\n", + "Id: 50_71 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_18', '49_83'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_71', 'origin': '49_18~CUW~49_83#MGNP'} Metrics: ['ELUC: -7.888073502160966', 'NSGA-II_crowding_distance: 1.8141868464776356', 'NSGA-II_rank: 7', 'change: 0.19659827999429816', 'is_elite: False']\n", + "Id: 49_34 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_41', '48_88'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_34', 'origin': '48_41~CUW~48_88#MGNP'} Metrics: ['ELUC: -7.945641163428854', 'NSGA-II_crowding_distance: 0.27063855338499326', 'NSGA-II_rank: 1', 'change: 0.10425844281622342', 'is_elite: True']\n", + "Id: 50_62 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_96', '2_49'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_62', 'origin': '49_96~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.992463412213646', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2974891033781674', 'is_elite: False']\n", + "Id: 50_83 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_34', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_83', 'origin': '48_34~CUW~49_13#MGNP'} Metrics: ['ELUC: -8.430017548557219', 'NSGA-II_crowding_distance: 1.6097293398865409', 'NSGA-II_rank: 6', 'change: 0.13651285034301178', 'is_elite: False']\n", + "Id: 50_72 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '49_33'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_72', 'origin': '49_34~CUW~49_33#MGNP'} Metrics: ['ELUC: -8.630693347014274', 'NSGA-II_crowding_distance: 1.4193934445447196', 'NSGA-II_rank: 5', 'change: 0.12686158832440766', 'is_elite: False']\n", + "Id: 50_81 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_54', '49_27'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_81', 'origin': '49_54~CUW~49_27#MGNP'} Metrics: ['ELUC: -8.723650636177904', 'NSGA-II_crowding_distance: 1.189927316825079', 'NSGA-II_rank: 5', 'change: 0.2608090663624104', 'is_elite: False']\n", + "Id: 50_38 Identity: {'ancestor_count': 48, 'ancestor_ids': ['48_91', '49_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_38', 'origin': '48_91~CUW~49_34#MGNP'} Metrics: ['ELUC: -8.962117397510172', 'NSGA-II_crowding_distance: 1.2991095087282503', 'NSGA-II_rank: 4', 'change: 0.12553472165772506', 'is_elite: False']\n", + "Id: 50_85 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '49_96'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_85', 'origin': '49_34~CUW~49_96#MGNP'} Metrics: ['ELUC: -9.021076092222755', 'NSGA-II_crowding_distance: 0.2601219792981755', 'NSGA-II_rank: 3', 'change: 0.12141311334331768', 'is_elite: False']\n", + "Id: 50_67 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '48_91'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_67', 'origin': '49_34~CUW~48_91#MGNP'} Metrics: ['ELUC: -9.400694311340931', 'NSGA-II_crowding_distance: 0.29653460850722557', 'NSGA-II_rank: 2', 'change: 0.11761276501294574', 'is_elite: False']\n", + "Id: 50_11 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_27', '49_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_11', 'origin': '49_27~CUW~49_34#MGNP'} Metrics: ['ELUC: -9.780546595428337', 'NSGA-II_crowding_distance: 0.6341778266728956', 'NSGA-II_rank: 3', 'change: 0.13298775630746887', 'is_elite: False']\n", + "Id: 50_49 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_91'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_49', 'origin': '48_91~CUW~48_91#MGNP'} Metrics: ['ELUC: -9.851592777762654', 'NSGA-II_crowding_distance: 0.19055649738098646', 'NSGA-II_rank: 1', 'change: 0.11505686078313702', 'is_elite: True']\n", + "Id: 50_88 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '47_71'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_88', 'origin': '48_91~CUW~47_71#MGNP'} Metrics: ['ELUC: -10.091777005536848', 'NSGA-II_crowding_distance: 0.14937594095350523', 'NSGA-II_rank: 2', 'change: 0.13092001402145023', 'is_elite: False']\n", + "Id: 48_91 Identity: {'ancestor_count': 46, 'ancestor_ids': ['46_14', '47_42'], 'birth_generation': 48, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '48_91', 'origin': '46_14~CUW~47_42#MGNP'} Metrics: ['ELUC: -10.478688532030786', 'NSGA-II_crowding_distance: 0.11845540630733535', 'NSGA-II_rank: 1', 'change: 0.11812966051473663', 'is_elite: False']\n", + "Id: 50_98 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_23', '49_27'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_98', 'origin': '49_23~CUW~49_27#MGNP'} Metrics: ['ELUC: -10.825483609805419', 'NSGA-II_crowding_distance: 1.2107649965387062', 'NSGA-II_rank: 4', 'change: 0.20891283332075605', 'is_elite: False']\n", + "Id: 50_65 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '49_27'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_65', 'origin': '1_1~CUW~49_27#MGNP'} Metrics: ['ELUC: -11.003846513175864', 'NSGA-II_crowding_distance: 0.3014167811240621', 'NSGA-II_rank: 2', 'change: 0.1316618128977985', 'is_elite: False']\n", + "Id: 50_28 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_13', '49_27'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_28', 'origin': '49_13~CUW~49_27#MGNP'} Metrics: ['ELUC: -11.049771466849757', 'NSGA-II_crowding_distance: 0.12600488258229892', 'NSGA-II_rank: 1', 'change: 0.1300678525782734', 'is_elite: False']\n", + "Id: 49_96 Identity: {'ancestor_count': 46, 'ancestor_ids': ['48_12', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_96', 'origin': '48_12~CUW~47_71#MGNP'} Metrics: ['ELUC: -11.34285255212047', 'NSGA-II_crowding_distance: 0.15374321310997235', 'NSGA-II_rank: 1', 'change: 0.14106157965097307', 'is_elite: False']\n", + "Id: 50_61 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_23', '49_18'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_61', 'origin': '49_23~CUW~49_18#MGNP'} Metrics: ['ELUC: -11.50881809794718', 'NSGA-II_crowding_distance: 0.669464848412859', 'NSGA-II_rank: 3', 'change: 0.19906108241904635', 'is_elite: False']\n", + "Id: 50_56 Identity: {'ancestor_count': 7, 'ancestor_ids': ['49_18', '49_54'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_56', 'origin': '49_18~CUW~49_54#MGNP'} Metrics: ['ELUC: -11.719110893083258', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3121817953181608', 'is_elite: False']\n", + "Id: 50_37 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_96', '49_78'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_37', 'origin': '49_96~CUW~49_78#MGNP'} Metrics: ['ELUC: -11.945091114316439', 'NSGA-II_crowding_distance: 0.41689584507054883', 'NSGA-II_rank: 3', 'change: 0.221410050723502', 'is_elite: False']\n", + "Id: 50_54 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_27', '49_33'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_54', 'origin': '49_27~CUW~49_33#MGNP'} Metrics: ['ELUC: -11.955130362999132', 'NSGA-II_crowding_distance: 0.3048496124815653', 'NSGA-II_rank: 2', 'change: 0.17958068919768905', 'is_elite: False']\n", + "Id: 50_94 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_13', '47_71'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_94', 'origin': '49_13~CUW~47_71#MGNP'} Metrics: ['ELUC: -12.368906226045505', 'NSGA-II_crowding_distance: 0.11678961679096524', 'NSGA-II_rank: 1', 'change: 0.15355527772789446', 'is_elite: False']\n", + "Id: 50_23 Identity: {'ancestor_count': 48, 'ancestor_ids': ['48_91', '49_23'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_23', 'origin': '48_91~CUW~49_23#MGNP'} Metrics: ['ELUC: -12.51117997060411', 'NSGA-II_crowding_distance: 0.11690432723435332', 'NSGA-II_rank: 2', 'change: 0.18646342889616435', 'is_elite: False']\n", + "Id: 47_71 Identity: {'ancestor_count': 45, 'ancestor_ids': ['46_82', '46_82'], 'birth_generation': 47, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '47_71', 'origin': '46_82~CUW~46_82#MGNP'} Metrics: ['ELUC: -12.588030833841653', 'NSGA-II_crowding_distance: 0.09595714485949777', 'NSGA-II_rank: 1', 'change: 0.15477793940682558', 'is_elite: False']\n", + "Id: 50_40 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_96', '49_27'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_40', 'origin': '49_96~CUW~49_27#MGNP'} Metrics: ['ELUC: -13.199380292447659', 'NSGA-II_crowding_distance: 0.1158012747339988', 'NSGA-II_rank: 1', 'change: 0.16809335045656634', 'is_elite: False']\n", + "Id: 50_93 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '49_33'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_93', 'origin': '2_49~CUW~49_33#MGNP'} Metrics: ['ELUC: -13.354014902124968', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2772798830879983', 'is_elite: False']\n", + "Id: 50_34 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_34', 'origin': '48_91~CUW~48_34#MGNP'} Metrics: ['ELUC: -13.483665319058904', 'NSGA-II_crowding_distance: 0.10272253179374387', 'NSGA-II_rank: 2', 'change: 0.18651973048465376', 'is_elite: False']\n", + "Id: 50_82 Identity: {'ancestor_count': 47, 'ancestor_ids': ['47_71', '49_96'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_82', 'origin': '47_71~CUW~49_96#MGNP'} Metrics: ['ELUC: -13.50565087096307', 'NSGA-II_crowding_distance: 0.10750411489550694', 'NSGA-II_rank: 1', 'change: 0.17375816427247634', 'is_elite: False']\n", + "Id: 50_15 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '49_23'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_15', 'origin': '1_1~CUW~49_23#MGNP'} Metrics: ['ELUC: -13.750223396735242', 'NSGA-II_crowding_distance: 0.10965533303126554', 'NSGA-II_rank: 2', 'change: 0.19410180777299801', 'is_elite: False']\n", + "Id: 50_55 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '49_54'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_55', 'origin': '49_34~CUW~49_54#MGNP'} Metrics: ['ELUC: -13.901258834073673', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.27499661073621146', 'is_elite: False']\n", + "Id: 50_41 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_96', '48_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_41', 'origin': '49_96~CUW~48_34#MGNP'} Metrics: ['ELUC: -13.90835575099359', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2394219446664476', 'is_elite: False']\n", + "Id: 49_27 Identity: {'ancestor_count': 46, 'ancestor_ids': ['47_71', '47_71'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_27', 'origin': '47_71~CUW~47_71#MGNP'} Metrics: ['ELUC: -13.977088904948522', 'NSGA-II_crowding_distance: 0.11683092569980809', 'NSGA-II_rank: 1', 'change: 0.18697222772583444', 'is_elite: False']\n", + "Id: 50_76 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_76', 'origin': '48_91~CUW~48_34#MGNP'} Metrics: ['ELUC: -14.10126000675805', 'NSGA-II_crowding_distance: 0.6533490960812333', 'NSGA-II_rank: 2', 'change: 0.20511537163415478', 'is_elite: False']\n", + "Id: 50_78 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_27', '49_27'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_78', 'origin': '49_27~CUW~49_27#MGNP'} Metrics: ['ELUC: -14.296317124276403', 'NSGA-II_crowding_distance: 0.15583369619327053', 'NSGA-II_rank: 1', 'change: 0.19520005887420339', 'is_elite: False']\n", + "Id: 50_73 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_78', '49_78'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_73', 'origin': '49_78~CUW~49_78#MGNP'} Metrics: ['ELUC: -14.806949299822682', 'NSGA-II_crowding_distance: 0.18220553556350141', 'NSGA-II_rank: 1', 'change: 0.2193865431809458', 'is_elite: False']\n", + "Id: 50_86 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_83', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_86', 'origin': '49_83~CUW~49_13#MGNP'} Metrics: ['ELUC: -15.364912154451012', 'NSGA-II_crowding_distance: 0.15937984671735153', 'NSGA-II_rank: 1', 'change: 0.2314317431530251', 'is_elite: False']\n", + "Id: 50_68 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_27', '48_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_68', 'origin': '49_27~CUW~48_34#MGNP'} Metrics: ['ELUC: -15.507158836894707', 'NSGA-II_crowding_distance: 0.33753051325424743', 'NSGA-II_rank: 1', 'change: 0.2550591659353812', 'is_elite: True']\n", + "Id: 50_27 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_23', '2_49'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_27', 'origin': '49_23~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.308613892244484', 'NSGA-II_crowding_distance: 0.25194051390913536', 'NSGA-II_rank: 1', 'change: 0.29915810875217974', 'is_elite: True']\n", + "Id: 50_36 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_83', '49_54'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_36', 'origin': '49_83~CUW~49_54#MGNP'} Metrics: ['ELUC: -17.326268832736076', 'NSGA-II_crowding_distance: 0.016251125653798798', 'NSGA-II_rank: 1', 'change: 0.29936174341286853', 'is_elite: False']\n", + "Id: 50_26 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_26', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.51269054045317', 'NSGA-II_crowding_distance: 0.02014987253288556', 'NSGA-II_rank: 1', 'change: 0.300543838870784', 'is_elite: False']\n", + "Id: 50_51 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_92', '49_69'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_51', 'origin': '49_92~CUW~49_69#MGNP'} Metrics: ['ELUC: -17.523893025346105', 'NSGA-II_crowding_distance: 0.013101677944305765', 'NSGA-II_rank: 1', 'change: 0.30202027287412125', 'is_elite: False']\n", + "Id: 50_45 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_59', '49_92'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_45', 'origin': '49_59~CUW~49_92#MGNP'} Metrics: ['ELUC: -17.540672589323197', 'NSGA-II_crowding_distance: 0.5909353373109286', 'NSGA-II_rank: 2', 'change: 0.303259175701513', 'is_elite: False']\n", + "Id: 50_100 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '2_49'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_100', 'origin': '48_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.56871628092567', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3032659296437435', 'is_elite: False']\n", + "Id: 50_64 Identity: {'ancestor_count': 7, 'ancestor_ids': ['49_54', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_64', 'origin': '49_54~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.59728904803772', 'NSGA-II_crowding_distance: 0.007532070270316851', 'NSGA-II_rank: 1', 'change: 0.3030174248460052', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 49_92 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_36', '48_36'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_92', 'origin': '48_36~CUW~48_36#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 50_17 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_17', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 50_25 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_92', '48_91'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_25', 'origin': '49_92~CUW~48_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 50_69 Identity: {'ancestor_count': 7, 'ancestor_ids': ['1_1', '49_54'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_69', 'origin': '1_1~CUW~49_54#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 50_90 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_13', '49_54'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_90', 'origin': '49_13~CUW~49_54#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 50.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 51...:\n", + "PopulationResponse:\n", + " Generation: 51\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/51/20240220-014814\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 51 and asking ESP for generation 52...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 51 data persisted.\n", + "Evaluated candidates:\n", + "Id: 51_46 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '2_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_46', 'origin': '49_34~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 51_97 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_97', 'origin': '2_49~CUW~50_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 51_31 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_27', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_31', 'origin': '50_27~CUW~50_89#MGNP'} Metrics: ['ELUC: 21.31461865743494', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2927695222219327', 'is_elite: False']\n", + "Id: 51_62 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_86', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_62', 'origin': '50_86~CUW~50_90#MGNP'} Metrics: ['ELUC: 14.65791643163783', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2734504322553529', 'is_elite: False']\n", + "Id: 51_29 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_29', 'origin': '2_49~CUW~49_34#MGNP'} Metrics: ['ELUC: 6.728359903057519', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27305628997604', 'is_elite: False']\n", + "Id: 51_16 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_16', 'origin': '1_1~CUW~50_68#MGNP'} Metrics: ['ELUC: 4.662539244330116', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.09887823409343431', 'is_elite: False']\n", + "Id: 51_34 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_90', '50_77'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_34', 'origin': '50_90~CUW~50_77#MGNP'} Metrics: ['ELUC: 4.1157245895817915', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2471626165323256', 'is_elite: False']\n", + "Id: 51_74 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_43', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_74', 'origin': '50_43~CUW~50_68#MGNP'} Metrics: ['ELUC: 2.7163304383208913', 'NSGA-II_crowding_distance: 0.6074603549893929', 'NSGA-II_rank: 6', 'change: 0.11300170291906869', 'is_elite: False']\n", + "Id: 51_75 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_27', '1_1'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_75', 'origin': '50_27~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.8076777983168625', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.22216561865030518', 'is_elite: False']\n", + "Id: 51_64 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_89', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_64', 'origin': '50_89~CUW~49_34#MGNP'} Metrics: ['ELUC: 0.21447017468280452', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.048481717832200996', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 51_65 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_49', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_65', 'origin': '50_49~CUW~50_30#MGNP'} Metrics: ['ELUC: -0.1623015396570172', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09599248365877801', 'is_elite: False']\n", + "Id: 51_18 Identity: {'ancestor_count': 3, 'ancestor_ids': ['50_66', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_18', 'origin': '50_66~CUW~50_89#MGNP'} Metrics: ['ELUC: -0.2663120145255094', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.027945057153900877', 'is_elite: False']\n", + "Id: 51_93 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_93', 'origin': '50_68~CUW~50_90#MGNP'} Metrics: ['ELUC: -0.32923441805067727', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30116975428918835', 'is_elite: False']\n", + "Id: 51_38 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_38', 'origin': '2_49~CUW~49_34#MGNP'} Metrics: ['ELUC: -0.5661572461055701', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2387009489122178', 'is_elite: False']\n", + "Id: 51_59 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '50_66'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_59', 'origin': '50_68~CUW~50_66#MGNP'} Metrics: ['ELUC: -0.7930706296840256', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.15276093208358318', 'is_elite: False']\n", + "Id: 50_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_89', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8753352639217634', 'NSGA-II_crowding_distance: 0.2596838983715314', 'NSGA-II_rank: 1', 'change: 0.027764991111589848', 'is_elite: True']\n", + "Id: 51_39 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_89', '50_86'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_39', 'origin': '50_89~CUW~50_86#MGNP'} Metrics: ['ELUC: -1.0685614766393225', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.14096490735260483', 'is_elite: False']\n", + "Id: 51_32 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_32', 'origin': '2_49~CUW~49_34#MGNP'} Metrics: ['ELUC: -1.1713967292194132', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.25550877316093845', 'is_elite: False']\n", + "Id: 51_36 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_36', 'origin': '50_68~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.3816987652462143', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07980766861368013', 'is_elite: False']\n", + "Id: 51_49 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '50_43'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_49', 'origin': '49_34~CUW~50_43#MGNP'} Metrics: ['ELUC: -1.6479426699248747', 'NSGA-II_crowding_distance: 0.2952835211511654', 'NSGA-II_rank: 3', 'change: 0.07699127745720105', 'is_elite: False']\n", + "Id: 51_28 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_96', '1_1'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_28', 'origin': '49_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.041148181837152', 'NSGA-II_crowding_distance: 0.3718433109998581', 'NSGA-II_rank: 4', 'change: 0.08857258959600739', 'is_elite: False']\n", + "Id: 51_23 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_23', 'origin': '1_1~CUW~50_30#MGNP'} Metrics: ['ELUC: -2.0479487894327986', 'NSGA-II_crowding_distance: 0.20474926215656497', 'NSGA-II_rank: 1', 'change: 0.04762767696756265', 'is_elite: False']\n", + "Id: 51_89 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_89', 'origin': '1_1~CUW~50_90#MGNP'} Metrics: ['ELUC: -2.172024241933993', 'NSGA-II_crowding_distance: 1.1911031695944987', 'NSGA-II_rank: 7', 'change: 0.24753836939362286', 'is_elite: False']\n", + "Id: 51_24 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_49', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_24', 'origin': '50_49~CUW~50_89#MGNP'} Metrics: ['ELUC: -2.252258958585579', 'NSGA-II_crowding_distance: 0.35486534269421693', 'NSGA-II_rank: 3', 'change: 0.08490753015108786', 'is_elite: False']\n", + "Id: 50_43 Identity: {'ancestor_count': 2, 'ancestor_ids': ['49_18', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_43', 'origin': '49_18~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2968258372216726', 'NSGA-II_crowding_distance: 0.3432079133328826', 'NSGA-II_rank: 2', 'change: 0.05294611077647936', 'is_elite: False']\n", + "Id: 51_96 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_28', '1_1'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_96', 'origin': '50_28~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.869057071153543', 'NSGA-II_crowding_distance: 0.16238700208755139', 'NSGA-II_rank: 2', 'change: 0.07650810007779264', 'is_elite: False']\n", + "Id: 51_12 Identity: {'ancestor_count': 3, 'ancestor_ids': ['50_66', '2_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_12', 'origin': '50_66~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.8700955447423895', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2622222294624557', 'is_elite: False']\n", + "Id: 51_69 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_77', '50_66'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_69', 'origin': '50_77~CUW~50_66#MGNP'} Metrics: ['ELUC: -2.8764085434427082', 'NSGA-II_crowding_distance: 0.18209749693669233', 'NSGA-II_rank: 2', 'change: 0.08667941194147316', 'is_elite: False']\n", + "Id: 51_94 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_78', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_94', 'origin': '50_78~CUW~50_30#MGNP'} Metrics: ['ELUC: -2.9840485166106516', 'NSGA-II_crowding_distance: 1.2413659788297515', 'NSGA-II_rank: 6', 'change: 0.12723703044535276', 'is_elite: False']\n", + "Id: 51_15 Identity: {'ancestor_count': 3, 'ancestor_ids': ['50_66', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_15', 'origin': '50_66~CUW~50_89#MGNP'} Metrics: ['ELUC: -3.2275245050993067', 'NSGA-II_crowding_distance: 0.209289537807048', 'NSGA-II_rank: 1', 'change: 0.048940231681520854', 'is_elite: False']\n", + "Id: 51_22 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_49', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_22', 'origin': '50_49~CUW~50_89#MGNP'} Metrics: ['ELUC: -4.002070343417983', 'NSGA-II_crowding_distance: 0.7369616463413042', 'NSGA-II_rank: 5', 'change: 0.11444492922345889', 'is_elite: False']\n", + "Id: 50_30 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_30', 'origin': '1_1~CUW~49_13#MGNP'} Metrics: ['ELUC: -4.477716577019264', 'NSGA-II_crowding_distance: 0.296419890108948', 'NSGA-II_rank: 1', 'change: 0.06884110276893476', 'is_elite: True']\n", + "Id: 51_45 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_77', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_45', 'origin': '50_77~CUW~50_49#MGNP'} Metrics: ['ELUC: -4.556201179658037', 'NSGA-II_crowding_distance: 0.5183282698114872', 'NSGA-II_rank: 4', 'change: 0.10497618102498005', 'is_elite: False']\n", + "Id: 51_80 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_80', 'origin': '1_1~CUW~50_49#MGNP'} Metrics: ['ELUC: -4.668196799595134', 'NSGA-II_crowding_distance: 0.2238030088689103', 'NSGA-II_rank: 2', 'change: 0.09537449074368018', 'is_elite: False']\n", + "Id: 51_48 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_86', '2_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_48', 'origin': '50_86~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.73740594350402', 'NSGA-II_crowding_distance: 1.1859416848672646', 'NSGA-II_rank: 7', 'change: 0.2592794201254164', 'is_elite: False']\n", + "Id: 51_85 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_73', '50_43'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_85', 'origin': '50_73~CUW~50_43#MGNP'} Metrics: ['ELUC: -5.300513602170633', 'NSGA-II_crowding_distance: 0.8317921083712893', 'NSGA-II_rank: 5', 'change: 0.16267241840204985', 'is_elite: False']\n", + "Id: 51_70 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '50_66'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_70', 'origin': '50_68~CUW~50_66#MGNP'} Metrics: ['ELUC: -5.790832117841203', 'NSGA-II_crowding_distance: 0.4365978023884299', 'NSGA-II_rank: 4', 'change: 0.13395120567186594', 'is_elite: False']\n", + "Id: 51_98 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_78', '50_27'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_98', 'origin': '50_78~CUW~50_27#MGNP'} Metrics: ['ELUC: -5.8476939847390454', 'NSGA-II_crowding_distance: 0.8767866635490942', 'NSGA-II_rank: 6', 'change: 0.24585715178711143', 'is_elite: False']\n", + "Id: 51_95 Identity: {'ancestor_count': 48, 'ancestor_ids': ['48_91', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_95', 'origin': '48_91~CUW~49_34#MGNP'} Metrics: ['ELUC: -5.848066779892208', 'NSGA-II_crowding_distance: 0.566715574086666', 'NSGA-II_rank: 3', 'change: 0.10229186911134516', 'is_elite: False']\n", + "Id: 51_76 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '1_1'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_76', 'origin': '49_34~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.8674310956723', 'NSGA-II_crowding_distance: 0.19792199264943164', 'NSGA-II_rank: 2', 'change: 0.09699989168765988', 'is_elite: False']\n", + "Id: 51_19 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_19', 'origin': '1_1~CUW~50_90#MGNP'} Metrics: ['ELUC: -6.012319508998356', 'NSGA-II_crowding_distance: 0.14076786920255216', 'NSGA-II_rank: 6', 'change: 0.253111440337022', 'is_elite: False']\n", + "Id: 51_99 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_27', '50_43'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_99', 'origin': '49_27~CUW~50_43#MGNP'} Metrics: ['ELUC: -6.186371414136155', 'NSGA-II_crowding_distance: 0.31593877304023077', 'NSGA-II_rank: 1', 'change: 0.08717277711904657', 'is_elite: True']\n", + "Id: 51_61 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_61', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.5262202381936865', 'NSGA-II_crowding_distance: 0.5157529814615129', 'NSGA-II_rank: 6', 'change: 0.2640262272385486', 'is_elite: False']\n", + "Id: 51_81 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_81', 'origin': '1_1~CUW~49_34#MGNP'} Metrics: ['ELUC: -7.052180100669425', 'NSGA-II_crowding_distance: 0.24119831453744484', 'NSGA-II_rank: 2', 'change: 0.10881038379638149', 'is_elite: False']\n", + "Id: 51_78 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_89', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_78', 'origin': '50_89~CUW~50_90#MGNP'} Metrics: ['ELUC: -7.192666148326994', 'NSGA-II_crowding_distance: 0.7967927078827884', 'NSGA-II_rank: 5', 'change: 0.223884395837255', 'is_elite: False']\n", + "Id: 51_47 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_47', 'origin': '49_34~CUW~50_68#MGNP'} Metrics: ['ELUC: -7.205754371428959', 'NSGA-II_crowding_distance: 0.8704511955036522', 'NSGA-II_rank: 4', 'change: 0.15095640248627468', 'is_elite: False']\n", + "Id: 49_34 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_41', '48_88'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_34', 'origin': '48_41~CUW~48_88#MGNP'} Metrics: ['ELUC: -7.945641163428854', 'NSGA-II_crowding_distance: 0.30191269444349916', 'NSGA-II_rank: 1', 'change: 0.10425844281622342', 'is_elite: True']\n", + "Id: 51_91 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_91', 'origin': '50_68~CUW~50_30#MGNP'} Metrics: ['ELUC: -8.13864892353833', 'NSGA-II_crowding_distance: 0.4185571874416642', 'NSGA-II_rank: 3', 'change: 0.13758988536881187', 'is_elite: False']\n", + "Id: 51_73 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '50_66'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_73', 'origin': '2_49~CUW~50_66#MGNP'} Metrics: ['ELUC: -8.215361923905716', 'NSGA-II_crowding_distance: 0.5514970374892216', 'NSGA-II_rank: 5', 'change: 0.2693608199064516', 'is_elite: False']\n", + "Id: 51_35 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '50_78'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_35', 'origin': '1_1~CUW~50_78#MGNP'} Metrics: ['ELUC: -8.406660473537043', 'NSGA-II_crowding_distance: 0.5408327511333116', 'NSGA-II_rank: 3', 'change: 0.16794821654354966', 'is_elite: False']\n", + "Id: 51_21 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_43', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_21', 'origin': '50_43~CUW~50_49#MGNP'} Metrics: ['ELUC: -8.516864797116602', 'NSGA-II_crowding_distance: 0.1601086654819811', 'NSGA-II_rank: 2', 'change: 0.11759444307695739', 'is_elite: False']\n", + "Id: 51_77 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_30', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_77', 'origin': '50_30~CUW~49_34#MGNP'} Metrics: ['ELUC: -8.736989891560679', 'NSGA-II_crowding_distance: 0.0801351644513382', 'NSGA-II_rank: 2', 'change: 0.12370043404402883', 'is_elite: False']\n", + "Id: 51_71 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_71', 'origin': '49_34~CUW~50_30#MGNP'} Metrics: ['ELUC: -9.286641922033409', 'NSGA-II_crowding_distance: 0.16876273526136495', 'NSGA-II_rank: 2', 'change: 0.12625934821594903', 'is_elite: False']\n", + "Id: 51_20 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_89', '50_73'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_20', 'origin': '50_89~CUW~50_73#MGNP'} Metrics: ['ELUC: -9.530104701752444', 'NSGA-II_crowding_distance: 0.2370803374161759', 'NSGA-II_rank: 2', 'change: 0.1556104629649926', 'is_elite: False']\n", + "Id: 51_30 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_30', '2_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_30', 'origin': '50_30~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.57289306647931', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29670455143997265', 'is_elite: False']\n", + "Id: 51_17 Identity: {'ancestor_count': 49, 'ancestor_ids': ['1_1', '50_27'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_17', 'origin': '1_1~CUW~50_27#MGNP'} Metrics: ['ELUC: -9.70609336893431', 'NSGA-II_crowding_distance: 0.9118843065540693', 'NSGA-II_rank: 4', 'change: 0.24646305553478995', 'is_elite: False']\n", + "Id: 50_49 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_91', '48_91'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_49', 'origin': '48_91~CUW~48_91#MGNP'} Metrics: ['ELUC: -9.851592777762654', 'NSGA-II_crowding_distance: 0.16511765789014005', 'NSGA-II_rank: 1', 'change: 0.11505686078313702', 'is_elite: False']\n", + "Id: 51_79 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_89', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_79', 'origin': '50_89~CUW~50_49#MGNP'} Metrics: ['ELUC: -9.88603441451547', 'NSGA-II_crowding_distance: 0.04800188059601615', 'NSGA-II_rank: 1', 'change: 0.12059680074233539', 'is_elite: False']\n", + "Id: 51_37 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_90', '50_86'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_37', 'origin': '50_90~CUW~50_86#MGNP'} Metrics: ['ELUC: -10.170422990913426', 'NSGA-II_crowding_distance: 0.44814175454999017', 'NSGA-II_rank: 3', 'change: 0.2414793115254494', 'is_elite: False']\n", + "Id: 51_53 Identity: {'ancestor_count': 49, 'ancestor_ids': ['48_91', '50_27'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_53', 'origin': '48_91~CUW~50_27#MGNP'} Metrics: ['ELUC: -10.30145205996003', 'NSGA-II_crowding_distance: 0.1506327228548212', 'NSGA-II_rank: 3', 'change: 0.25087418189693256', 'is_elite: False']\n", + "Id: 51_27 Identity: {'ancestor_count': 49, 'ancestor_ids': ['48_91', '50_73'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_27', 'origin': '48_91~CUW~50_73#MGNP'} Metrics: ['ELUC: -10.30533086645977', 'NSGA-II_crowding_distance: 0.12483745931119802', 'NSGA-II_rank: 1', 'change: 0.12167947700829518', 'is_elite: False']\n", + "Id: 51_54 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_54', 'origin': '2_49~CUW~50_30#MGNP'} Metrics: ['ELUC: -10.864650043001141', 'NSGA-II_crowding_distance: 0.46624564577590716', 'NSGA-II_rank: 5', 'change: 0.27605199167335154', 'is_elite: False']\n", + "Id: 51_33 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_33', 'origin': '50_68~CUW~49_34#MGNP'} Metrics: ['ELUC: -10.866794282895434', 'NSGA-II_crowding_distance: 0.11971605797850554', 'NSGA-II_rank: 2', 'change: 0.16339865346771829', 'is_elite: False']\n", + "Id: 51_58 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_30', '50_27'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_58', 'origin': '50_30~CUW~50_27#MGNP'} Metrics: ['ELUC: -10.89501189879051', 'NSGA-II_crowding_distance: 0.5160986039147297', 'NSGA-II_rank: 4', 'change: 0.27510960853988414', 'is_elite: False']\n", + "Id: 51_72 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_72', 'origin': '50_68~CUW~50_30#MGNP'} Metrics: ['ELUC: -10.935694656694627', 'NSGA-II_crowding_distance: 0.15936945613449197', 'NSGA-II_rank: 2', 'change: 0.16433791069900447', 'is_elite: False']\n", + "Id: 51_50 Identity: {'ancestor_count': 48, 'ancestor_ids': ['48_91', '50_28'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_50', 'origin': '48_91~CUW~50_28#MGNP'} Metrics: ['ELUC: -11.382424814009154', 'NSGA-II_crowding_distance: 0.13410512219381548', 'NSGA-II_rank: 1', 'change: 0.13245131030091223', 'is_elite: False']\n", + "Id: 51_44 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_78', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_44', 'origin': '50_78~CUW~50_49#MGNP'} Metrics: ['ELUC: -11.862327513770609', 'NSGA-II_crowding_distance: 0.2165247099025468', 'NSGA-II_rank: 1', 'change: 0.13527074393301133', 'is_elite: True']\n", + "Id: 51_55 Identity: {'ancestor_count': 49, 'ancestor_ids': ['2_49', '50_73'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_55', 'origin': '2_49~CUW~50_73#MGNP'} Metrics: ['ELUC: -11.995758597672285', 'NSGA-II_crowding_distance: 0.17595147399591832', 'NSGA-II_rank: 3', 'change: 0.251583828605354', 'is_elite: False']\n", + "Id: 51_88 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '48_91'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_88', 'origin': '50_68~CUW~48_91#MGNP'} Metrics: ['ELUC: -12.205147590734141', 'NSGA-II_crowding_distance: 0.3467206999094421', 'NSGA-II_rank: 2', 'change: 0.18380800288457244', 'is_elite: False']\n", + "Id: 51_26 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_27', '2_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_26', 'origin': '50_27~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.326741846493405', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2790744805900786', 'is_elite: False']\n", + "Id: 51_51 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_89', '50_27'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_51', 'origin': '50_89~CUW~50_27#MGNP'} Metrics: ['ELUC: -12.374250333230192', 'NSGA-II_crowding_distance: 0.10787470778857608', 'NSGA-II_rank: 3', 'change: 0.2635643918264359', 'is_elite: False']\n", + "Id: 51_83 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_83', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.790087344807361', 'NSGA-II_crowding_distance: 0.17780533407971105', 'NSGA-II_rank: 3', 'change: 0.26648842010285706', 'is_elite: False']\n", + "Id: 51_67 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_73', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_67', 'origin': '50_73~CUW~50_89#MGNP'} Metrics: ['ELUC: -12.95325825407435', 'NSGA-II_crowding_distance: 0.34114333194636304', 'NSGA-II_rank: 1', 'change: 0.1703999307886106', 'is_elite: True']\n", + "Id: 51_13 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_77', '50_86'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_13', 'origin': '50_77~CUW~50_86#MGNP'} Metrics: ['ELUC: -13.590616151151165', 'NSGA-II_crowding_distance: 0.29393101417375944', 'NSGA-II_rank: 2', 'change: 0.2129766549952534', 'is_elite: False']\n", + "Id: 51_84 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_86', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_84', 'origin': '50_86~CUW~50_30#MGNP'} Metrics: ['ELUC: -14.026066418554128', 'NSGA-II_crowding_distance: 0.21165518440825898', 'NSGA-II_rank: 1', 'change: 0.20034099558376334', 'is_elite: True']\n", + "Id: 51_66 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_66', 'origin': '2_49~CUW~50_68#MGNP'} Metrics: ['ELUC: -14.040446954700489', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2778184261944195', 'is_elite: False']\n", + "Id: 51_25 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_30', '50_73'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_25', 'origin': '50_30~CUW~50_73#MGNP'} Metrics: ['ELUC: -14.29214622349798', 'NSGA-II_crowding_distance: 0.29032852583875973', 'NSGA-II_rank: 2', 'change: 0.22774227464011135', 'is_elite: False']\n", + "Id: 51_52 Identity: {'ancestor_count': 49, 'ancestor_ids': ['49_27', '50_73'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_52', 'origin': '49_27~CUW~50_73#MGNP'} Metrics: ['ELUC: -14.312513403332648', 'NSGA-II_crowding_distance: 0.14072999094265734', 'NSGA-II_rank: 1', 'change: 0.21048614218586112', 'is_elite: False']\n", + "Id: 51_41 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_30', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_41', 'origin': '50_30~CUW~50_68#MGNP'} Metrics: ['ELUC: -14.331684797739761', 'NSGA-II_crowding_distance: 0.12137795328929697', 'NSGA-II_rank: 1', 'change: 0.23714525054839994', 'is_elite: False']\n", + "Id: 51_68 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_90', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_68', 'origin': '50_90~CUW~50_68#MGNP'} Metrics: ['ELUC: -14.359279764654136', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2776282771277797', 'is_elite: False']\n", + "Id: 51_14 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_30', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_14', 'origin': '50_30~CUW~50_68#MGNP'} Metrics: ['ELUC: -14.361236652310712', 'NSGA-II_crowding_distance: 0.12689309640408247', 'NSGA-II_rank: 1', 'change: 0.24587576991347163', 'is_elite: False']\n", + "Id: 51_56 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_49', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_56', 'origin': '50_49~CUW~50_90#MGNP'} Metrics: ['ELUC: -14.404528893933437', 'NSGA-II_crowding_distance: 0.1781313482118626', 'NSGA-II_rank: 3', 'change: 0.2773505819320984', 'is_elite: False']\n", + "Id: 51_92 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_90', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_92', 'origin': '50_90~CUW~49_34#MGNP'} Metrics: ['ELUC: -14.557003038181012', 'NSGA-II_crowding_distance: 0.17754097485526438', 'NSGA-II_rank: 3', 'change: 0.28429324956409163', 'is_elite: False']\n", + "Id: 51_63 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_90', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_63', 'origin': '50_90~CUW~50_68#MGNP'} Metrics: ['ELUC: -14.822127921105798', 'NSGA-II_crowding_distance: 0.3826712499902418', 'NSGA-II_rank: 2', 'change: 0.2700656009106227', 'is_elite: False']\n", + "Id: 50_68 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_27', '48_34'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_68', 'origin': '49_27~CUW~48_34#MGNP'} Metrics: ['ELUC: -15.507158836894707', 'NSGA-II_crowding_distance: 0.18304305797305598', 'NSGA-II_rank: 1', 'change: 0.2550591659353812', 'is_elite: False']\n", + "Id: 51_90 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_27', '50_68'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_90', 'origin': '49_27~CUW~50_68#MGNP'} Metrics: ['ELUC: -15.961266696264682', 'NSGA-II_crowding_distance: 0.18839882286125498', 'NSGA-II_rank: 1', 'change: 0.2733387362595767', 'is_elite: False']\n", + "Id: 51_82 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_78', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_82', 'origin': '50_78~CUW~50_90#MGNP'} Metrics: ['ELUC: -16.114486242785613', 'NSGA-II_crowding_distance: 0.1605293747735972', 'NSGA-II_rank: 3', 'change: 0.2958604644211371', 'is_elite: False']\n", + "Id: 51_86 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '50_43'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_86', 'origin': '2_49~CUW~50_43#MGNP'} Metrics: ['ELUC: -16.38982104867549', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29674284652809274', 'is_elite: False']\n", + "Id: 51_57 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_27', '50_27'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_57', 'origin': '50_27~CUW~50_27#MGNP'} Metrics: ['ELUC: -16.42570933163334', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.29456847680872467', 'is_elite: False']\n", + "Id: 51_43 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_90', '50_27'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_43', 'origin': '50_90~CUW~50_27#MGNP'} Metrics: ['ELUC: -16.88437198163055', 'NSGA-II_crowding_distance: 0.16316322323130955', 'NSGA-II_rank: 1', 'change: 0.287901444612279', 'is_elite: False']\n", + "Id: 50_27 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_23', '2_49'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_27', 'origin': '49_23~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.308613892244484', 'NSGA-II_crowding_distance: 0.07296312004726824', 'NSGA-II_rank: 1', 'change: 0.29915810875217974', 'is_elite: False']\n", + "Id: 51_100 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_28', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_100', 'origin': '50_28~CUW~50_90#MGNP'} Metrics: ['ELUC: -17.37708992802164', 'NSGA-II_crowding_distance: 0.028488860829523295', 'NSGA-II_rank: 1', 'change: 0.3013104382154082', 'is_elite: False']\n", + "Id: 51_42 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_90', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_42', 'origin': '50_90~CUW~50_89#MGNP'} Metrics: ['ELUC: -17.591728412349426', 'NSGA-II_crowding_distance: 0.018260513803814524', 'NSGA-II_rank: 1', 'change: 0.30285400927860645', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 50_90 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_13', '49_54'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_90', 'origin': '49_13~CUW~49_54#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 51_11 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_11', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 51_40 Identity: {'ancestor_count': 47, 'ancestor_ids': ['2_49', '48_91'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_40', 'origin': '2_49~CUW~48_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 51_60 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_73', '50_90'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_60', 'origin': '50_73~CUW~50_90#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 51_87 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_87', 'origin': '2_49~CUW~49_34#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 51.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 52...:\n", + "PopulationResponse:\n", + " Generation: 52\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/52/20240220-015528\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 52 and asking ESP for generation 53...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 52 data persisted.\n", + "Evaluated candidates:\n", + "Id: 52_91 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_30', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_91', 'origin': '50_30~CUW~51_87#MGNP'} Metrics: ['ELUC: 19.86592138202694', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2925512268368698', 'is_elite: False']\n", + "Id: 52_82 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_87', '51_15'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_82', 'origin': '51_87~CUW~51_15#MGNP'} Metrics: ['ELUC: 11.463929689545932', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.29326595998810195', 'is_elite: False']\n", + "Id: 52_78 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_52', '2_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_78', 'origin': '51_52~CUW~2_49#MGNP'} Metrics: ['ELUC: 11.14954444901883', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2548243231488472', 'is_elite: False']\n", + "Id: 52_90 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '2_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_90', 'origin': '51_44~CUW~2_49#MGNP'} Metrics: ['ELUC: 11.031941055729153', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3111778652986309', 'is_elite: False']\n", + "Id: 52_32 Identity: {'ancestor_count': 49, 'ancestor_ids': ['2_49', '51_23'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_32', 'origin': '2_49~CUW~51_23#MGNP'} Metrics: ['ELUC: 9.387975933235222', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2758785121706039', 'is_elite: False']\n", + "Id: 52_48 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_99', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_48', 'origin': '51_99~CUW~51_87#MGNP'} Metrics: ['ELUC: 5.644438942522039', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.22971616586410798', 'is_elite: False']\n", + "Id: 52_65 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_90', '50_89'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_65', 'origin': '51_90~CUW~50_89#MGNP'} Metrics: ['ELUC: 1.7710520072638525', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10395838626385409', 'is_elite: False']\n", + "Id: 52_81 Identity: {'ancestor_count': 2, 'ancestor_ids': ['50_89', '1_1'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_81', 'origin': '50_89~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.8338534568483839', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05172597994947343', 'is_elite: False']\n", + "Id: 52_36 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_36', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.4997286172595634', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03180936700860407', 'is_elite: False']\n", + "Id: 52_49 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_49', '51_23'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_49', 'origin': '50_49~CUW~51_23#MGNP'} Metrics: ['ELUC: 0.21463510410232914', 'NSGA-II_crowding_distance: 0.3497917682956436', 'NSGA-II_rank: 6', 'change: 0.10601108670623216', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 52_97 Identity: {'ancestor_count': 4, 'ancestor_ids': ['50_89', '51_15'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_97', 'origin': '50_89~CUW~51_15#MGNP'} Metrics: ['ELUC: -0.47049355766676104', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.041314045988407495', 'is_elite: False']\n", + "Id: 52_50 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '49_34'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_50', 'origin': '1_1~CUW~49_34#MGNP'} Metrics: ['ELUC: -0.4788871603354577', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06594618412650367', 'is_elite: False']\n", + "Id: 52_35 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_23', '2_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_35', 'origin': '51_23~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 52_51 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '1_1'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_51', 'origin': '51_67~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.611305299132522', 'NSGA-II_crowding_distance: 0.21009392106418423', 'NSGA-II_rank: 2', 'change: 0.03307537395012975', 'is_elite: False']\n", + "Id: 52_93 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '50_89'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_93', 'origin': '50_68~CUW~50_89#MGNP'} Metrics: ['ELUC: -0.6754386374720214', 'NSGA-II_crowding_distance: 0.20439532053504617', 'NSGA-II_rank: 6', 'change: 0.12305415575375439', 'is_elite: False']\n", + "Id: 52_45 Identity: {'ancestor_count': 48, 'ancestor_ids': ['51_99', '1_1'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_45', 'origin': '51_99~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7123248068278529', 'NSGA-II_crowding_distance: 0.25711138430259334', 'NSGA-II_rank: 4', 'change: 0.05891989502378412', 'is_elite: False']\n", + "Id: 52_64 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '50_30'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_64', 'origin': '51_67~CUW~50_30#MGNP'} Metrics: ['ELUC: -0.7890687954844708', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1276921444518906', 'is_elite: False']\n", + "Id: 52_31 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_89', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_31', 'origin': '50_89~CUW~51_44#MGNP'} Metrics: ['ELUC: -0.8514085092932333', 'NSGA-II_crowding_distance: 0.7399048962908923', 'NSGA-II_rank: 6', 'change: 0.12409226721686893', 'is_elite: False']\n", + "Id: 52_100 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_30', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_100', 'origin': '50_30~CUW~51_44#MGNP'} Metrics: ['ELUC: -0.8591976828694241', 'NSGA-II_crowding_distance: 0.3634180682799946', 'NSGA-II_rank: 5', 'change: 0.09071064964438634', 'is_elite: False']\n", + "Id: 50_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_89', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8753352639217634', 'NSGA-II_crowding_distance: 0.19783024934987475', 'NSGA-II_rank: 1', 'change: 0.027764991111589848', 'is_elite: True']\n", + "Id: 52_94 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_30', '50_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_94', 'origin': '50_30~CUW~50_49#MGNP'} Metrics: ['ELUC: -0.9348780078154894', 'NSGA-II_crowding_distance: 0.4404231197747286', 'NSGA-II_rank: 4', 'change: 0.07422788731637676', 'is_elite: False']\n", + "Id: 52_61 Identity: {'ancestor_count': 4, 'ancestor_ids': ['51_15', '50_89'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_61', 'origin': '51_15~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.360787233396522', 'NSGA-II_crowding_distance: 0.18615701079997016', 'NSGA-II_rank: 1', 'change: 0.04083326991389189', 'is_elite: True']\n", + "Id: 52_28 Identity: {'ancestor_count': 49, 'ancestor_ids': ['1_1', '51_23'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_28', 'origin': '1_1~CUW~51_23#MGNP'} Metrics: ['ELUC: -1.7825482212525912', 'NSGA-II_crowding_distance: 0.1717476854432568', 'NSGA-II_rank: 2', 'change: 0.053807600112389456', 'is_elite: False']\n", + "Id: 52_11 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '50_30'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_11', 'origin': '51_84~CUW~50_30#MGNP'} Metrics: ['ELUC: -1.8700797283256585', 'NSGA-II_crowding_distance: 0.36917401838534425', 'NSGA-II_rank: 5', 'change: 0.10973492230555479', 'is_elite: False']\n", + "Id: 52_89 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '51_23'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_89', 'origin': '51_67~CUW~51_23#MGNP'} Metrics: ['ELUC: -2.062661112254613', 'NSGA-II_crowding_distance: 0.255767448714428', 'NSGA-II_rank: 3', 'change: 0.05552624604807671', 'is_elite: False']\n", + "Id: 52_12 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '51_99'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_12', 'origin': '1_1~CUW~51_99#MGNP'} Metrics: ['ELUC: -2.2188549480762982', 'NSGA-II_crowding_distance: 0.08829860476290524', 'NSGA-II_rank: 2', 'change: 0.05518988366334767', 'is_elite: False']\n", + "Id: 52_40 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '1_1'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_40', 'origin': '49_34~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.457663243035925', 'NSGA-II_crowding_distance: 0.17899660872981038', 'NSGA-II_rank: 3', 'change: 0.07200051884080068', 'is_elite: False']\n", + "Id: 52_41 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '51_99'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_41', 'origin': '51_67~CUW~51_99#MGNP'} Metrics: ['ELUC: -2.633262673851377', 'NSGA-II_crowding_distance: 0.18194104220546564', 'NSGA-II_rank: 3', 'change: 0.09130596842677821', 'is_elite: False']\n", + "Id: 52_42 Identity: {'ancestor_count': 49, 'ancestor_ids': ['1_1', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_42', 'origin': '1_1~CUW~51_44#MGNP'} Metrics: ['ELUC: -2.7966701289610914', 'NSGA-II_crowding_distance: 0.18763266428458852', 'NSGA-II_rank: 2', 'change: 0.06217413368864493', 'is_elite: False']\n", + "Id: 52_34 Identity: {'ancestor_count': 4, 'ancestor_ids': ['51_15', '51_15'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_34', 'origin': '51_15~CUW~51_15#MGNP'} Metrics: ['ELUC: -2.9454301602538098', 'NSGA-II_crowding_distance: 0.20113692522190843', 'NSGA-II_rank: 1', 'change: 0.048179946181128565', 'is_elite: True']\n", + "Id: 52_98 Identity: {'ancestor_count': 48, 'ancestor_ids': ['51_15', '50_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_98', 'origin': '51_15~CUW~50_49#MGNP'} Metrics: ['ELUC: -3.3394736065312545', 'NSGA-II_crowding_distance: 0.38411549327279926', 'NSGA-II_rank: 5', 'change: 0.11022474208975998', 'is_elite: False']\n", + "Id: 52_46 Identity: {'ancestor_count': 48, 'ancestor_ids': ['51_99', '51_15'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_46', 'origin': '51_99~CUW~51_15#MGNP'} Metrics: ['ELUC: -3.4422987130319913', 'NSGA-II_crowding_distance: 0.13079990604251793', 'NSGA-II_rank: 1', 'change: 0.06552415467326553', 'is_elite: False']\n", + "Id: 52_80 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_99', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_80', 'origin': '51_99~CUW~51_44#MGNP'} Metrics: ['ELUC: -3.6691265156426796', 'NSGA-II_crowding_distance: 0.6334700889127596', 'NSGA-II_rank: 4', 'change: 0.09891281217818451', 'is_elite: False']\n", + "Id: 52_27 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_30', '49_34'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_27', 'origin': '50_30~CUW~49_34#MGNP'} Metrics: ['ELUC: -3.8042221926571695', 'NSGA-II_crowding_distance: 0.18336812465155794', 'NSGA-II_rank: 2', 'change: 0.0820840775805941', 'is_elite: False']\n", + "Id: 52_38 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '51_15'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_38', 'origin': '1_1~CUW~51_15#MGNP'} Metrics: ['ELUC: -3.984641319111159', 'NSGA-II_crowding_distance: 0.14362746881267718', 'NSGA-II_rank: 3', 'change: 0.09185157526861774', 'is_elite: False']\n", + "Id: 52_26 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '50_89'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_26', 'origin': '49_34~CUW~50_89#MGNP'} Metrics: ['ELUC: -4.165428468252944', 'NSGA-II_crowding_distance: 0.07000626160679622', 'NSGA-II_rank: 1', 'change: 0.06650397593528214', 'is_elite: False']\n", + "Id: 50_30 Identity: {'ancestor_count': 47, 'ancestor_ids': ['1_1', '49_13'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_30', 'origin': '1_1~CUW~49_13#MGNP'} Metrics: ['ELUC: -4.477716577019264', 'NSGA-II_crowding_distance: 0.05334787784192947', 'NSGA-II_rank: 1', 'change: 0.06884110276893476', 'is_elite: False']\n", + "Id: 52_67 Identity: {'ancestor_count': 48, 'ancestor_ids': ['51_15', '51_99'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_67', 'origin': '51_15~CUW~51_99#MGNP'} Metrics: ['ELUC: -4.478279534205337', 'NSGA-II_crowding_distance: 0.1681132029417316', 'NSGA-II_rank: 2', 'change: 0.086340316600263', 'is_elite: False']\n", + "Id: 52_16 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_23', '51_90'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_16', 'origin': '51_23~CUW~51_90#MGNP'} Metrics: ['ELUC: -4.497522318332815', 'NSGA-II_crowding_distance: 0.3399779647361068', 'NSGA-II_rank: 5', 'change: 0.12894411038070172', 'is_elite: False']\n", + "Id: 52_95 Identity: {'ancestor_count': 48, 'ancestor_ids': ['51_99', '50_30'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_95', 'origin': '51_99~CUW~50_30#MGNP'} Metrics: ['ELUC: -4.529650868557126', 'NSGA-II_crowding_distance: 0.2096614807992904', 'NSGA-II_rank: 3', 'change: 0.0949250628015255', 'is_elite: False']\n", + "Id: 52_14 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_99', '51_23'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_14', 'origin': '51_99~CUW~51_23#MGNP'} Metrics: ['ELUC: -4.5637205528622795', 'NSGA-II_crowding_distance: 0.06558648552422094', 'NSGA-II_rank: 1', 'change: 0.07566265437576397', 'is_elite: False']\n", + "Id: 52_66 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_23', '51_52'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_66', 'origin': '51_23~CUW~51_52#MGNP'} Metrics: ['ELUC: -4.752044127042042', 'NSGA-II_crowding_distance: 1.440723343228794', 'NSGA-II_rank: 6', 'change: 0.18436433404074798', 'is_elite: False']\n", + "Id: 52_68 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '1_1'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_68', 'origin': '49_34~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.756147555064105', 'NSGA-II_crowding_distance: 0.12430837969949812', 'NSGA-II_rank: 1', 'change: 0.08368558891250154', 'is_elite: False']\n", + "Id: 52_62 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_23', '51_84'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_62', 'origin': '51_23~CUW~51_84#MGNP'} Metrics: ['ELUC: -5.342149705935714', 'NSGA-II_crowding_distance: 0.788556836410496', 'NSGA-II_rank: 5', 'change: 0.13478124163659247', 'is_elite: False']\n", + "Id: 52_86 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_87', '51_84'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_86', 'origin': '51_87~CUW~51_84#MGNP'} Metrics: ['ELUC: -5.509505863471989', 'NSGA-II_crowding_distance: 1.1305959197574846', 'NSGA-II_rank: 5', 'change: 0.2709131188832596', 'is_elite: False']\n", + "Id: 52_19 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_27', '1_1'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_19', 'origin': '51_27~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.653399458465187', 'NSGA-II_crowding_distance: 0.9610199913012637', 'NSGA-II_rank: 4', 'change: 0.12251080658229006', 'is_elite: False']\n", + "Id: 52_99 Identity: {'ancestor_count': 48, 'ancestor_ids': ['51_99', '51_99'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_99', 'origin': '51_99~CUW~51_99#MGNP'} Metrics: ['ELUC: -5.972395135093029', 'NSGA-II_crowding_distance: 0.1418452644221956', 'NSGA-II_rank: 2', 'change: 0.09421470479937358', 'is_elite: False']\n", + "Id: 52_58 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_30', '51_99'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_58', 'origin': '50_30~CUW~51_99#MGNP'} Metrics: ['ELUC: -6.100928438625783', 'NSGA-II_crowding_distance: 0.06312149881577304', 'NSGA-II_rank: 2', 'change: 0.09988398277618242', 'is_elite: False']\n", + "Id: 52_70 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_23', '49_34'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_70', 'origin': '51_23~CUW~49_34#MGNP'} Metrics: ['ELUC: -6.119758641953905', 'NSGA-II_crowding_distance: 0.09303150505842812', 'NSGA-II_rank: 1', 'change: 0.08634705869510388', 'is_elite: False']\n", + "Id: 52_76 Identity: {'ancestor_count': 50, 'ancestor_ids': ['49_34', '51_27'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_76', 'origin': '49_34~CUW~51_27#MGNP'} Metrics: ['ELUC: -6.17172378215341', 'NSGA-II_crowding_distance: 0.2925220646458808', 'NSGA-II_rank: 3', 'change: 0.10727153956312936', 'is_elite: False']\n", + "Id: 51_99 Identity: {'ancestor_count': 47, 'ancestor_ids': ['49_27', '50_43'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_99', 'origin': '49_27~CUW~50_43#MGNP'} Metrics: ['ELUC: -6.186371414136155', 'NSGA-II_crowding_distance: 0.07314260034685825', 'NSGA-II_rank: 1', 'change: 0.08717277711904657', 'is_elite: False']\n", + "Id: 52_13 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_87', '51_99'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_13', 'origin': '51_87~CUW~51_99#MGNP'} Metrics: ['ELUC: -6.37760233957402', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29600256300092587', 'is_elite: False']\n", + "Id: 52_47 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '51_99'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_47', 'origin': '51_84~CUW~51_99#MGNP'} Metrics: ['ELUC: -6.455598026835996', 'NSGA-II_crowding_distance: 0.2676870935250507', 'NSGA-II_rank: 3', 'change: 0.13606984678213824', 'is_elite: False']\n", + "Id: 52_74 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_99', '51_23'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_74', 'origin': '51_99~CUW~51_23#MGNP'} Metrics: ['ELUC: -6.458949111225433', 'NSGA-II_crowding_distance: 0.08502984747101912', 'NSGA-II_rank: 2', 'change: 0.10401077795583737', 'is_elite: False']\n", + "Id: 52_75 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '50_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_75', 'origin': '1_1~CUW~50_49#MGNP'} Metrics: ['ELUC: -6.496710920933156', 'NSGA-II_crowding_distance: 0.14116619526637472', 'NSGA-II_rank: 2', 'change: 0.11723514211613721', 'is_elite: False']\n", + "Id: 52_57 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '50_89'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_57', 'origin': '2_49~CUW~50_89#MGNP'} Metrics: ['ELUC: -6.574642020527621', 'NSGA-II_crowding_distance: 0.910303335413464', 'NSGA-II_rank: 6', 'change: 0.2856485674894928', 'is_elite: False']\n", + "Id: 52_55 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '50_89'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_55', 'origin': '51_67~CUW~50_89#MGNP'} Metrics: ['ELUC: -6.8063094114314655', 'NSGA-II_crowding_distance: 0.20991072199346367', 'NSGA-II_rank: 2', 'change: 0.137773406937211', 'is_elite: False']\n", + "Id: 52_56 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '49_34'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_56', 'origin': '49_34~CUW~49_34#MGNP'} Metrics: ['ELUC: -7.015864437238174', 'NSGA-II_crowding_distance: 0.1352897644424378', 'NSGA-II_rank: 1', 'change: 0.09296398911292077', 'is_elite: False']\n", + "Id: 52_44 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_30', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_44', 'origin': '50_30~CUW~51_87#MGNP'} Metrics: ['ELUC: -7.239828700008316', 'NSGA-II_crowding_distance: 0.9751902368805586', 'NSGA-II_rank: 4', 'change: 0.2433438606119321', 'is_elite: False']\n", + "Id: 52_54 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_99', '51_50'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_54', 'origin': '51_99~CUW~51_50#MGNP'} Metrics: ['ELUC: -7.571960448054947', 'NSGA-II_crowding_distance: 0.0907341599923208', 'NSGA-II_rank: 1', 'change: 0.10402635491183293', 'is_elite: False']\n", + "Id: 52_39 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '51_84'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_39', 'origin': '1_1~CUW~51_84#MGNP'} Metrics: ['ELUC: -7.717744719822743', 'NSGA-II_crowding_distance: 0.3732413351944207', 'NSGA-II_rank: 3', 'change: 0.14869781121632353', 'is_elite: False']\n", + "Id: 49_34 Identity: {'ancestor_count': 47, 'ancestor_ids': ['48_41', '48_88'], 'birth_generation': 49, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '49_34', 'origin': '48_41~CUW~48_88#MGNP'} Metrics: ['ELUC: -7.945641163428854', 'NSGA-II_crowding_distance: 0.15410535599626551', 'NSGA-II_rank: 1', 'change: 0.10425844281622342', 'is_elite: False']\n", + "Id: 52_87 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_49', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_87', 'origin': '50_49~CUW~51_87#MGNP'} Metrics: ['ELUC: -8.089737889040121', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29174463309217935', 'is_elite: False']\n", + "Id: 52_85 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_23', '51_52'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_85', 'origin': '51_23~CUW~51_52#MGNP'} Metrics: ['ELUC: -8.724236266255502', 'NSGA-II_crowding_distance: 0.3086993060636933', 'NSGA-II_rank: 2', 'change: 0.1400585198102762', 'is_elite: False']\n", + "Id: 52_33 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_49', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_33', 'origin': '50_49~CUW~51_44#MGNP'} Metrics: ['ELUC: -9.087431681374152', 'NSGA-II_crowding_distance: 0.3266989147757491', 'NSGA-II_rank: 1', 'change: 0.12428994495768048', 'is_elite: True']\n", + "Id: 52_92 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '2_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_92', 'origin': '51_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.21801443930434', 'NSGA-II_crowding_distance: 0.42949396657012595', 'NSGA-II_rank: 4', 'change: 0.2702368981709057', 'is_elite: False']\n", + "Id: 52_21 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '51_43'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_21', 'origin': '2_49~CUW~51_43#MGNP'} Metrics: ['ELUC: -9.456325369421297', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2760118299148929', 'is_elite: False']\n", + "Id: 52_96 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_87', '49_34'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_96', 'origin': '51_87~CUW~49_34#MGNP'} Metrics: ['ELUC: -10.456358144237914', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2757352828425235', 'is_elite: False']\n", + "Id: 52_52 Identity: {'ancestor_count': 49, 'ancestor_ids': ['49_34', '51_90'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_52', 'origin': '49_34~CUW~51_90#MGNP'} Metrics: ['ELUC: -10.609194696864389', 'NSGA-II_crowding_distance: 0.5883564579480807', 'NSGA-II_rank: 3', 'change: 0.15898343843605928', 'is_elite: False']\n", + "Id: 52_37 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '1_1'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_37', 'origin': '51_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.891027439964793', 'NSGA-II_crowding_distance: 0.24703875869036568', 'NSGA-II_rank: 2', 'change: 0.15839382047472766', 'is_elite: False']\n", + "Id: 52_72 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_87', '50_68'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_72', 'origin': '51_87~CUW~50_68#MGNP'} Metrics: ['ELUC: -11.176351356449757', 'NSGA-II_crowding_distance: 0.5275142797533887', 'NSGA-II_rank: 3', 'change: 0.23869330096104774', 'is_elite: False']\n", + "Id: 52_71 Identity: {'ancestor_count': 50, 'ancestor_ids': ['49_34', '51_84'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_71', 'origin': '49_34~CUW~51_84#MGNP'} Metrics: ['ELUC: -11.393765249667702', 'NSGA-II_crowding_distance: 0.3875999628528483', 'NSGA-II_rank: 2', 'change: 0.1661505109403575', 'is_elite: False']\n", + "Id: 52_20 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_15', '51_43'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_20', 'origin': '51_15~CUW~51_43#MGNP'} Metrics: ['ELUC: -11.483420638116185', 'NSGA-II_crowding_distance: 0.37342458634301195', 'NSGA-II_rank: 2', 'change: 0.2568785089558285', 'is_elite: False']\n", + "Id: 51_44 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_78', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_44', 'origin': '50_78~CUW~50_49#MGNP'} Metrics: ['ELUC: -11.862327513770609', 'NSGA-II_crowding_distance: 0.26879414704404636', 'NSGA-II_rank: 1', 'change: 0.13527074393301133', 'is_elite: True']\n", + "Id: 52_73 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_73', 'origin': '51_67~CUW~51_87#MGNP'} Metrics: ['ELUC: -11.960367710150743', 'NSGA-II_crowding_distance: 0.21568907096681258', 'NSGA-II_rank: 2', 'change: 0.2610994207626682', 'is_elite: False']\n", + "Id: 52_43 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_50', '51_84'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_43', 'origin': '51_50~CUW~51_84#MGNP'} Metrics: ['ELUC: -11.991332921043824', 'NSGA-II_crowding_distance: 0.10286855021996678', 'NSGA-II_rank: 1', 'change: 0.1552120292633003', 'is_elite: False']\n", + "Id: 52_60 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_87', '51_50'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_60', 'origin': '51_87~CUW~51_50#MGNP'} Metrics: ['ELUC: -12.240524576788728', 'NSGA-II_crowding_distance: 0.31131493699547913', 'NSGA-II_rank: 3', 'change: 0.26530531400483337', 'is_elite: False']\n", + "Id: 52_79 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '51_50'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_79', 'origin': '51_67~CUW~51_50#MGNP'} Metrics: ['ELUC: -12.476149724716862', 'NSGA-II_crowding_distance: 0.10561134207871692', 'NSGA-II_rank: 1', 'change: 0.15554767474846448', 'is_elite: False']\n", + "Id: 51_67 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_73', '50_89'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_67', 'origin': '50_73~CUW~50_89#MGNP'} Metrics: ['ELUC: -12.95325825407435', 'NSGA-II_crowding_distance: 0.16154786545154215', 'NSGA-II_rank: 1', 'change: 0.1703999307886106', 'is_elite: False']\n", + "Id: 52_17 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '51_67'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_17', 'origin': '51_84~CUW~51_67#MGNP'} Metrics: ['ELUC: -13.374591151721548', 'NSGA-II_crowding_distance: 0.12791026230206373', 'NSGA-II_rank: 1', 'change: 0.18850312971667466', 'is_elite: False']\n", + "Id: 52_69 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_68', '2_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_69', 'origin': '50_68~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.77313149732805', 'NSGA-II_crowding_distance: 0.3197775116050264', 'NSGA-II_rank: 3', 'change: 0.2729389524525995', 'is_elite: False']\n", + "Id: 52_15 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '51_67'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_15', 'origin': '51_84~CUW~51_67#MGNP'} Metrics: ['ELUC: -14.004700707716989', 'NSGA-II_crowding_distance: 0.07672691627485409', 'NSGA-II_rank: 1', 'change: 0.19072220004005896', 'is_elite: False']\n", + "Id: 51_84 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_86', '50_30'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_84', 'origin': '50_86~CUW~50_30#MGNP'} Metrics: ['ELUC: -14.026066418554128', 'NSGA-II_crowding_distance: 0.15838328936809082', 'NSGA-II_rank: 1', 'change: 0.20034099558376334', 'is_elite: False']\n", + "Id: 52_59 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_90', '49_34'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_59', 'origin': '51_90~CUW~49_34#MGNP'} Metrics: ['ELUC: -14.516709246115196', 'NSGA-II_crowding_distance: 0.2599219406630586', 'NSGA-II_rank: 1', 'change: 0.22929130123537028', 'is_elite: True']\n", + "Id: 52_29 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_52', '51_90'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_29', 'origin': '51_52~CUW~51_90#MGNP'} Metrics: ['ELUC: -14.836958223057703', 'NSGA-II_crowding_distance: 0.28821583337022993', 'NSGA-II_rank: 2', 'change: 0.2632921414964447', 'is_elite: False']\n", + "Id: 52_25 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_87', '51_43'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_25', 'origin': '51_87~CUW~51_43#MGNP'} Metrics: ['ELUC: -15.118690674870264', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2968051964894366', 'is_elite: False']\n", + "Id: 52_88 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_90', '50_30'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_88', 'origin': '51_90~CUW~50_30#MGNP'} Metrics: ['ELUC: -15.14752481935819', 'NSGA-II_crowding_distance: 0.16547292511748177', 'NSGA-II_rank: 1', 'change: 0.25886441549508754', 'is_elite: False']\n", + "Id: 52_24 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_87', '51_15'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_24', 'origin': '51_87~CUW~51_15#MGNP'} Metrics: ['ELUC: -15.181149716425253', 'NSGA-II_crowding_distance: 0.2878554808327445', 'NSGA-II_rank: 2', 'change: 0.2898395808244691', 'is_elite: False']\n", + "Id: 52_22 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '51_90'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_22', 'origin': '51_67~CUW~51_90#MGNP'} Metrics: ['ELUC: -15.562951072256725', 'NSGA-II_crowding_distance: 0.1429730081711971', 'NSGA-II_rank: 1', 'change: 0.2609096882147985', 'is_elite: False']\n", + "Id: 52_53 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_99', '51_90'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_53', 'origin': '51_99~CUW~51_90#MGNP'} Metrics: ['ELUC: -16.39662010217506', 'NSGA-II_crowding_distance: 0.17422093289612312', 'NSGA-II_rank: 1', 'change: 0.28032684300981403', 'is_elite: True']\n", + "Id: 52_84 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_30', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_84', 'origin': '50_30~CUW~51_87#MGNP'} Metrics: ['ELUC: -16.906442708529617', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3103558443767988', 'is_elite: False']\n", + "Id: 52_18 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_68', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_18', 'origin': '50_68~CUW~51_87#MGNP'} Metrics: ['ELUC: -17.014289929652776', 'NSGA-II_crowding_distance: 0.14431198977952106', 'NSGA-II_rank: 1', 'change: 0.2882636643022671', 'is_elite: False']\n", + "Id: 52_30 Identity: {'ancestor_count': 49, 'ancestor_ids': ['1_1', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_30', 'origin': '1_1~CUW~51_87#MGNP'} Metrics: ['ELUC: -17.597037193976984', 'NSGA-II_crowding_distance: 0.08262055399354541', 'NSGA-II_rank: 1', 'change: 0.30301487669899596', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 51_87 Identity: {'ancestor_count': 48, 'ancestor_ids': ['2_49', '49_34'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_87', 'origin': '2_49~CUW~49_34#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 52_23 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_43', '51_67'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_23', 'origin': '51_43~CUW~51_67#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 52_63 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_63', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 52_77 Identity: {'ancestor_count': 49, 'ancestor_ids': ['2_49', '51_87'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_77', 'origin': '2_49~CUW~51_87#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 52_83 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_83', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 52.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 53...:\n", + "PopulationResponse:\n", + " Generation: 53\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/53/20240220-020242\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 53 and asking ESP for generation 54...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 53 data persisted.\n", + "Evaluated candidates:\n", + "Id: 53_81 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '51_67'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_81', 'origin': '2_49~CUW~51_67#MGNP'} Metrics: ['ELUC: 23.796212255680373', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 16', 'change: 0.30329291324944335', 'is_elite: False']\n", + "Id: 53_60 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_60', 'origin': '52_33~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.258614485868144', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.30277952583226236', 'is_elite: False']\n", + "Id: 53_46 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_46', 'origin': '52_33~CUW~2_49#MGNP'} Metrics: ['ELUC: 19.88987973181848', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.2844305843447695', 'is_elite: False']\n", + "Id: 53_88 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_53', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_88', 'origin': '52_53~CUW~2_49#MGNP'} Metrics: ['ELUC: 16.226560608067782', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.28395414763682353', 'is_elite: False']\n", + "Id: 53_66 Identity: {'ancestor_count': 49, 'ancestor_ids': ['52_83', '52_46'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_66', 'origin': '52_83~CUW~52_46#MGNP'} Metrics: ['ELUC: 16.087688591240518', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2852334889502209', 'is_elite: False']\n", + "Id: 53_62 Identity: {'ancestor_count': 49, 'ancestor_ids': ['52_83', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_62', 'origin': '52_83~CUW~51_44#MGNP'} Metrics: ['ELUC: 15.60494794660268', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2773562347209363', 'is_elite: False']\n", + "Id: 53_27 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_83', '52_61'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_27', 'origin': '52_83~CUW~52_61#MGNP'} Metrics: ['ELUC: 15.18223951950408', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27380730170312656', 'is_elite: False']\n", + "Id: 53_29 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_83', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_29', 'origin': '52_83~CUW~52_33#MGNP'} Metrics: ['ELUC: 5.418220050896998', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.267558652783512', 'is_elite: False']\n", + "Id: 53_45 Identity: {'ancestor_count': 50, 'ancestor_ids': ['50_89', '51_84'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_45', 'origin': '50_89~CUW~51_84#MGNP'} Metrics: ['ELUC: 4.480832809195354', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.10837175420409385', 'is_elite: False']\n", + "Id: 53_53 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_18', '52_61'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_53', 'origin': '52_18~CUW~52_61#MGNP'} Metrics: ['ELUC: 3.9667655349828737', 'NSGA-II_crowding_distance: 1.6394250697733659', 'NSGA-II_rank: 9', 'change: 0.19829392885137578', 'is_elite: False']\n", + "Id: 53_22 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_61'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_22', 'origin': '52_33~CUW~52_61#MGNP'} Metrics: ['ELUC: 2.02344746319768', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.0709354149366452', 'is_elite: False']\n", + "Id: 53_19 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '50_89'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_19', 'origin': '52_33~CUW~50_89#MGNP'} Metrics: ['ELUC: 1.5155102208599978', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.10655362427964853', 'is_elite: False']\n", + "Id: 53_79 Identity: {'ancestor_count': 51, 'ancestor_ids': ['52_34', '52_17'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_79', 'origin': '52_34~CUW~52_17#MGNP'} Metrics: ['ELUC: 0.824514207956752', 'NSGA-II_crowding_distance: 1.4195409834384902', 'NSGA-II_rank: 7', 'change: 0.09857387922985228', 'is_elite: False']\n", + "Id: 53_55 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '50_89'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_55', 'origin': '51_44~CUW~50_89#MGNP'} Metrics: ['ELUC: 0.5453235099717075', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.06935228609049372', 'is_elite: False']\n", + "Id: 53_21 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_21', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.4591445682102639', 'NSGA-II_crowding_distance: 1.5149837286585899', 'NSGA-II_rank: 9', 'change: 0.30955450248688643', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 53_14 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_61'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_14', 'origin': '52_33~CUW~52_61#MGNP'} Metrics: ['ELUC: -0.029274562231481845', 'NSGA-II_crowding_distance: 1.2333415189341648', 'NSGA-II_rank: 6', 'change: 0.09859342514101958', 'is_elite: False']\n", + "Id: 53_59 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_18', '52_53'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_59', 'origin': '52_18~CUW~52_53#MGNP'} Metrics: ['ELUC: -0.12290785496770097', 'NSGA-II_crowding_distance: 1.433799941085999', 'NSGA-II_rank: 8', 'change: 0.22848589175518205', 'is_elite: False']\n", + "Id: 53_44 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_44', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.6997049370833317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3414601101775704', 'is_elite: False']\n", + "Id: 53_26 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '52_61'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_26', 'origin': '1_1~CUW~52_61#MGNP'} Metrics: ['ELUC: -0.7798961412040353', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.059416586883989875', 'is_elite: False']\n", + "Id: 50_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_89', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8753352639217634', 'NSGA-II_crowding_distance: 0.19783024934987475', 'NSGA-II_rank: 1', 'change: 0.027764991111589848', 'is_elite: True']\n", + "Id: 53_90 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_34', '52_61'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_90', 'origin': '52_34~CUW~52_61#MGNP'} Metrics: ['ELUC: -1.0095166844570107', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0460948530499805', 'is_elite: False']\n", + "Id: 53_98 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '50_89'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_98', 'origin': '1_1~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.1115224420328809', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.043190669424334006', 'is_elite: False']\n", + "Id: 53_70 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_59'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_70', 'origin': '1_1~CUW~52_59#MGNP'} Metrics: ['ELUC: -1.1859056977877402', 'NSGA-II_crowding_distance: 0.13697751096224847', 'NSGA-II_rank: 3', 'change: 0.05137904936903001', 'is_elite: False']\n", + "Id: 53_32 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_34', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_32', 'origin': '52_34~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.307008428360939', 'NSGA-II_crowding_distance: 0.9983643129039126', 'NSGA-II_rank: 8', 'change: 0.2673923350236247', 'is_elite: False']\n", + "Id: 53_20 Identity: {'ancestor_count': 2, 'ancestor_ids': ['50_89', '1_1'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_20', 'origin': '50_89~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.3348135372978938', 'NSGA-II_crowding_distance: 0.13192370676729265', 'NSGA-II_rank: 2', 'change: 0.043241776316564985', 'is_elite: False']\n", + "Id: 52_61 Identity: {'ancestor_count': 4, 'ancestor_ids': ['51_15', '50_89'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_61', 'origin': '51_15~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.360787233396522', 'NSGA-II_crowding_distance: 0.11975943216609572', 'NSGA-II_rank: 1', 'change: 0.04083326991389189', 'is_elite: False']\n", + "Id: 53_31 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_88', '51_67'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_31', 'origin': '52_88~CUW~51_67#MGNP'} Metrics: ['ELUC: -1.5441058705174118', 'NSGA-II_crowding_distance: 1.0015865237353723', 'NSGA-II_rank: 5', 'change: 0.12943286228872367', 'is_elite: False']\n", + "Id: 53_40 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '52_61'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_40', 'origin': '1_1~CUW~52_61#MGNP'} Metrics: ['ELUC: -1.781876650137207', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05838102856668706', 'is_elite: False']\n", + "Id: 53_77 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_34', '52_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_77', 'origin': '52_34~CUW~52_34#MGNP'} Metrics: ['ELUC: -1.816329779890014', 'NSGA-II_crowding_distance: 0.11474903594581089', 'NSGA-II_rank: 1', 'change: 0.047529569835663914', 'is_elite: False']\n", + "Id: 53_56 Identity: {'ancestor_count': 49, 'ancestor_ids': ['52_34', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_56', 'origin': '52_34~CUW~51_44#MGNP'} Metrics: ['ELUC: -1.9182796831945608', 'NSGA-II_crowding_distance: 0.2738111307655543', 'NSGA-II_rank: 4', 'change: 0.10569867253095523', 'is_elite: False']\n", + "Id: 53_41 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_53', '1_1'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_41', 'origin': '52_53~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2595439852373107', 'NSGA-II_crowding_distance: 0.16673542274157177', 'NSGA-II_rank: 4', 'change: 0.11575446716444741', 'is_elite: False']\n", + "Id: 53_49 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_61', '50_89'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_49', 'origin': '52_61~CUW~50_89#MGNP'} Metrics: ['ELUC: -2.4382956354542697', 'NSGA-II_crowding_distance: 0.20784652946334697', 'NSGA-II_rank: 3', 'change: 0.05786922004453952', 'is_elite: False']\n", + "Id: 53_18 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_59', '52_61'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_18', 'origin': '52_59~CUW~52_61#MGNP'} Metrics: ['ELUC: -2.6368394925658816', 'NSGA-II_crowding_distance: 0.16912671854678454', 'NSGA-II_rank: 3', 'change: 0.08143522919874761', 'is_elite: False']\n", + "Id: 53_50 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_34', '52_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_50', 'origin': '52_34~CUW~52_34#MGNP'} Metrics: ['ELUC: -2.77357663059724', 'NSGA-II_crowding_distance: 0.12801282031464783', 'NSGA-II_rank: 2', 'change: 0.04990099270370977', 'is_elite: False']\n", + "Id: 53_76 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_89', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_76', 'origin': '50_89~CUW~51_44#MGNP'} Metrics: ['ELUC: -2.8259090863114147', 'NSGA-II_crowding_distance: 0.21520521206905663', 'NSGA-II_rank: 3', 'change: 0.09580761087633805', 'is_elite: False']\n", + "Id: 53_23 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_34', '52_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_23', 'origin': '52_34~CUW~52_34#MGNP'} Metrics: ['ELUC: -2.9334850553237803', 'NSGA-II_crowding_distance: 0.21423502603018754', 'NSGA-II_rank: 2', 'change: 0.049981895808987646', 'is_elite: False']\n", + "Id: 52_34 Identity: {'ancestor_count': 4, 'ancestor_ids': ['51_15', '51_15'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_34', 'origin': '51_15~CUW~51_15#MGNP'} Metrics: ['ELUC: -2.9454301602538098', 'NSGA-II_crowding_distance: 0.13739509557860036', 'NSGA-II_rank: 1', 'change: 0.048179946181128565', 'is_elite: False']\n", + "Id: 53_15 Identity: {'ancestor_count': 50, 'ancestor_ids': ['50_89', '52_59'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_15', 'origin': '50_89~CUW~52_59#MGNP'} Metrics: ['ELUC: -3.0977180716752617', 'NSGA-II_crowding_distance: 0.6702698577590791', 'NSGA-II_rank: 4', 'change: 0.12315395540163289', 'is_elite: False']\n", + "Id: 53_61 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_34', '52_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_61', 'origin': '52_34~CUW~52_34#MGNP'} Metrics: ['ELUC: -3.3428460880988142', 'NSGA-II_crowding_distance: 0.11460872052599673', 'NSGA-II_rank: 1', 'change: 0.06261975224690129', 'is_elite: False']\n", + "Id: 53_47 Identity: {'ancestor_count': 48, 'ancestor_ids': ['52_61', '49_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_47', 'origin': '52_61~CUW~49_34#MGNP'} Metrics: ['ELUC: -3.5078287616247668', 'NSGA-II_crowding_distance: 0.0539823278608976', 'NSGA-II_rank: 1', 'change: 0.07283255668043753', 'is_elite: False']\n", + "Id: 53_84 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_88', '52_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_84', 'origin': '52_88~CUW~52_34#MGNP'} Metrics: ['ELUC: -3.562687489242919', 'NSGA-II_crowding_distance: 0.2601831058096558', 'NSGA-II_rank: 2', 'change: 0.09175641185258182', 'is_elite: False']\n", + "Id: 53_38 Identity: {'ancestor_count': 50, 'ancestor_ids': ['49_34', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_38', 'origin': '49_34~CUW~52_33#MGNP'} Metrics: ['ELUC: -3.6666387939920644', 'NSGA-II_crowding_distance: 0.21763984133559855', 'NSGA-II_rank: 1', 'change: 0.0732320138490511', 'is_elite: True']\n", + "Id: 53_85 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '51_84'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_85', 'origin': '1_1~CUW~51_84#MGNP'} Metrics: ['ELUC: -3.713324886225709', 'NSGA-II_crowding_distance: 0.5585663233384931', 'NSGA-II_rank: 3', 'change: 0.11979441102660637', 'is_elite: False']\n", + "Id: 53_91 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_83', '52_59'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_91', 'origin': '52_83~CUW~52_59#MGNP'} Metrics: ['ELUC: -4.359673487276338', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2752561931947496', 'is_elite: False']\n", + "Id: 53_63 Identity: {'ancestor_count': 49, 'ancestor_ids': ['52_34', '52_46'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_63', 'origin': '52_34~CUW~52_46#MGNP'} Metrics: ['ELUC: -4.373200354195961', 'NSGA-II_crowding_distance: 0.17338171545176206', 'NSGA-II_rank: 2', 'change: 0.0930119187739852', 'is_elite: False']\n", + "Id: 53_39 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '51_84'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_39', 'origin': '1_1~CUW~51_84#MGNP'} Metrics: ['ELUC: -4.694841423495968', 'NSGA-II_crowding_distance: 1.4785378886577343', 'NSGA-II_rank: 7', 'change: 0.1980483449855543', 'is_elite: False']\n", + "Id: 53_94 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_59', '52_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_94', 'origin': '52_59~CUW~52_34#MGNP'} Metrics: ['ELUC: -5.144286318088904', 'NSGA-II_crowding_distance: 0.2046377392918866', 'NSGA-II_rank: 2', 'change: 0.11034575098442376', 'is_elite: False']\n", + "Id: 53_78 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '51_67'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_78', 'origin': '2_49~CUW~51_67#MGNP'} Metrics: ['ELUC: -5.294225573297285', 'NSGA-II_crowding_distance: 0.4861142898993633', 'NSGA-II_rank: 7', 'change: 0.2506266408242962', 'is_elite: False']\n", + "Id: 53_35 Identity: {'ancestor_count': 50, 'ancestor_ids': ['50_89', '52_88'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_35', 'origin': '50_89~CUW~52_88#MGNP'} Metrics: ['ELUC: -5.958226066254868', 'NSGA-II_crowding_distance: 0.37613363805162336', 'NSGA-II_rank: 2', 'change: 0.1195183545030889', 'is_elite: False']\n", + "Id: 53_30 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_83', '52_53'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_30', 'origin': '52_83~CUW~52_53#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.24278106877586686', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 53_43 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '49_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_43', 'origin': '1_1~CUW~49_34#MGNP'} Metrics: ['ELUC: -6.425940799961196', 'NSGA-II_crowding_distance: 0.23364450661949485', 'NSGA-II_rank: 1', 'change: 0.08825017453575823', 'is_elite: True']\n", + "Id: 53_83 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '50_89'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_83', 'origin': '49_34~CUW~50_89#MGNP'} Metrics: ['ELUC: -6.710565412763305', 'NSGA-II_crowding_distance: 0.2721587000426509', 'NSGA-II_rank: 1', 'change: 0.09128995494909606', 'is_elite: True']\n", + "Id: 53_92 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_83', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_92', 'origin': '52_83~CUW~52_33#MGNP'} Metrics: ['ELUC: -6.712389823806868', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.26634593045431865', 'is_elite: False']\n", + "Id: 53_36 Identity: {'ancestor_count': 51, 'ancestor_ids': ['52_17', '1_1'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_36', 'origin': '52_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.199266751513532', 'NSGA-II_crowding_distance: 1.6445314895356415', 'NSGA-II_rank: 6', 'change: 0.1720094671349278', 'is_elite: False']\n", + "Id: 53_54 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '49_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_54', 'origin': '51_84~CUW~49_34#MGNP'} Metrics: ['ELUC: -8.55051912919964', 'NSGA-II_crowding_distance: 1.624070950153392', 'NSGA-II_rank: 5', 'change: 0.14046390205421802', 'is_elite: False']\n", + "Id: 52_33 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_49', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_33', 'origin': '50_49~CUW~51_44#MGNP'} Metrics: ['ELUC: -9.087431681374152', 'NSGA-II_crowding_distance: 0.27204101122711327', 'NSGA-II_rank: 1', 'change: 0.12428994495768048', 'is_elite: True']\n", + "Id: 53_25 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '52_83'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_25', 'origin': '1_1~CUW~52_83#MGNP'} Metrics: ['ELUC: -9.093638696454136', 'NSGA-II_crowding_distance: 0.7416773311545072', 'NSGA-II_rank: 6', 'change: 0.28534621060570314', 'is_elite: False']\n", + "Id: 53_51 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_67', '50_89'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_51', 'origin': '51_67~CUW~50_89#MGNP'} Metrics: ['ELUC: -9.17339608097019', 'NSGA-II_crowding_distance: 0.4157387258738492', 'NSGA-II_rank: 3', 'change: 0.13496039473312643', 'is_elite: False']\n", + "Id: 53_42 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_59', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_42', 'origin': '52_59~CUW~52_33#MGNP'} Metrics: ['ELUC: -9.223894763207468', 'NSGA-II_crowding_distance: 0.0566420687648652', 'NSGA-II_rank: 3', 'change: 0.13557099328746244', 'is_elite: False']\n", + "Id: 53_99 Identity: {'ancestor_count': 51, 'ancestor_ids': ['52_22', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_99', 'origin': '52_22~CUW~52_33#MGNP'} Metrics: ['ELUC: -9.387582051033112', 'NSGA-II_crowding_distance: 0.1119617934707755', 'NSGA-II_rank: 1', 'change: 0.12703113277283126', 'is_elite: False']\n", + "Id: 53_17 Identity: {'ancestor_count': 51, 'ancestor_ids': ['52_22', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_17', 'origin': '52_22~CUW~51_44#MGNP'} Metrics: ['ELUC: -9.404027509981754', 'NSGA-II_crowding_distance: 1.3396386492969463', 'NSGA-II_rank: 4', 'change: 0.13864308190119845', 'is_elite: False']\n", + "Id: 53_28 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '52_53'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_28', 'origin': '51_84~CUW~52_53#MGNP'} Metrics: ['ELUC: -9.687907508280048', 'NSGA-II_crowding_distance: 0.2978500886065776', 'NSGA-II_rank: 2', 'change: 0.1326408174181968', 'is_elite: False']\n", + "Id: 53_95 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_95', 'origin': '52_33~CUW~52_33#MGNP'} Metrics: ['ELUC: -9.753206564703497', 'NSGA-II_crowding_distance: 0.08548915843180431', 'NSGA-II_rank: 2', 'change: 0.13397989987007697', 'is_elite: False']\n", + "Id: 53_72 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_72', 'origin': '52_33~CUW~52_33#MGNP'} Metrics: ['ELUC: -10.009775805820222', 'NSGA-II_crowding_distance: 0.14984762151157394', 'NSGA-II_rank: 3', 'change: 0.13565474661836918', 'is_elite: False']\n", + "Id: 53_52 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_52', 'origin': '52_33~CUW~51_44#MGNP'} Metrics: ['ELUC: -10.56619286215985', 'NSGA-II_crowding_distance: 0.15971565320221548', 'NSGA-II_rank: 1', 'change: 0.1326018160459971', 'is_elite: False']\n", + "Id: 53_68 Identity: {'ancestor_count': 49, 'ancestor_ids': ['2_49', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_68', 'origin': '2_49~CUW~51_44#MGNP'} Metrics: ['ELUC: -10.67992822734237', 'NSGA-II_crowding_distance: 0.17192206461147433', 'NSGA-II_rank: 6', 'change: 0.2871161485811702', 'is_elite: False']\n", + "Id: 53_13 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '52_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_13', 'origin': '51_44~CUW~52_34#MGNP'} Metrics: ['ELUC: -10.829893287562223', 'NSGA-II_crowding_distance: 0.5183338948253897', 'NSGA-II_rank: 3', 'change: 0.1477210884979565', 'is_elite: False']\n", + "Id: 53_100 Identity: {'ancestor_count': 3, 'ancestor_ids': ['52_83', '50_89'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_100', 'origin': '52_83~CUW~50_89#MGNP'} Metrics: ['ELUC: -10.877027615515466', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2888115949984354', 'is_elite: False']\n", + "Id: 53_86 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_86', 'origin': '52_33~CUW~51_44#MGNP'} Metrics: ['ELUC: -10.880221423182507', 'NSGA-II_crowding_distance: 0.4997282599314379', 'NSGA-II_rank: 2', 'change: 0.13512083076098502', 'is_elite: False']\n", + "Id: 53_67 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_84', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_67', 'origin': '51_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.105568468839389', 'NSGA-II_crowding_distance: 0.7095142577521972', 'NSGA-II_rank: 3', 'change: 0.2534936342801173', 'is_elite: False']\n", + "Id: 53_58 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_18'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_58', 'origin': '52_33~CUW~52_18#MGNP'} Metrics: ['ELUC: -11.542628516503402', 'NSGA-II_crowding_distance: 0.6564803149698631', 'NSGA-II_rank: 2', 'change: 0.2324436180446983', 'is_elite: False']\n", + "Id: 53_57 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_57', 'origin': '51_44~CUW~51_44#MGNP'} Metrics: ['ELUC: -11.765449854652156', 'NSGA-II_crowding_distance: 0.08266278332385198', 'NSGA-II_rank: 1', 'change: 0.1343335749150665', 'is_elite: False']\n", + "Id: 53_71 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_59', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_71', 'origin': '52_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.852869295263307', 'NSGA-II_crowding_distance: 0.9517715361853019', 'NSGA-II_rank: 4', 'change: 0.27758518884369177', 'is_elite: False']\n", + "Id: 51_44 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_78', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_44', 'origin': '50_78~CUW~50_49#MGNP'} Metrics: ['ELUC: -11.862327513770609', 'NSGA-II_crowding_distance: 0.2939946924759722', 'NSGA-II_rank: 1', 'change: 0.13527074393301133', 'is_elite: True']\n", + "Id: 53_69 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_34', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_69', 'origin': '52_34~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.936760160324951', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28306313921326287', 'is_elite: False']\n", + "Id: 53_24 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '51_84'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_24', 'origin': '52_33~CUW~51_84#MGNP'} Metrics: ['ELUC: -13.438145890850118', 'NSGA-II_crowding_distance: 0.3578842879358498', 'NSGA-II_rank: 1', 'change: 0.19366887208837358', 'is_elite: True']\n", + "Id: 53_48 Identity: {'ancestor_count': 49, 'ancestor_ids': ['52_46', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_48', 'origin': '52_46~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.126779057078009', 'NSGA-II_crowding_distance: 0.28858382864367255', 'NSGA-II_rank: 4', 'change: 0.2778240798985101', 'is_elite: False']\n", + "Id: 53_74 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_74', 'origin': '51_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.17667861987554', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.30223959712078263', 'is_elite: False']\n", + "Id: 53_75 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_44', '51_84'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_75', 'origin': '51_44~CUW~51_84#MGNP'} Metrics: ['ELUC: -14.278188476493542', 'NSGA-II_crowding_distance: 0.1704610011940866', 'NSGA-II_rank: 1', 'change: 0.20105753474918014', 'is_elite: False']\n", + "Id: 53_93 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_83'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_93', 'origin': '52_33~CUW~52_83#MGNP'} Metrics: ['ELUC: -14.380746230507395', 'NSGA-II_crowding_distance: 0.560353483562219', 'NSGA-II_rank: 3', 'change: 0.2741581791557298', 'is_elite: False']\n", + "Id: 53_96 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_53'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_96', 'origin': '1_1~CUW~52_53#MGNP'} Metrics: ['ELUC: -14.40927849732323', 'NSGA-II_crowding_distance: 0.37761847073479593', 'NSGA-II_rank: 2', 'change: 0.24537046688472725', 'is_elite: False']\n", + "Id: 53_33 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_59', '52_59'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_33', 'origin': '52_59~CUW~52_59#MGNP'} Metrics: ['ELUC: -14.487435575374793', 'NSGA-II_crowding_distance: 0.10819017606244047', 'NSGA-II_rank: 1', 'change: 0.22672386671064276', 'is_elite: False']\n", + "Id: 52_59 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_90', '49_34'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_59', 'origin': '51_90~CUW~49_34#MGNP'} Metrics: ['ELUC: -14.516709246115196', 'NSGA-II_crowding_distance: 0.09829007141114135', 'NSGA-II_rank: 1', 'change: 0.22929130123537028', 'is_elite: False']\n", + "Id: 53_80 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_59', '52_88'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_80', 'origin': '52_59~CUW~52_88#MGNP'} Metrics: ['ELUC: -15.073872219364622', 'NSGA-II_crowding_distance: 0.19467118593484395', 'NSGA-II_rank: 1', 'change: 0.24609942299441587', 'is_elite: False']\n", + "Id: 53_11 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_53'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_11', 'origin': '52_33~CUW~52_53#MGNP'} Metrics: ['ELUC: -15.4106924037782', 'NSGA-II_crowding_distance: 0.26085640900714274', 'NSGA-II_rank: 2', 'change: 0.2660675097619556', 'is_elite: False']\n", + "Id: 53_37 Identity: {'ancestor_count': 49, 'ancestor_ids': ['52_83', '51_44'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_37', 'origin': '52_83~CUW~51_44#MGNP'} Metrics: ['ELUC: -15.580040280474787', 'NSGA-II_crowding_distance: 0.21757995359703652', 'NSGA-II_rank: 2', 'change: 0.2929316895878494', 'is_elite: False']\n", + "Id: 53_65 Identity: {'ancestor_count': 51, 'ancestor_ids': ['52_34', '52_22'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_65', 'origin': '52_34~CUW~52_22#MGNP'} Metrics: ['ELUC: -15.932287724277906', 'NSGA-II_crowding_distance: 0.15429785265173945', 'NSGA-II_rank: 1', 'change: 0.263354041738666', 'is_elite: False']\n", + "Id: 53_34 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_53', '52_59'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_34', 'origin': '52_53~CUW~52_59#MGNP'} Metrics: ['ELUC: -16.264472718853618', 'NSGA-II_crowding_distance: 0.08329263084748444', 'NSGA-II_rank: 1', 'change: 0.2719336062201588', 'is_elite: False']\n", + "Id: 52_53 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_99', '51_90'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_53', 'origin': '51_99~CUW~51_90#MGNP'} Metrics: ['ELUC: -16.39662010217506', 'NSGA-II_crowding_distance: 0.057225448281406376', 'NSGA-II_rank: 1', 'change: 0.28032684300981403', 'is_elite: False']\n", + "Id: 53_12 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_12', 'origin': '2_49~CUW~52_33#MGNP'} Metrics: ['ELUC: -16.496664309213042', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3093755418452973', 'is_elite: False']\n", + "Id: 53_82 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_53', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_82', 'origin': '52_53~CUW~52_33#MGNP'} Metrics: ['ELUC: -16.688818433220053', 'NSGA-II_crowding_distance: 0.10988201790582203', 'NSGA-II_rank: 1', 'change: 0.2818071271398224', 'is_elite: False']\n", + "Id: 53_16 Identity: {'ancestor_count': 3, 'ancestor_ids': ['52_83', '52_83'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_16', 'origin': '52_83~CUW~52_83#MGNP'} Metrics: ['ELUC: -16.848214247273116', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2982660702301948', 'is_elite: False']\n", + "Id: 53_73 Identity: {'ancestor_count': 2, 'ancestor_ids': ['50_89', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_73', 'origin': '50_89~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.36567033989981', 'NSGA-II_crowding_distance: 0.12275884432342925', 'NSGA-II_rank: 1', 'change: 0.29666810719891556', 'is_elite: False']\n", + "Id: 53_89 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '52_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_89', 'origin': '2_49~CUW~52_34#MGNP'} Metrics: ['ELUC: -17.59724700497802', 'NSGA-II_crowding_distance: 0.034468577318999875', 'NSGA-II_rank: 1', 'change: 0.3030193177168888', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 52_83 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_83', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 53_64 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_64', 'origin': '2_49~CUW~52_33#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 53_87 Identity: {'ancestor_count': 3, 'ancestor_ids': ['52_83', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_87', 'origin': '52_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 53_97 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_97', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 53.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 54...:\n", + "PopulationResponse:\n", + " Generation: 54\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/54/20240220-020957\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 54 and asking ESP for generation 55...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 54 data persisted.\n", + "Evaluated candidates:\n", + "Id: 54_12 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_97', '53_83'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_12', 'origin': '53_97~CUW~53_83#MGNP'} Metrics: ['ELUC: 16.069187657400143', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2711327701578747', 'is_elite: False']\n", + "Id: 54_79 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_52', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_79', 'origin': '53_52~CUW~53_97#MGNP'} Metrics: ['ELUC: 15.617241525815365', 'NSGA-II_crowding_distance: 1.7591050695114558', 'NSGA-II_rank: 9', 'change: 0.28662338350416783', 'is_elite: False']\n", + "Id: 54_15 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_83', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_15', 'origin': '53_83~CUW~2_49#MGNP'} Metrics: ['ELUC: 10.33883677638097', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26953603835602014', 'is_elite: False']\n", + "Id: 54_73 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_77', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_73', 'origin': '53_77~CUW~53_24#MGNP'} Metrics: ['ELUC: 6.950842978931522', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.12406282201222528', 'is_elite: False']\n", + "Id: 54_84 Identity: {'ancestor_count': 49, 'ancestor_ids': ['2_49', '53_83'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_84', 'origin': '2_49~CUW~53_83#MGNP'} Metrics: ['ELUC: 6.443202717212564', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3089792812135015', 'is_elite: False']\n", + "Id: 54_18 Identity: {'ancestor_count': 6, 'ancestor_ids': ['2_49', '53_77'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_18', 'origin': '2_49~CUW~53_77#MGNP'} Metrics: ['ELUC: 1.9378010219704658', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.34874960378214087', 'is_elite: False']\n", + "Id: 54_23 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_52', '50_89'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_23', 'origin': '53_52~CUW~50_89#MGNP'} Metrics: ['ELUC: 1.1278023729709181', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07369108158318229', 'is_elite: False']\n", + "Id: 54_74 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '50_89'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_74', 'origin': '1_1~CUW~50_89#MGNP'} Metrics: ['ELUC: 1.0534330443300415', 'NSGA-II_crowding_distance: 0.7149756512149177', 'NSGA-II_rank: 5', 'change: 0.08313099172260138', 'is_elite: False']\n", + "Id: 54_93 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_77', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_93', 'origin': '53_77~CUW~51_44#MGNP'} Metrics: ['ELUC: 0.27841392752863187', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06067515477978131', 'is_elite: False']\n", + "Id: 54_71 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '53_38'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_71', 'origin': '1_1~CUW~53_38#MGNP'} Metrics: ['ELUC: 0.2727245519476452', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05586332201171524', 'is_elite: False']\n", + "Id: 54_16 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_38', '50_89'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_16', 'origin': '53_38~CUW~50_89#MGNP'} Metrics: ['ELUC: 0.1797409272332713', 'NSGA-II_crowding_distance: 0.14585378684144634', 'NSGA-II_rank: 3', 'change: 0.06662380063544827', 'is_elite: False']\n", + "Id: 54_22 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '50_89'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_22', 'origin': '1_1~CUW~50_89#MGNP'} Metrics: ['ELUC: 0.1500318977746072', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03189615025431323', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 54_76 Identity: {'ancestor_count': 2, 'ancestor_ids': ['50_89', '1_1'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_76', 'origin': '50_89~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.026749706955723932', 'NSGA-II_crowding_distance: 0.16953539142678486', 'NSGA-II_rank: 2', 'change: 0.036150834210892664', 'is_elite: False']\n", + "Id: 54_54 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '53_38'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_54', 'origin': '1_1~CUW~53_38#MGNP'} Metrics: ['ELUC: -0.21235428871301035', 'NSGA-II_crowding_distance: 0.19150982329685637', 'NSGA-II_rank: 2', 'change: 0.07232418258067601', 'is_elite: False']\n", + "Id: 54_32 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '50_89'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_32', 'origin': '53_24~CUW~50_89#MGNP'} Metrics: ['ELUC: -0.2554815806884129', 'NSGA-II_crowding_distance: 0.22988505031703216', 'NSGA-II_rank: 4', 'change: 0.083052511636197', 'is_elite: False']\n", + "Id: 50_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_89', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8753352639217634', 'NSGA-II_crowding_distance: 0.3524812447692962', 'NSGA-II_rank: 1', 'change: 0.027764991111589848', 'is_elite: True']\n", + "Id: 54_67 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '50_89'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_67', 'origin': '52_33~CUW~50_89#MGNP'} Metrics: ['ELUC: -0.889014537204465', 'NSGA-II_crowding_distance: 0.20997706680731587', 'NSGA-II_rank: 3', 'change: 0.07351216724140949', 'is_elite: False']\n", + "Id: 54_70 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '52_34'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_70', 'origin': '53_24~CUW~52_34#MGNP'} Metrics: ['ELUC: -0.9781507227925639', 'NSGA-II_crowding_distance: 0.2795048198856679', 'NSGA-II_rank: 4', 'change: 0.08982482540979887', 'is_elite: False']\n", + "Id: 54_94 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_83', '52_61'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_94', 'origin': '53_83~CUW~52_61#MGNP'} Metrics: ['ELUC: -0.9858990701544086', 'NSGA-II_crowding_distance: 0.1530729465659622', 'NSGA-II_rank: 2', 'change: 0.07341798074315178', 'is_elite: False']\n", + "Id: 54_60 Identity: {'ancestor_count': 51, 'ancestor_ids': ['52_33', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_60', 'origin': '52_33~CUW~53_80#MGNP'} Metrics: ['ELUC: -1.7977914512394637', 'NSGA-II_crowding_distance: 0.35905608994398086', 'NSGA-II_rank: 4', 'change: 0.1183006571992939', 'is_elite: False']\n", + "Id: 54_63 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_63', 'origin': '1_1~CUW~53_80#MGNP'} Metrics: ['ELUC: -2.073280363824242', 'NSGA-II_crowding_distance: 0.12744169521571988', 'NSGA-II_rank: 3', 'change: 0.0832384019770344', 'is_elite: False']\n", + "Id: 54_97 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_83', '50_89'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_97', 'origin': '53_83~CUW~50_89#MGNP'} Metrics: ['ELUC: -2.249189065652771', 'NSGA-II_crowding_distance: 0.10601001503117917', 'NSGA-II_rank: 3', 'change: 0.08370598493402116', 'is_elite: False']\n", + "Id: 54_58 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '53_43'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_58', 'origin': '51_44~CUW~53_43#MGNP'} Metrics: ['ELUC: -2.314946148105271', 'NSGA-II_crowding_distance: 0.3111368556055937', 'NSGA-II_rank: 1', 'change: 0.07078530962891603', 'is_elite: True']\n", + "Id: 54_64 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_43', '1_1'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_64', 'origin': '53_43~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.7510962613148373', 'NSGA-II_crowding_distance: 0.16582258239638178', 'NSGA-II_rank: 2', 'change: 0.07503345895747626', 'is_elite: False']\n", + "Id: 54_38 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_38', '53_77'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_38', 'origin': '53_38~CUW~53_77#MGNP'} Metrics: ['ELUC: -2.795753396775485', 'NSGA-II_crowding_distance: 0.3108006056962235', 'NSGA-II_rank: 3', 'change: 0.09791253387633864', 'is_elite: False']\n", + "Id: 54_36 Identity: {'ancestor_count': 51, 'ancestor_ids': ['50_89', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_36', 'origin': '50_89~CUW~53_24#MGNP'} Metrics: ['ELUC: -3.1944717700103706', 'NSGA-II_crowding_distance: 0.11730113934383463', 'NSGA-II_rank: 2', 'change: 0.08462909576580498', 'is_elite: False']\n", + "Id: 54_56 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_38', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_56', 'origin': '53_38~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.4978600239310054', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2692112640581217', 'is_elite: False']\n", + "Id: 54_41 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_41', 'origin': '1_1~CUW~53_80#MGNP'} Metrics: ['ELUC: -3.520198881508232', 'NSGA-II_crowding_distance: 0.4217586990830807', 'NSGA-II_rank: 4', 'change: 0.12763760692906367', 'is_elite: False']\n", + "Id: 53_38 Identity: {'ancestor_count': 50, 'ancestor_ids': ['49_34', '52_33'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_38', 'origin': '49_34~CUW~52_33#MGNP'} Metrics: ['ELUC: -3.6666387939920644', 'NSGA-II_crowding_distance: 0.1472227837232308', 'NSGA-II_rank: 1', 'change: 0.0732320138490511', 'is_elite: False']\n", + "Id: 54_91 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_43', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_91', 'origin': '53_43~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.7440470223597657', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.26942120089863014', 'is_elite: False']\n", + "Id: 54_26 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_38', '53_52'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_26', 'origin': '53_38~CUW~53_52#MGNP'} Metrics: ['ELUC: -3.8680504791007952', 'NSGA-II_crowding_distance: 0.12405652250850172', 'NSGA-II_rank: 2', 'change: 0.08976941921369827', 'is_elite: False']\n", + "Id: 54_68 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_52', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_68', 'origin': '53_52~CUW~53_24#MGNP'} Metrics: ['ELUC: -3.9482308449135335', 'NSGA-II_crowding_distance: 0.20726871705597177', 'NSGA-II_rank: 1', 'change: 0.08699596270920026', 'is_elite: False']\n", + "Id: 54_48 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_48', 'origin': '52_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.070248705750717', 'NSGA-II_crowding_distance: 1.56870265882801', 'NSGA-II_rank: 6', 'change: 0.24608203257956754', 'is_elite: False']\n", + "Id: 54_78 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_83', '53_73'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_78', 'origin': '53_83~CUW~53_73#MGNP'} Metrics: ['ELUC: -4.173137018295505', 'NSGA-II_crowding_distance: 1.4249139477051629', 'NSGA-II_rank: 9', 'change: 0.30218533512031676', 'is_elite: False']\n", + "Id: 54_90 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '53_65'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_90', 'origin': '1_1~CUW~53_65#MGNP'} Metrics: ['ELUC: -5.013933875942901', 'NSGA-II_crowding_distance: 0.21140787996270308', 'NSGA-II_rank: 2', 'change: 0.09046208438398544', 'is_elite: False']\n", + "Id: 54_96 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_83', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_96', 'origin': '53_83~CUW~53_24#MGNP'} Metrics: ['ELUC: -5.137378488795964', 'NSGA-II_crowding_distance: 0.8932119465712887', 'NSGA-II_rank: 5', 'change: 0.1390085145739877', 'is_elite: False']\n", + "Id: 54_35 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_65', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_35', 'origin': '53_65~CUW~53_97#MGNP'} Metrics: ['ELUC: -5.296665885736952', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.29027783713850963', 'is_elite: False']\n", + "Id: 54_88 Identity: {'ancestor_count': 52, 'ancestor_ids': ['52_33', '53_65'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_88', 'origin': '52_33~CUW~53_65#MGNP'} Metrics: ['ELUC: -5.344168414859033', 'NSGA-II_crowding_distance: 0.2822609211693774', 'NSGA-II_rank: 3', 'change: 0.1119315492857992', 'is_elite: False']\n", + "Id: 54_27 Identity: {'ancestor_count': 49, 'ancestor_ids': ['1_1', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_27', 'origin': '1_1~CUW~51_44#MGNP'} Metrics: ['ELUC: -5.636731352890745', 'NSGA-II_crowding_distance: 0.13118551303757237', 'NSGA-II_rank: 3', 'change: 0.12308881728175065', 'is_elite: False']\n", + "Id: 54_75 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '53_73'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_75', 'origin': '53_24~CUW~53_73#MGNP'} Metrics: ['ELUC: -5.974827138756915', 'NSGA-II_crowding_distance: 0.2133836372709552', 'NSGA-II_rank: 6', 'change: 0.260988839974473', 'is_elite: False']\n", + "Id: 54_39 Identity: {'ancestor_count': 5, 'ancestor_ids': ['52_34', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_39', 'origin': '52_34~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.08544405943987501', 'NSGA-II_rank: 6', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 54_98 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_43', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_98', 'origin': '53_43~CUW~53_24#MGNP'} Metrics: ['ELUC: -6.139119707098459', 'NSGA-II_crowding_distance: 0.22184418494101796', 'NSGA-II_rank: 3', 'change: 0.13159154597004266', 'is_elite: False']\n", + "Id: 54_14 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_43', '53_83'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_14', 'origin': '53_43~CUW~53_83#MGNP'} Metrics: ['ELUC: -6.25689465417625', 'NSGA-II_crowding_distance: 0.19399360566065046', 'NSGA-II_rank: 2', 'change: 0.11058527800354874', 'is_elite: False']\n", + "Id: 54_89 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_75', '53_38'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_89', 'origin': '53_75~CUW~53_38#MGNP'} Metrics: ['ELUC: -6.3795315750888175', 'NSGA-II_crowding_distance: 0.07911673030014608', 'NSGA-II_rank: 2', 'change: 0.12219199660334663', 'is_elite: False']\n", + "Id: 54_99 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_80', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_99', 'origin': '53_80~CUW~53_97#MGNP'} Metrics: ['ELUC: -6.385613435067946', 'NSGA-II_crowding_distance: 0.4157309047719576', 'NSGA-II_rank: 6', 'change: 0.2709668994721553', 'is_elite: False']\n", + "Id: 53_43 Identity: {'ancestor_count': 48, 'ancestor_ids': ['1_1', '49_34'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_43', 'origin': '1_1~CUW~49_34#MGNP'} Metrics: ['ELUC: -6.425940799961196', 'NSGA-II_crowding_distance: 0.17149960822827703', 'NSGA-II_rank: 1', 'change: 0.08825017453575823', 'is_elite: False']\n", + "Id: 53_83 Identity: {'ancestor_count': 48, 'ancestor_ids': ['49_34', '50_89'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_83', 'origin': '49_34~CUW~50_89#MGNP'} Metrics: ['ELUC: -6.710565412763305', 'NSGA-II_crowding_distance: 0.048407173980200266', 'NSGA-II_rank: 1', 'change: 0.09128995494909606', 'is_elite: False']\n", + "Id: 54_100 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '53_38'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_100', 'origin': '53_24~CUW~53_38#MGNP'} Metrics: ['ELUC: -6.719631912849844', 'NSGA-II_crowding_distance: 0.1639787532826342', 'NSGA-II_rank: 2', 'change: 0.12496509359409069', 'is_elite: False']\n", + "Id: 54_72 Identity: {'ancestor_count': 51, 'ancestor_ids': ['51_44', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_72', 'origin': '51_44~CUW~53_24#MGNP'} Metrics: ['ELUC: -6.7958430072657166', 'NSGA-II_crowding_distance: 0.28071576385762487', 'NSGA-II_rank: 4', 'change: 0.13592297575966816', 'is_elite: False']\n", + "Id: 54_82 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_83', '53_83'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_82', 'origin': '53_83~CUW~53_83#MGNP'} Metrics: ['ELUC: -6.829137585192828', 'NSGA-II_crowding_distance: 0.24578291047912781', 'NSGA-II_rank: 1', 'change: 0.09585142276955316', 'is_elite: False']\n", + "Id: 54_53 Identity: {'ancestor_count': 51, 'ancestor_ids': ['52_61', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_53', 'origin': '52_61~CUW~53_80#MGNP'} Metrics: ['ELUC: -6.872434388103902', 'NSGA-II_crowding_distance: 0.04584414652275019', 'NSGA-II_rank: 4', 'change: 0.13902565889172067', 'is_elite: False']\n", + "Id: 54_30 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '53_83'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_30', 'origin': '53_24~CUW~53_83#MGNP'} Metrics: ['ELUC: -6.913404712618718', 'NSGA-II_crowding_distance: 0.18925351463500867', 'NSGA-II_rank: 4', 'change: 0.14350748329133137', 'is_elite: False']\n", + "Id: 54_24 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_75', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_24', 'origin': '53_75~CUW~53_80#MGNP'} Metrics: ['ELUC: -7.916620995569583', 'NSGA-II_crowding_distance: 0.7735122729500822', 'NSGA-II_rank: 5', 'change: 0.14954782119091148', 'is_elite: False']\n", + "Id: 54_95 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_38', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_95', 'origin': '53_38~CUW~53_97#MGNP'} Metrics: ['ELUC: -8.07178844274192', 'NSGA-II_crowding_distance: 0.24089493048854427', 'NSGA-II_rank: 9', 'change: 0.30233554603186064', 'is_elite: False']\n", + "Id: 54_42 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_83', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_42', 'origin': '53_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.08206010914422', 'NSGA-II_crowding_distance: 0.5675762216626894', 'NSGA-II_rank: 5', 'change: 0.2605958454493296', 'is_elite: False']\n", + "Id: 54_55 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_55', 'origin': '53_24~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.241547903239532', 'NSGA-II_crowding_distance: 0.5115120758349999', 'NSGA-II_rank: 5', 'change: 0.2631502177972347', 'is_elite: False']\n", + "Id: 54_57 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '1_1'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_57', 'origin': '51_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.503263768526983', 'NSGA-II_crowding_distance: 0.3216511994771318', 'NSGA-II_rank: 3', 'change: 0.13327822641623374', 'is_elite: False']\n", + "Id: 54_92 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_33'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_92', 'origin': '52_33~CUW~52_33#MGNP'} Metrics: ['ELUC: -8.996762961259737', 'NSGA-II_crowding_distance: 0.32754774945138065', 'NSGA-II_rank: 2', 'change: 0.12665877582502058', 'is_elite: False']\n", + "Id: 54_66 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_66', 'origin': '53_24~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.07274745438867', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30368320572641666', 'is_elite: False']\n", + "Id: 52_33 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_49', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_33', 'origin': '50_49~CUW~51_44#MGNP'} Metrics: ['ELUC: -9.087431681374152', 'NSGA-II_crowding_distance: 0.41837610285707816', 'NSGA-II_rank: 1', 'change: 0.12428994495768048', 'is_elite: True']\n", + "Id: 54_61 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_73', '53_75'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_61', 'origin': '53_73~CUW~53_75#MGNP'} Metrics: ['ELUC: -9.335325229573968', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.29156860191951706', 'is_elite: False']\n", + "Id: 54_40 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_75', '53_38'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_40', 'origin': '53_75~CUW~53_38#MGNP'} Metrics: ['ELUC: -9.351281761347373', 'NSGA-II_crowding_distance: 0.3299765618377818', 'NSGA-II_rank: 4', 'change: 0.1437892324334887', 'is_elite: False']\n", + "Id: 54_43 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_43', '53_75'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_43', 'origin': '53_43~CUW~53_75#MGNP'} Metrics: ['ELUC: -9.955735453487046', 'NSGA-II_crowding_distance: 0.2608080712724678', 'NSGA-II_rank: 4', 'change: 0.16885430683523844', 'is_elite: False']\n", + "Id: 54_50 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_65', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_50', 'origin': '53_65~CUW~53_24#MGNP'} Metrics: ['ELUC: -10.063020467346673', 'NSGA-II_crowding_distance: 0.7751778208965332', 'NSGA-II_rank: 4', 'change: 0.18636596241364836', 'is_elite: False']\n", + "Id: 54_69 Identity: {'ancestor_count': 51, 'ancestor_ids': ['51_44', '53_52'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_69', 'origin': '51_44~CUW~53_52#MGNP'} Metrics: ['ELUC: -10.596759840112442', 'NSGA-II_crowding_distance: 0.9181457558937365', 'NSGA-II_rank: 3', 'change: 0.14179884627586467', 'is_elite: False']\n", + "Id: 54_29 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '53_73'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_29', 'origin': '53_24~CUW~53_73#MGNP'} Metrics: ['ELUC: -11.176203398048134', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.28548887158985115', 'is_elite: False']\n", + "Id: 54_44 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_44', 'origin': '51_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.446336597615929', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.28215539782056026', 'is_elite: False']\n", + "Id: 54_21 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_21', 'origin': '52_33~CUW~51_44#MGNP'} Metrics: ['ELUC: -11.678548758930637', 'NSGA-II_crowding_distance: 0.49746575444904106', 'NSGA-II_rank: 2', 'change: 0.13799798011312508', 'is_elite: False']\n", + "Id: 51_44 Identity: {'ancestor_count': 48, 'ancestor_ids': ['50_78', '50_49'], 'birth_generation': 51, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '51_44', 'origin': '50_78~CUW~50_49#MGNP'} Metrics: ['ELUC: -11.862327513770609', 'NSGA-II_crowding_distance: 0.2076704865487431', 'NSGA-II_rank: 1', 'change: 0.13527074393301133', 'is_elite: False']\n", + "Id: 54_19 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_77', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_19', 'origin': '53_77~CUW~51_44#MGNP'} Metrics: ['ELUC: -11.86240936468595', 'NSGA-II_crowding_distance: 0.11620005973216885', 'NSGA-II_rank: 1', 'change: 0.13916196363210076', 'is_elite: False']\n", + "Id: 54_17 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '53_77'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_17', 'origin': '53_24~CUW~53_77#MGNP'} Metrics: ['ELUC: -11.982948232839293', 'NSGA-II_crowding_distance: 0.25036295269383546', 'NSGA-II_rank: 1', 'change: 0.16789528139185458', 'is_elite: True']\n", + "Id: 53_24 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '51_84'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_24', 'origin': '52_33~CUW~51_84#MGNP'} Metrics: ['ELUC: -13.438145890850118', 'NSGA-II_crowding_distance: 0.3127059619177128', 'NSGA-II_rank: 2', 'change: 0.19366887208837358', 'is_elite: False']\n", + "Id: 54_20 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_75', '50_89'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_20', 'origin': '53_75~CUW~50_89#MGNP'} Metrics: ['ELUC: -13.576894276929435', 'NSGA-II_crowding_distance: 0.1915183456268443', 'NSGA-II_rank: 2', 'change: 0.19377331739910206', 'is_elite: False']\n", + "Id: 54_51 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_75', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_51', 'origin': '53_75~CUW~51_44#MGNP'} Metrics: ['ELUC: -13.65168050911476', 'NSGA-II_crowding_distance: 0.3107257714272301', 'NSGA-II_rank: 1', 'change: 0.18350020650372928', 'is_elite: True']\n", + "Id: 54_49 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_83', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_49', 'origin': '53_83~CUW~53_80#MGNP'} Metrics: ['ELUC: -14.463761667991264', 'NSGA-II_crowding_distance: 0.3104738182481083', 'NSGA-II_rank: 2', 'change: 0.22992270265714101', 'is_elite: False']\n", + "Id: 54_11 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_52', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_11', 'origin': '53_52~CUW~53_97#MGNP'} Metrics: ['ELUC: -14.512312600350871', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2814492921582376', 'is_elite: False']\n", + "Id: 54_83 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_65', '53_75'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_83', 'origin': '53_65~CUW~53_75#MGNP'} Metrics: ['ELUC: -14.709779776404353', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2602646960721199', 'is_elite: False']\n", + "Id: 54_45 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_65', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_45', 'origin': '53_65~CUW~53_24#MGNP'} Metrics: ['ELUC: -14.781291928415826', 'NSGA-II_crowding_distance: 0.3118501984671626', 'NSGA-II_rank: 1', 'change: 0.2131201719935676', 'is_elite: True']\n", + "Id: 54_13 Identity: {'ancestor_count': 51, 'ancestor_ids': ['52_33', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_13', 'origin': '52_33~CUW~53_80#MGNP'} Metrics: ['ELUC: -15.253978742826824', 'NSGA-II_crowding_distance: 0.1735859092918108', 'NSGA-II_rank: 1', 'change: 0.24935786114618158', 'is_elite: False']\n", + "Id: 54_25 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_65', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_25', 'origin': '53_65~CUW~53_80#MGNP'} Metrics: ['ELUC: -15.339119847749803', 'NSGA-II_crowding_distance: 0.963067199731906', 'NSGA-II_rank: 3', 'change: 0.2516063516896347', 'is_elite: False']\n", + "Id: 54_81 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_80', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_81', 'origin': '53_80~CUW~53_80#MGNP'} Metrics: ['ELUC: -15.37701024623896', 'NSGA-II_crowding_distance: 0.15744422593886526', 'NSGA-II_rank: 2', 'change: 0.2504444399157772', 'is_elite: False']\n", + "Id: 54_86 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_75', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_86', 'origin': '53_75~CUW~53_80#MGNP'} Metrics: ['ELUC: -15.52036126704458', 'NSGA-II_crowding_distance: 0.17144007518780066', 'NSGA-II_rank: 2', 'change: 0.25646472176815555', 'is_elite: False']\n", + "Id: 54_87 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_97', '53_43'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_87', 'origin': '53_97~CUW~53_43#MGNP'} Metrics: ['ELUC: -15.680952532936084', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29751488797102504', 'is_elite: False']\n", + "Id: 54_80 Identity: {'ancestor_count': 51, 'ancestor_ids': ['51_44', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_80', 'origin': '51_44~CUW~53_80#MGNP'} Metrics: ['ELUC: -15.69775633583108', 'NSGA-II_crowding_distance: 0.04693886113100412', 'NSGA-II_rank: 1', 'change: 0.24936165543668617', 'is_elite: False']\n", + "Id: 54_62 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_80', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_62', 'origin': '53_80~CUW~51_44#MGNP'} Metrics: ['ELUC: -15.897366075245003', 'NSGA-II_crowding_distance: 0.11330953115353984', 'NSGA-II_rank: 1', 'change: 0.2524448899432916', 'is_elite: False']\n", + "Id: 54_46 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '53_80'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_46', 'origin': '53_24~CUW~53_80#MGNP'} Metrics: ['ELUC: -16.458572331593448', 'NSGA-II_crowding_distance: 0.2741226746391126', 'NSGA-II_rank: 2', 'change: 0.2803996591847068', 'is_elite: False']\n", + "Id: 54_33 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_65', '53_75'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_33', 'origin': '53_65~CUW~53_75#MGNP'} Metrics: ['ELUC: -16.50275466429918', 'NSGA-II_crowding_distance: 0.2534694214618538', 'NSGA-II_rank: 1', 'change: 0.2695096246502319', 'is_elite: True']\n", + "Id: 54_85 Identity: {'ancestor_count': 51, 'ancestor_ids': ['2_49', '53_38'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_85', 'origin': '2_49~CUW~53_38#MGNP'} Metrics: ['ELUC: -17.411435479197195', 'NSGA-II_crowding_distance: 0.1473983075955667', 'NSGA-II_rank: 2', 'change: 0.3018902461293798', 'is_elite: False']\n", + "Id: 54_37 Identity: {'ancestor_count': 5, 'ancestor_ids': ['53_97', '52_61'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_37', 'origin': '53_97~CUW~52_61#MGNP'} Metrics: ['ELUC: -17.46918364402968', 'NSGA-II_crowding_distance: 0.1708071521539784', 'NSGA-II_rank: 1', 'change: 0.30140028805657126', 'is_elite: False']\n", + "Id: 54_52 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_52', 'origin': '2_49~CUW~53_97#MGNP'} Metrics: ['ELUC: -17.548930525604522', 'NSGA-II_crowding_distance: 0.01148310880277466', 'NSGA-II_rank: 1', 'change: 0.3027207455443538', 'is_elite: False']\n", + "Id: 54_34 Identity: {'ancestor_count': 3, 'ancestor_ids': ['53_97', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_34', 'origin': '53_97~CUW~53_97#MGNP'} Metrics: ['ELUC: -17.582051130744457', 'NSGA-II_crowding_distance: 0.002985648301233952', 'NSGA-II_rank: 1', 'change: 0.3029111957833579', 'is_elite: False']\n", + "Id: 54_65 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_65', 'origin': '2_49~CUW~53_97#MGNP'} Metrics: ['ELUC: -17.587414686285435', 'NSGA-II_crowding_distance: 0.0009489688418952236', 'NSGA-II_rank: 1', 'change: 0.30295850839406124', 'is_elite: False']\n", + "Id: 54_28 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '52_33'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_28', 'origin': '2_49~CUW~52_33#MGNP'} Metrics: ['ELUC: -17.593014514548443', 'NSGA-II_crowding_distance: 0.0007748039454786222', 'NSGA-II_rank: 1', 'change: 0.30300829493569764', 'is_elite: False']\n", + "Id: 54_47 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '53_97'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_47', 'origin': '53_24~CUW~53_97#MGNP'} Metrics: ['ELUC: -17.593450824287885', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030218468950379', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 53_97 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 53, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '53_97', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 54_31 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_43', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_31', 'origin': '53_43~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 54_59 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_97', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_59', 'origin': '53_97~CUW~51_44#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 54_77 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_77', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 54.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 55...:\n", + "PopulationResponse:\n", + " Generation: 55\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/55/20240220-021713\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 55 and asking ESP for generation 56...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 55 data persisted.\n", + "Evaluated candidates:\n", + "Id: 55_75 Identity: {'ancestor_count': 49, 'ancestor_ids': ['2_49', '51_44'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_75', 'origin': '2_49~CUW~51_44#MGNP'} Metrics: ['ELUC: 23.832460620282614', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.30378735366336135', 'is_elite: False']\n", + "Id: 55_98 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_77', '54_58'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_98', 'origin': '54_77~CUW~54_58#MGNP'} Metrics: ['ELUC: 14.176776758107655', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2870577155194617', 'is_elite: False']\n", + "Id: 55_12 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_12', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 8.056051767762115', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.26150643574987187', 'is_elite: False']\n", + "Id: 55_39 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '54_77'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_39', 'origin': '51_44~CUW~54_77#MGNP'} Metrics: ['ELUC: 4.7717155134577025', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2600294389030458', 'is_elite: False']\n", + "Id: 55_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['50_89', '2_49'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_82', 'origin': '50_89~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.460633309846533', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.2606870878953885', 'is_elite: False']\n", + "Id: 55_73 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_82', '2_49'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_73', 'origin': '54_82~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.8654275090359524', 'NSGA-II_crowding_distance: 1.9778842730741042', 'NSGA-II_rank: 11', 'change: 0.34722973485459263', 'is_elite: False']\n", + "Id: 55_42 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_68', '2_49'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_42', 'origin': '54_68~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.2348392409037046', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2279095652037732', 'is_elite: False']\n", + "Id: 55_89 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_89', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.491695802646836', 'NSGA-II_crowding_distance: 0.29671335079383276', 'NSGA-II_rank: 11', 'change: 0.3500531173811318', 'is_elite: False']\n", + "Id: 55_21 Identity: {'ancestor_count': 50, 'ancestor_ids': ['50_89', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_21', 'origin': '50_89~CUW~52_33#MGNP'} Metrics: ['ELUC: 2.412051590021568', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.09585157341304874', 'is_elite: False']\n", + "Id: 55_81 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_81', 'origin': '2_49~CUW~52_33#MGNP'} Metrics: ['ELUC: 2.400584377049428', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.35058808838489547', 'is_elite: False']\n", + "Id: 55_64 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_83', '2_49'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_64', 'origin': '53_83~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.33971246331684', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2396179692185737', 'is_elite: False']\n", + "Id: 55_68 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_68', '53_38'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_68', 'origin': '54_68~CUW~53_38#MGNP'} Metrics: ['ELUC: 1.5452842997017144', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08413347729539249', 'is_elite: False']\n", + "Id: 55_17 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_13', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_17', 'origin': '54_13~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.9588539636727602', 'NSGA-II_crowding_distance: 1.3065932600335468', 'NSGA-II_rank: 7', 'change: 0.10386868372202583', 'is_elite: False']\n", + "Id: 55_26 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_26', 'origin': '1_1~CUW~54_17#MGNP'} Metrics: ['ELUC: 0.8275222698269711', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05115408104885234', 'is_elite: False']\n", + "Id: 55_34 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_34', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.7199933780726193', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.026322946917038497', 'is_elite: False']\n", + "Id: 55_36 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '54_68'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_36', 'origin': '1_1~CUW~54_68#MGNP'} Metrics: ['ELUC: 0.3139569110672288', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07011848645515552', 'is_elite: False']\n", + "Id: 55_18 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_18', 'origin': '52_33~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.1885901558350117', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08160892629611181', 'is_elite: False']\n", + "Id: 55_66 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_66', 'origin': '51_44~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.15531890000307016', 'NSGA-II_crowding_distance: 1.2465604876357546', 'NSGA-II_rank: 6', 'change: 0.09360434878859811', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 55_69 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_13', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_69', 'origin': '54_13~CUW~52_33#MGNP'} Metrics: ['ELUC: -0.1531674907273226', 'NSGA-II_crowding_distance: 0.10387299135271374', 'NSGA-II_rank: 4', 'change: 0.07698673522367731', 'is_elite: False']\n", + "Id: 55_27 Identity: {'ancestor_count': 50, 'ancestor_ids': ['50_89', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_27', 'origin': '50_89~CUW~52_33#MGNP'} Metrics: ['ELUC: -0.38197206547793133', 'NSGA-II_crowding_distance: 0.1256772828649767', 'NSGA-II_rank: 4', 'change: 0.0803398547007203', 'is_elite: False']\n", + "Id: 55_96 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '50_89'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_96', 'origin': '1_1~CUW~50_89#MGNP'} Metrics: ['ELUC: -0.6766026480759991', 'NSGA-II_crowding_distance: 0.1264222744957155', 'NSGA-II_rank: 1', 'change: 0.023350538251739883', 'is_elite: False']\n", + "Id: 55_67 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_17', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_67', 'origin': '54_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8377222530971615', 'NSGA-II_crowding_distance: 0.4124307760861403', 'NSGA-II_rank: 5', 'change: 0.08823294237800113', 'is_elite: False']\n", + "Id: 50_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 50, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '50_89', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8753352639217634', 'NSGA-II_crowding_distance: 0.1107122534040203', 'NSGA-II_rank: 1', 'change: 0.027764991111589848', 'is_elite: False']\n", + "Id: 55_41 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_13', '54_77'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_41', 'origin': '54_13~CUW~54_77#MGNP'} Metrics: ['ELUC: -0.9341873219598777', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.24084931688844813', 'is_elite: False']\n", + "Id: 55_51 Identity: {'ancestor_count': 50, 'ancestor_ids': ['50_89', '54_58'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_51', 'origin': '50_89~CUW~54_58#MGNP'} Metrics: ['ELUC: -1.0550945561368386', 'NSGA-II_crowding_distance: 0.22153892040037593', 'NSGA-II_rank: 3', 'change: 0.06343870761928973', 'is_elite: False']\n", + "Id: 55_60 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_82', '50_89'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_60', 'origin': '54_82~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.0938572689299366', 'NSGA-II_crowding_distance: 0.2825621990915909', 'NSGA-II_rank: 4', 'change: 0.08775900754361628', 'is_elite: False']\n", + "Id: 55_86 Identity: {'ancestor_count': 52, 'ancestor_ids': ['52_33', '54_13'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_86', 'origin': '52_33~CUW~54_13#MGNP'} Metrics: ['ELUC: -1.1257053840353668', 'NSGA-II_crowding_distance: 0.08024845666080459', 'NSGA-II_rank: 3', 'change: 0.06834743579324772', 'is_elite: False']\n", + "Id: 55_72 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_58', '51_44'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_72', 'origin': '54_58~CUW~51_44#MGNP'} Metrics: ['ELUC: -1.3600628726466704', 'NSGA-II_crowding_distance: 0.30628382934446036', 'NSGA-II_rank: 3', 'change: 0.07473420657080496', 'is_elite: False']\n", + "Id: 55_11 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_11', 'origin': '52_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5503799379897625', 'NSGA-II_crowding_distance: 0.2819902668085291', 'NSGA-II_rank: 2', 'change: 0.05854798308599253', 'is_elite: False']\n", + "Id: 55_46 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_19', '2_49'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_46', 'origin': '54_19~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.589638442829735', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.23617559213183179', 'is_elite: False']\n", + "Id: 55_80 Identity: {'ancestor_count': 49, 'ancestor_ids': ['53_43', '50_89'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_80', 'origin': '53_43~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.640528775245072', 'NSGA-II_crowding_distance: 0.22307336857989735', 'NSGA-II_rank: 2', 'change: 0.0675944218809283', 'is_elite: False']\n", + "Id: 55_77 Identity: {'ancestor_count': 2, 'ancestor_ids': ['50_89', '50_89'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_77', 'origin': '50_89~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.7228911037057053', 'NSGA-II_crowding_distance: 0.2038179147258038', 'NSGA-II_rank: 1', 'change: 0.038628769851003185', 'is_elite: True']\n", + "Id: 55_50 Identity: {'ancestor_count': 49, 'ancestor_ids': ['1_1', '53_43'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_50', 'origin': '1_1~CUW~53_43#MGNP'} Metrics: ['ELUC: -2.1609895059856292', 'NSGA-II_crowding_distance: 0.14144453255302183', 'NSGA-II_rank: 1', 'change: 0.06676176597058832', 'is_elite: False']\n", + "Id: 55_99 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_33', '54_58'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_99', 'origin': '54_33~CUW~54_58#MGNP'} Metrics: ['ELUC: -2.1816724799482015', 'NSGA-II_crowding_distance: 0.2454568619450036', 'NSGA-II_rank: 4', 'change: 0.10965431313792334', 'is_elite: False']\n", + "Id: 55_15 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_68', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_15', 'origin': '54_68~CUW~54_17#MGNP'} Metrics: ['ELUC: -2.2937786727447564', 'NSGA-II_crowding_distance: 0.9074151708835629', 'NSGA-II_rank: 5', 'change: 0.12493160718553149', 'is_elite: False']\n", + "Id: 54_58 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '53_43'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_58', 'origin': '51_44~CUW~53_43#MGNP'} Metrics: ['ELUC: -2.314946148105271', 'NSGA-II_crowding_distance: 0.24072062905994848', 'NSGA-II_rank: 1', 'change: 0.07078530962891603', 'is_elite: True']\n", + "Id: 55_45 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_45', 'origin': '1_1~CUW~52_33#MGNP'} Metrics: ['ELUC: -2.676358890516253', 'NSGA-II_crowding_distance: 0.28647707228852126', 'NSGA-II_rank: 4', 'change: 0.11291475782677222', 'is_elite: False']\n", + "Id: 55_30 Identity: {'ancestor_count': 53, 'ancestor_ids': ['1_1', '54_45'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_30', 'origin': '1_1~CUW~54_45#MGNP'} Metrics: ['ELUC: -2.946755925819045', 'NSGA-II_crowding_distance: 0.6933688872525683', 'NSGA-II_rank: 3', 'change: 0.10318728784527896', 'is_elite: False']\n", + "Id: 55_33 Identity: {'ancestor_count': 50, 'ancestor_ids': ['53_43', '54_58'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_33', 'origin': '53_43~CUW~54_58#MGNP'} Metrics: ['ELUC: -3.631679059195852', 'NSGA-II_crowding_distance: 0.29174951633971463', 'NSGA-II_rank: 2', 'change: 0.0879013167135964', 'is_elite: False']\n", + "Id: 55_70 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '54_51'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_70', 'origin': '1_1~CUW~54_51#MGNP'} Metrics: ['ELUC: -3.8648497297703583', 'NSGA-II_crowding_distance: 0.34815878521506305', 'NSGA-II_rank: 2', 'change: 0.1136499377435683', 'is_elite: False']\n", + "Id: 55_38 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_38', 'origin': '52_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.677820902939669', 'NSGA-II_crowding_distance: 0.6111285289575028', 'NSGA-II_rank: 4', 'change: 0.12852268245202683', 'is_elite: False']\n", + "Id: 55_84 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_84', 'origin': '1_1~CUW~52_33#MGNP'} Metrics: ['ELUC: -5.592011266999677', 'NSGA-II_crowding_distance: 0.3121216697782022', 'NSGA-II_rank: 1', 'change: 0.08036194045690388', 'is_elite: True']\n", + "Id: 55_55 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_19', '54_82'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_55', 'origin': '54_19~CUW~54_82#MGNP'} Metrics: ['ELUC: -5.694766853989452', 'NSGA-II_crowding_distance: 0.15201848578965688', 'NSGA-II_rank: 1', 'change: 0.10655886113265435', 'is_elite: False']\n", + "Id: 55_23 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_45', '50_89'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_23', 'origin': '54_45~CUW~50_89#MGNP'} Metrics: ['ELUC: -6.591787292662942', 'NSGA-II_crowding_distance: 0.15410292860295982', 'NSGA-II_rank: 1', 'change: 0.1087543615349099', 'is_elite: False']\n", + "Id: 55_59 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '54_82'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_59', 'origin': '2_49~CUW~54_82#MGNP'} Metrics: ['ELUC: -7.676476879883187', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.29492316403221297', 'is_elite: False']\n", + "Id: 55_47 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_82', '54_51'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_47', 'origin': '54_82~CUW~54_51#MGNP'} Metrics: ['ELUC: -7.839389782812704', 'NSGA-II_crowding_distance: 0.4829100552514679', 'NSGA-II_rank: 3', 'change: 0.12393646418437632', 'is_elite: False']\n", + "Id: 55_76 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_68', '1_1'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_76', 'origin': '54_68~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.876503609098349', 'NSGA-II_crowding_distance: 0.3014129363955634', 'NSGA-II_rank: 2', 'change: 0.1183680725815458', 'is_elite: False']\n", + "Id: 55_49 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_17', '53_38'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_49', 'origin': '54_17~CUW~53_38#MGNP'} Metrics: ['ELUC: -7.917009757116863', 'NSGA-II_crowding_distance: 0.19400724312880716', 'NSGA-II_rank: 1', 'change: 0.1148275938574921', 'is_elite: False']\n", + "Id: 55_32 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '54_58'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_32', 'origin': '2_49~CUW~54_58#MGNP'} Metrics: ['ELUC: -8.178416889023346', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.28202526540771616', 'is_elite: False']\n", + "Id: 55_95 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_82', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_95', 'origin': '54_82~CUW~52_33#MGNP'} Metrics: ['ELUC: -8.234749951583188', 'NSGA-II_crowding_distance: 0.1437142076287488', 'NSGA-II_rank: 3', 'change: 0.12769478251774313', 'is_elite: False']\n", + "Id: 55_78 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_33', '54_82'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_78', 'origin': '54_33~CUW~54_82#MGNP'} Metrics: ['ELUC: -8.29169824153506', 'NSGA-II_crowding_distance: 1.8144377051972491', 'NSGA-II_rank: 7', 'change: 0.14568222521307297', 'is_elite: False']\n", + "Id: 55_58 Identity: {'ancestor_count': 52, 'ancestor_ids': ['2_49', '54_51'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_58', 'origin': '2_49~CUW~54_51#MGNP'} Metrics: ['ELUC: -8.364669713422245', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2664108150669774', 'is_elite: False']\n", + "Id: 55_40 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_77', '54_45'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_40', 'origin': '54_77~CUW~54_45#MGNP'} Metrics: ['ELUC: -8.49581651585075', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24903233631973365', 'is_elite: False']\n", + "Id: 55_90 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_90', 'origin': '52_33~CUW~52_33#MGNP'} Metrics: ['ELUC: -8.530170386032625', 'NSGA-II_crowding_distance: 0.15373748908575713', 'NSGA-II_rank: 2', 'change: 0.12477289767927773', 'is_elite: False']\n", + "Id: 55_29 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_82', '54_62'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_29', 'origin': '54_82~CUW~54_62#MGNP'} Metrics: ['ELUC: -8.796885561376858', 'NSGA-II_crowding_distance: 1.8253227784575048', 'NSGA-II_rank: 6', 'change: 0.14292378151690435', 'is_elite: False']\n", + "Id: 55_31 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_43', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_31', 'origin': '53_43~CUW~54_17#MGNP'} Metrics: ['ELUC: -8.808870355296085', 'NSGA-II_crowding_distance: 0.6708548969361527', 'NSGA-II_rank: 5', 'change: 0.1407414254260939', 'is_elite: False']\n", + "Id: 55_53 Identity: {'ancestor_count': 3, 'ancestor_ids': ['50_89', '54_77'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_53', 'origin': '50_89~CUW~54_77#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 52_33 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_49', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_33', 'origin': '50_49~CUW~51_44#MGNP'} Metrics: ['ELUC: -9.087431681374152', 'NSGA-II_crowding_distance: 0.1990215171827989', 'NSGA-II_rank: 1', 'change: 0.12428994495768048', 'is_elite: True']\n", + "Id: 55_92 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_17', '53_43'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_92', 'origin': '54_17~CUW~53_43#MGNP'} Metrics: ['ELUC: -9.122171728746615', 'NSGA-II_crowding_distance: 0.9764098177416536', 'NSGA-II_rank: 5', 'change: 0.14779663287350864', 'is_elite: False']\n", + "Id: 55_56 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_45', '50_89'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_56', 'origin': '54_45~CUW~50_89#MGNP'} Metrics: ['ELUC: -9.181771133698977', 'NSGA-II_crowding_distance: 1.0020590528220523', 'NSGA-II_rank: 4', 'change: 0.13408801511825083', 'is_elite: False']\n", + "Id: 55_61 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_68', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_61', 'origin': '54_68~CUW~52_33#MGNP'} Metrics: ['ELUC: -9.298577154563601', 'NSGA-II_crowding_distance: 0.22302697845015867', 'NSGA-II_rank: 3', 'change: 0.13267155249554644', 'is_elite: False']\n", + "Id: 55_97 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_13', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_97', 'origin': '54_13~CUW~52_33#MGNP'} Metrics: ['ELUC: -9.310369613580017', 'NSGA-II_crowding_distance: 0.20210814824281403', 'NSGA-II_rank: 3', 'change: 0.15621650384568497', 'is_elite: False']\n", + "Id: 55_25 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_44', '54_58'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_25', 'origin': '51_44~CUW~54_58#MGNP'} Metrics: ['ELUC: -9.886038974934213', 'NSGA-II_crowding_distance: 0.29013852290277464', 'NSGA-II_rank: 2', 'change: 0.12974020565816297', 'is_elite: False']\n", + "Id: 55_79 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_77', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_79', 'origin': '54_77~CUW~54_17#MGNP'} Metrics: ['ELUC: -9.892195732354654', 'NSGA-II_crowding_distance: 0.9479793615003004', 'NSGA-II_rank: 4', 'change: 0.2513566721483549', 'is_elite: False']\n", + "Id: 55_52 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_17', '54_51'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_52', 'origin': '54_17~CUW~54_51#MGNP'} Metrics: ['ELUC: -10.415060268898383', 'NSGA-II_crowding_distance: 0.24031411733713762', 'NSGA-II_rank: 3', 'change: 0.1567336483550838', 'is_elite: False']\n", + "Id: 55_44 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_44', '54_19'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_44', 'origin': '51_44~CUW~54_19#MGNP'} Metrics: ['ELUC: -10.747800551174647', 'NSGA-II_crowding_distance: 0.2912481297221622', 'NSGA-II_rank: 1', 'change: 0.12617178713165664', 'is_elite: True']\n", + "Id: 55_62 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_51', '54_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_62', 'origin': '54_51~CUW~54_33#MGNP'} Metrics: ['ELUC: -11.665376943634154', 'NSGA-II_crowding_distance: 0.23859997965011592', 'NSGA-II_rank: 2', 'change: 0.1563568420548194', 'is_elite: False']\n", + "Id: 54_17 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_24', '53_77'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_17', 'origin': '53_24~CUW~53_77#MGNP'} Metrics: ['ELUC: -11.982948232839293', 'NSGA-II_crowding_distance: 0.49339211164179075', 'NSGA-II_rank: 3', 'change: 0.16789528139185458', 'is_elite: False']\n", + "Id: 55_94 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_13', '54_77'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_94', 'origin': '54_13~CUW~54_77#MGNP'} Metrics: ['ELUC: -11.988100093981119', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28932341153250635', 'is_elite: False']\n", + "Id: 55_83 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_51', '54_45'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_83', 'origin': '54_51~CUW~54_45#MGNP'} Metrics: ['ELUC: -12.366295646218497', 'NSGA-II_crowding_distance: 0.30268127283961044', 'NSGA-II_rank: 2', 'change: 0.15722346815309532', 'is_elite: False']\n", + "Id: 55_87 Identity: {'ancestor_count': 51, 'ancestor_ids': ['54_37', '53_38'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_87', 'origin': '54_37~CUW~53_38#MGNP'} Metrics: ['ELUC: -12.474790160385064', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.276795740314542', 'is_elite: False']\n", + "Id: 55_37 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_51', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_37', 'origin': '54_51~CUW~54_17#MGNP'} Metrics: ['ELUC: -12.523039998723924', 'NSGA-II_crowding_distance: 0.3572926261092533', 'NSGA-II_rank: 1', 'change: 0.15288856433011014', 'is_elite: True']\n", + "Id: 55_65 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_82', '54_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_65', 'origin': '54_82~CUW~54_33#MGNP'} Metrics: ['ELUC: -12.73758251770361', 'NSGA-II_crowding_distance: 0.5259260992163994', 'NSGA-II_rank: 3', 'change: 0.22054871436060053', 'is_elite: False']\n", + "Id: 54_51 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_75', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_51', 'origin': '53_75~CUW~51_44#MGNP'} Metrics: ['ELUC: -13.65168050911476', 'NSGA-II_crowding_distance: 0.2529770667395251', 'NSGA-II_rank: 1', 'change: 0.18350020650372928', 'is_elite: True']\n", + "Id: 55_88 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '54_13'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_88', 'origin': '1_1~CUW~54_13#MGNP'} Metrics: ['ELUC: -14.154186730371197', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2397505711558315', 'is_elite: False']\n", + "Id: 55_24 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_33', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_24', 'origin': '54_33~CUW~54_17#MGNP'} Metrics: ['ELUC: -14.201699181849522', 'NSGA-II_crowding_distance: 0.33816749607330376', 'NSGA-II_rank: 2', 'change: 0.20061661167128025', 'is_elite: False']\n", + "Id: 55_35 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_45', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_35', 'origin': '54_45~CUW~54_17#MGNP'} Metrics: ['ELUC: -14.253923565645344', 'NSGA-II_crowding_distance: 0.1603168324026784', 'NSGA-II_rank: 1', 'change: 0.19899765575927528', 'is_elite: False']\n", + "Id: 54_45 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_65', '53_24'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_45', 'origin': '53_65~CUW~53_24#MGNP'} Metrics: ['ELUC: -14.781291928415826', 'NSGA-II_crowding_distance: 0.3872790032442076', 'NSGA-II_rank: 2', 'change: 0.2131201719935676', 'is_elite: False']\n", + "Id: 55_19 Identity: {'ancestor_count': 53, 'ancestor_ids': ['53_43', '54_45'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_19', 'origin': '53_43~CUW~54_45#MGNP'} Metrics: ['ELUC: -14.787687429167464', 'NSGA-II_crowding_distance: 0.09357299925481966', 'NSGA-II_rank: 1', 'change: 0.21205678901743266', 'is_elite: False']\n", + "Id: 55_13 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_33', '54_45'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_13', 'origin': '54_33~CUW~54_45#MGNP'} Metrics: ['ELUC: -14.805680345916409', 'NSGA-II_crowding_distance: 0.16298732261586774', 'NSGA-II_rank: 1', 'change: 0.21755427080903972', 'is_elite: False']\n", + "Id: 55_16 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_33', '54_13'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_16', 'origin': '54_33~CUW~54_13#MGNP'} Metrics: ['ELUC: -15.500617069623617', 'NSGA-II_crowding_distance: 0.17933012416591387', 'NSGA-II_rank: 1', 'change: 0.2485899381107668', 'is_elite: False']\n", + "Id: 55_71 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_13', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_71', 'origin': '54_13~CUW~52_33#MGNP'} Metrics: ['ELUC: -15.701751067782029', 'NSGA-II_crowding_distance: 0.06062500794164495', 'NSGA-II_rank: 1', 'change: 0.2558557870856146', 'is_elite: False']\n", + "Id: 55_20 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_33', '54_19'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_20', 'origin': '54_33~CUW~54_19#MGNP'} Metrics: ['ELUC: -16.070261862009886', 'NSGA-II_crowding_distance: 0.045370523342395754', 'NSGA-II_rank: 1', 'change: 0.2570120417412269', 'is_elite: False']\n", + "Id: 55_43 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_58', '54_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_43', 'origin': '54_58~CUW~54_33#MGNP'} Metrics: ['ELUC: -16.204800148797375', 'NSGA-II_crowding_distance: 0.03669377438820831', 'NSGA-II_rank: 1', 'change: 0.26085644221203697', 'is_elite: False']\n", + "Id: 55_48 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_33', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_48', 'origin': '54_33~CUW~54_17#MGNP'} Metrics: ['ELUC: -16.27070087019611', 'NSGA-II_crowding_distance: 0.04594700517456057', 'NSGA-II_rank: 1', 'change: 0.26455913453711477', 'is_elite: False']\n", + "Id: 54_33 Identity: {'ancestor_count': 52, 'ancestor_ids': ['53_65', '53_75'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_33', 'origin': '53_65~CUW~53_75#MGNP'} Metrics: ['ELUC: -16.50275466429918', 'NSGA-II_crowding_distance: 0.036748861627411866', 'NSGA-II_rank: 1', 'change: 0.2695096246502319', 'is_elite: False']\n", + "Id: 55_54 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_13', '54_51'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_54', 'origin': '54_13~CUW~54_51#MGNP'} Metrics: ['ELUC: -16.528515802982582', 'NSGA-II_crowding_distance: 0.45417942165106184', 'NSGA-II_rank: 2', 'change: 0.2713904729309348', 'is_elite: False']\n", + "Id: 55_85 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_33', '54_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_85', 'origin': '54_33~CUW~54_33#MGNP'} Metrics: ['ELUC: -16.549253407682116', 'NSGA-II_crowding_distance: 0.02889424124244097', 'NSGA-II_rank: 1', 'change: 0.27079705347323246', 'is_elite: False']\n", + "Id: 55_14 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_45', '54_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_14', 'origin': '54_45~CUW~54_33#MGNP'} Metrics: ['ELUC: -16.680010864107835', 'NSGA-II_crowding_distance: 0.1280059138695557', 'NSGA-II_rank: 1', 'change: 0.27512292997527427', 'is_elite: False']\n", + "Id: 55_63 Identity: {'ancestor_count': 52, 'ancestor_ids': ['2_49', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_63', 'origin': '2_49~CUW~54_17#MGNP'} Metrics: ['ELUC: -17.15437777829', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30159744228547186', 'is_elite: False']\n", + "Id: 55_100 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_77', '54_45'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_100', 'origin': '54_77~CUW~54_45#MGNP'} Metrics: ['ELUC: -17.320101965072485', 'NSGA-II_crowding_distance: 0.13185316821818427', 'NSGA-II_rank: 1', 'change: 0.2959096279101809', 'is_elite: False']\n", + "Id: 55_22 Identity: {'ancestor_count': 53, 'ancestor_ids': ['2_49', '54_45'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_22', 'origin': '2_49~CUW~54_45#MGNP'} Metrics: ['ELUC: -17.363146742326556', 'NSGA-II_crowding_distance: 0.0381827874200112', 'NSGA-II_rank: 1', 'change: 0.3028719505671469', 'is_elite: False']\n", + "Id: 55_93 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_77', '54_58'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_93', 'origin': '54_77~CUW~54_58#MGNP'} Metrics: ['ELUC: -17.57646508390158', 'NSGA-II_crowding_distance: 0.013820194940065731', 'NSGA-II_rank: 1', 'change: 0.3029519596195475', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 54_77 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_77', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 55_28 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '2_49'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_28', 'origin': '51_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 55_57 Identity: {'ancestor_count': 3, 'ancestor_ids': ['54_77', '54_77'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_57', 'origin': '54_77~CUW~54_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 55_74 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '54_77'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_74', 'origin': '2_49~CUW~54_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 55_91 Identity: {'ancestor_count': 3, 'ancestor_ids': ['54_77', '54_77'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_91', 'origin': '54_77~CUW~54_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 55.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 56...:\n", + "PopulationResponse:\n", + " Generation: 56\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/56/20240220-022427\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 56 and asking ESP for generation 57...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 56 data persisted.\n", + "Evaluated candidates:\n", + "Id: 56_70 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '52_33'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_70', 'origin': '2_49~CUW~52_33#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 56_30 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_14', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_30', 'origin': '55_14~CUW~55_91#MGNP'} Metrics: ['ELUC: 12.390994167680182', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2865673919851264', 'is_elite: False']\n", + "Id: 56_87 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_87', 'origin': '55_84~CUW~55_91#MGNP'} Metrics: ['ELUC: 7.314837135522013', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2673185779675496', 'is_elite: False']\n", + "Id: 56_32 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '55_100'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_32', 'origin': '2_49~CUW~55_100#MGNP'} Metrics: ['ELUC: 6.395331198371128', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.2749610825900049', 'is_elite: False']\n", + "Id: 56_69 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_35', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_69', 'origin': '55_35~CUW~2_49#MGNP'} Metrics: ['ELUC: 6.138073475980107', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26602661172315256', 'is_elite: False']\n", + "Id: 56_61 Identity: {'ancestor_count': 4, 'ancestor_ids': ['55_91', '55_77'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_61', 'origin': '55_91~CUW~55_77#MGNP'} Metrics: ['ELUC: 4.6309242737910825', 'NSGA-II_crowding_distance: 1.6647391245108465', 'NSGA-II_rank: 9', 'change: 0.2910287324688099', 'is_elite: False']\n", + "Id: 56_60 Identity: {'ancestor_count': 52, 'ancestor_ids': ['55_91', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_60', 'origin': '55_91~CUW~54_51#MGNP'} Metrics: ['ELUC: 3.3155854522902555', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.25842541301341765', 'is_elite: False']\n", + "Id: 56_96 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_58', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_96', 'origin': '54_58~CUW~55_91#MGNP'} Metrics: ['ELUC: 2.1066934703388616', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.33704766256522506', 'is_elite: False']\n", + "Id: 56_68 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_91', '55_84'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_68', 'origin': '55_91~CUW~55_84#MGNP'} Metrics: ['ELUC: 1.945759872922894', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3504362913946641', 'is_elite: False']\n", + "Id: 56_51 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_35', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_51', 'origin': '55_35~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.2954032623615583', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2809066789449544', 'is_elite: False']\n", + "Id: 56_44 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '52_33'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_44', 'origin': '2_49~CUW~52_33#MGNP'} Metrics: ['ELUC: 0.21644560118669098', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2470824446074313', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 56_48 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_58', '1_1'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_48', 'origin': '54_58~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.07551557312878308', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04422953811558983', 'is_elite: False']\n", + "Id: 56_11 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_51', '55_84'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_11', 'origin': '54_51~CUW~55_84#MGNP'} Metrics: ['ELUC: -0.09102947671228995', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09070358089851889', 'is_elite: False']\n", + "Id: 56_50 Identity: {'ancestor_count': 54, 'ancestor_ids': ['1_1', '55_16'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_50', 'origin': '1_1~CUW~55_16#MGNP'} Metrics: ['ELUC: -0.3301987333059648', 'NSGA-II_crowding_distance: 0.3836674634178967', 'NSGA-II_rank: 5', 'change: 0.11741747413082444', 'is_elite: False']\n", + "Id: 56_62 Identity: {'ancestor_count': 52, 'ancestor_ids': ['55_91', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_62', 'origin': '55_91~CUW~54_51#MGNP'} Metrics: ['ELUC: -0.5747019970184702', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.23879677897722817', 'is_elite: False']\n", + "Id: 56_91 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_23', '55_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_91', 'origin': '55_23~CUW~55_49#MGNP'} Metrics: ['ELUC: -1.6299246087586192', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09062752578061299', 'is_elite: False']\n", + "Id: 55_77 Identity: {'ancestor_count': 2, 'ancestor_ids': ['50_89', '50_89'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_77', 'origin': '50_89~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.7228911037057053', 'NSGA-II_crowding_distance: 0.3292441396220762', 'NSGA-II_rank: 1', 'change: 0.038628769851003185', 'is_elite: True']\n", + "Id: 56_67 Identity: {'ancestor_count': 51, 'ancestor_ids': ['2_49', '55_84'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_67', 'origin': '2_49~CUW~55_84#MGNP'} Metrics: ['ELUC: -1.817783358840651', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.34439400700840445', 'is_elite: False']\n", + "Id: 56_79 Identity: {'ancestor_count': 52, 'ancestor_ids': ['55_77', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_79', 'origin': '55_77~CUW~54_51#MGNP'} Metrics: ['ELUC: -1.8301126939702195', 'NSGA-II_crowding_distance: 0.3489441776853406', 'NSGA-II_rank: 5', 'change: 0.1383958944421465', 'is_elite: False']\n", + "Id: 56_20 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '1_1'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_20', 'origin': '55_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2056491775017317', 'NSGA-II_crowding_distance: 0.25367518339964545', 'NSGA-II_rank: 2', 'change: 0.06354024779840704', 'is_elite: False']\n", + "Id: 54_58 Identity: {'ancestor_count': 49, 'ancestor_ids': ['51_44', '53_43'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_58', 'origin': '51_44~CUW~53_43#MGNP'} Metrics: ['ELUC: -2.314946148105271', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07078530962891603', 'is_elite: False']\n", + "Id: 56_85 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '55_44'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_85', 'origin': '55_84~CUW~55_44#MGNP'} Metrics: ['ELUC: -2.3519468686731937', 'NSGA-II_crowding_distance: 0.03228504012007878', 'NSGA-II_rank: 3', 'change: 0.07351639207872451', 'is_elite: False']\n", + "Id: 56_35 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '55_44'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_35', 'origin': '55_84~CUW~55_44#MGNP'} Metrics: ['ELUC: -2.4658625486724235', 'NSGA-II_crowding_distance: 0.07021067557225334', 'NSGA-II_rank: 3', 'change: 0.07490915755830416', 'is_elite: False']\n", + "Id: 56_15 Identity: {'ancestor_count': 54, 'ancestor_ids': ['52_33', '55_35'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_15', 'origin': '52_33~CUW~55_35#MGNP'} Metrics: ['ELUC: -2.5433270841455737', 'NSGA-II_crowding_distance: 0.9722592806400605', 'NSGA-II_rank: 5', 'change: 0.15022383077019769', 'is_elite: False']\n", + "Id: 56_42 Identity: {'ancestor_count': 54, 'ancestor_ids': ['54_58', '55_100'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_42', 'origin': '54_58~CUW~55_100#MGNP'} Metrics: ['ELUC: -2.543980864141568', 'NSGA-II_crowding_distance: 0.9655125619196698', 'NSGA-II_rank: 6', 'change: 0.2523399254926096', 'is_elite: False']\n", + "Id: 56_49 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_23', '1_1'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_49', 'origin': '55_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.5501831804847184', 'NSGA-II_crowding_distance: 0.1535918351959974', 'NSGA-II_rank: 1', 'change: 0.05985983037448142', 'is_elite: False']\n", + "Id: 56_36 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_35', '55_84'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_36', 'origin': '55_35~CUW~55_84#MGNP'} Metrics: ['ELUC: -2.784141415318868', 'NSGA-II_crowding_distance: 0.07327435746260161', 'NSGA-II_rank: 3', 'change: 0.08070901330257582', 'is_elite: False']\n", + "Id: 56_53 Identity: {'ancestor_count': 54, 'ancestor_ids': ['1_1', '55_23'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_53', 'origin': '1_1~CUW~55_23#MGNP'} Metrics: ['ELUC: -2.7892710726467165', 'NSGA-II_crowding_distance: 0.18533293080679947', 'NSGA-II_rank: 2', 'change: 0.06822689622170143', 'is_elite: False']\n", + "Id: 56_19 Identity: {'ancestor_count': 54, 'ancestor_ids': ['1_1', '55_23'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_19', 'origin': '1_1~CUW~55_23#MGNP'} Metrics: ['ELUC: -2.8555733518926067', 'NSGA-II_crowding_distance: 0.21756479237285614', 'NSGA-II_rank: 3', 'change: 0.08346297301545638', 'is_elite: False']\n", + "Id: 56_47 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_23', '55_44'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_47', 'origin': '55_23~CUW~55_44#MGNP'} Metrics: ['ELUC: -3.0143134499123554', 'NSGA-II_crowding_distance: 0.10957136227304448', 'NSGA-II_rank: 1', 'change: 0.06254131539314527', 'is_elite: False']\n", + "Id: 56_94 Identity: {'ancestor_count': 50, 'ancestor_ids': ['2_49', '55_50'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_94', 'origin': '2_49~CUW~55_50#MGNP'} Metrics: ['ELUC: -3.1083291602653587', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30566822244821', 'is_elite: False']\n", + "Id: 56_55 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_44', '1_1'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_55', 'origin': '55_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.4693303465131318', 'NSGA-II_crowding_distance: 0.45869161396201547', 'NSGA-II_rank: 3', 'change: 0.11416441058999588', 'is_elite: False']\n", + "Id: 56_13 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_49', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_13', 'origin': '55_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.790723139485749', 'NSGA-II_crowding_distance: 1.480196435566518', 'NSGA-II_rank: 7', 'change: 0.2795782376367484', 'is_elite: False']\n", + "Id: 56_98 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_44', '1_1'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_98', 'origin': '55_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.8449949452006287', 'NSGA-II_crowding_distance: 0.20633227086919603', 'NSGA-II_rank: 1', 'change: 0.070580128343652', 'is_elite: False']\n", + "Id: 56_17 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_23', '55_84'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_17', 'origin': '55_23~CUW~55_84#MGNP'} Metrics: ['ELUC: -4.191006241835729', 'NSGA-II_crowding_distance: 0.29437029401041515', 'NSGA-II_rank: 2', 'change: 0.08103037264586511', 'is_elite: False']\n", + "Id: 56_74 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '54_58'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_74', 'origin': '52_33~CUW~54_58#MGNP'} Metrics: ['ELUC: -5.114205717419022', 'NSGA-II_crowding_distance: 0.45755698409939444', 'NSGA-II_rank: 2', 'change: 0.10888804432713442', 'is_elite: False']\n", + "Id: 55_84 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_84', 'origin': '1_1~CUW~52_33#MGNP'} Metrics: ['ELUC: -5.592011266999677', 'NSGA-II_crowding_distance: 0.27522052065378794', 'NSGA-II_rank: 1', 'change: 0.08036194045690388', 'is_elite: True']\n", + "Id: 56_92 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_51', '55_77'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_92', 'origin': '54_51~CUW~55_77#MGNP'} Metrics: ['ELUC: -5.697301222916876', 'NSGA-II_crowding_distance: 0.7481374795086855', 'NSGA-II_rank: 4', 'change: 0.12819879257353928', 'is_elite: False']\n", + "Id: 56_63 Identity: {'ancestor_count': 53, 'ancestor_ids': ['1_1', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_63', 'origin': '1_1~CUW~55_37#MGNP'} Metrics: ['ELUC: -5.958059656975363', 'NSGA-II_crowding_distance: 0.4099932709922426', 'NSGA-II_rank: 3', 'change: 0.12569063083739115', 'is_elite: False']\n", + "Id: 56_65 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_65', 'origin': '1_1~CUW~55_91#MGNP'} Metrics: ['ELUC: -6.050167242892401', 'NSGA-II_crowding_distance: 1.1058402498035593', 'NSGA-II_rank: 6', 'change: 0.26252230363195384', 'is_elite: False']\n", + "Id: 56_37 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_37', 'origin': '55_84~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.099467972796868', 'NSGA-II_crowding_distance: 1.3114640811325347', 'NSGA-II_rank: 9', 'change: 0.3024797718610837', 'is_elite: False']\n", + "Id: 56_73 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_91', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_73', 'origin': '55_91~CUW~55_37#MGNP'} Metrics: ['ELUC: -6.753199238088396', 'NSGA-II_crowding_distance: 0.6270924989362177', 'NSGA-II_rank: 7', 'change: 0.28556186521181054', 'is_elite: False']\n", + "Id: 56_54 Identity: {'ancestor_count': 54, 'ancestor_ids': ['52_33', '55_35'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_54', 'origin': '52_33~CUW~55_35#MGNP'} Metrics: ['ELUC: -7.095248122387698', 'NSGA-II_crowding_distance: 0.342890698628172', 'NSGA-II_rank: 4', 'change: 0.13663546776034421', 'is_elite: False']\n", + "Id: 56_22 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_49', '55_84'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_22', 'origin': '55_49~CUW~55_84#MGNP'} Metrics: ['ELUC: -7.190135053074711', 'NSGA-II_crowding_distance: 0.2811859476578368', 'NSGA-II_rank: 1', 'change: 0.09593173974959476', 'is_elite: True']\n", + "Id: 56_78 Identity: {'ancestor_count': 50, 'ancestor_ids': ['52_33', '1_1'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_78', 'origin': '52_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.765862235876428', 'NSGA-II_crowding_distance: 0.18867973685860276', 'NSGA-II_rank: 3', 'change: 0.1258984601484923', 'is_elite: False']\n", + "Id: 56_46 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_35', '1_1'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_46', 'origin': '55_35~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.090978697785067', 'NSGA-II_crowding_distance: 0.22111063550595456', 'NSGA-II_rank: 3', 'change: 0.12843322645819794', 'is_elite: False']\n", + "Id: 56_29 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_13', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_29', 'origin': '55_13~CUW~55_37#MGNP'} Metrics: ['ELUC: -8.351462487804454', 'NSGA-II_crowding_distance: 0.23555573902663923', 'NSGA-II_rank: 4', 'change: 0.1464675785600313', 'is_elite: False']\n", + "Id: 56_90 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '55_55'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_90', 'origin': '55_84~CUW~55_55#MGNP'} Metrics: ['ELUC: -8.362820093278753', 'NSGA-II_crowding_distance: 0.2867496720525666', 'NSGA-II_rank: 1', 'change: 0.11724008117666955', 'is_elite: True']\n", + "Id: 56_12 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_91', '55_23'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_12', 'origin': '55_91~CUW~55_23#MGNP'} Metrics: ['ELUC: -8.608472034706347', 'NSGA-II_crowding_distance: 0.5198035644334819', 'NSGA-II_rank: 7', 'change: 0.2879376515868894', 'is_elite: False']\n", + "Id: 56_95 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_37', '55_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_95', 'origin': '55_37~CUW~55_49#MGNP'} Metrics: ['ELUC: -8.752073924368226', 'NSGA-II_crowding_distance: 0.37945255348572976', 'NSGA-II_rank: 4', 'change: 0.15232891777852597', 'is_elite: False']\n", + "Id: 56_64 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_51', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_64', 'origin': '54_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.054610568179585', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3084510042070376', 'is_elite: False']\n", + "Id: 52_33 Identity: {'ancestor_count': 49, 'ancestor_ids': ['50_49', '51_44'], 'birth_generation': 52, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '52_33', 'origin': '50_49~CUW~51_44#MGNP'} Metrics: ['ELUC: -9.087431681374152', 'NSGA-II_crowding_distance: 0.3638588350752641', 'NSGA-II_rank: 2', 'change: 0.12428994495768048', 'is_elite: False']\n", + "Id: 56_38 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_44', '55_16'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_38', 'origin': '55_44~CUW~55_16#MGNP'} Metrics: ['ELUC: -9.40898828314027', 'NSGA-II_crowding_distance: 0.22279518186955027', 'NSGA-II_rank: 3', 'change: 0.1437343695212015', 'is_elite: False']\n", + "Id: 56_26 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_23', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_26', 'origin': '55_23~CUW~55_37#MGNP'} Metrics: ['ELUC: -9.77938415297855', 'NSGA-II_crowding_distance: 0.20109717704258406', 'NSGA-II_rank: 3', 'change: 0.1458456704264054', 'is_elite: False']\n", + "Id: 56_72 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_16', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_72', 'origin': '55_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.960486793808611', 'NSGA-II_crowding_distance: 1.0344874380803302', 'NSGA-II_rank: 6', 'change: 0.2738934016640447', 'is_elite: False']\n", + "Id: 56_93 Identity: {'ancestor_count': 54, 'ancestor_ids': ['1_1', '55_16'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_93', 'origin': '1_1~CUW~55_16#MGNP'} Metrics: ['ELUC: -10.044269402486009', 'NSGA-II_crowding_distance: 1.407282891811034', 'NSGA-II_rank: 5', 'change: 0.19552678539728302', 'is_elite: False']\n", + "Id: 56_57 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_16', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_57', 'origin': '55_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.129445597306036', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.29324120426509515', 'is_elite: False']\n", + "Id: 56_75 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_16', '55_44'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_75', 'origin': '55_16~CUW~55_44#MGNP'} Metrics: ['ELUC: -10.193934589288675', 'NSGA-II_crowding_distance: 0.09931172830817336', 'NSGA-II_rank: 2', 'change: 0.12484929236413234', 'is_elite: False']\n", + "Id: 56_27 Identity: {'ancestor_count': 52, 'ancestor_ids': ['2_49', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_27', 'origin': '2_49~CUW~54_51#MGNP'} Metrics: ['ELUC: -10.596395024095902', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2931310983377049', 'is_elite: False']\n", + "Id: 56_71 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_44', '55_44'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_71', 'origin': '55_44~CUW~55_44#MGNP'} Metrics: ['ELUC: -10.63991487131725', 'NSGA-II_crowding_distance: 0.03807184283671418', 'NSGA-II_rank: 2', 'change: 0.12606513764098262', 'is_elite: False']\n", + "Id: 55_44 Identity: {'ancestor_count': 50, 'ancestor_ids': ['51_44', '54_19'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_44', 'origin': '51_44~CUW~54_19#MGNP'} Metrics: ['ELUC: -10.747800551174647', 'NSGA-II_crowding_distance: 0.12794408587683015', 'NSGA-II_rank: 2', 'change: 0.12617178713165664', 'is_elite: False']\n", + "Id: 56_84 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '52_33'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_84', 'origin': '55_84~CUW~52_33#MGNP'} Metrics: ['ELUC: -10.771223220008585', 'NSGA-II_crowding_distance: 0.2576015002186907', 'NSGA-II_rank: 1', 'change: 0.12071928172471472', 'is_elite: True']\n", + "Id: 56_83 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '55_35'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_83', 'origin': '2_49~CUW~55_35#MGNP'} Metrics: ['ELUC: -11.005555920972817', 'NSGA-II_crowding_distance: 0.6440732559420427', 'NSGA-II_rank: 5', 'change: 0.2902855344902159', 'is_elite: False']\n", + "Id: 56_89 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_35', '54_58'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_89', 'origin': '55_35~CUW~54_58#MGNP'} Metrics: ['ELUC: -11.060900699128112', 'NSGA-II_crowding_distance: 0.9663367764224025', 'NSGA-II_rank: 4', 'change: 0.1709835485211788', 'is_elite: False']\n", + "Id: 56_39 Identity: {'ancestor_count': 53, 'ancestor_ids': ['54_58', '55_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_39', 'origin': '54_58~CUW~55_49#MGNP'} Metrics: ['ELUC: -11.105087010179728', 'NSGA-II_crowding_distance: 0.20279208435876397', 'NSGA-II_rank: 3', 'change: 0.15651219630104324', 'is_elite: False']\n", + "Id: 56_18 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '55_13'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_18', 'origin': '2_49~CUW~55_13#MGNP'} Metrics: ['ELUC: -11.252912906314629', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2912007761464581', 'is_elite: False']\n", + "Id: 56_58 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_49', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_58', 'origin': '55_49~CUW~55_37#MGNP'} Metrics: ['ELUC: -11.5758898172086', 'NSGA-II_crowding_distance: 0.8638204485130934', 'NSGA-II_rank: 3', 'change: 0.1572609586510904', 'is_elite: False']\n", + "Id: 56_14 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_84', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_14', 'origin': '55_84~CUW~55_37#MGNP'} Metrics: ['ELUC: -11.618313659353875', 'NSGA-II_crowding_distance: 0.12347701280363055', 'NSGA-II_rank: 1', 'change: 0.1388558989762101', 'is_elite: False']\n", + "Id: 56_31 Identity: {'ancestor_count': 52, 'ancestor_ids': ['52_33', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_31', 'origin': '52_33~CUW~54_51#MGNP'} Metrics: ['ELUC: -11.648414255930065', 'NSGA-II_crowding_distance: 0.20851008526888615', 'NSGA-II_rank: 2', 'change: 0.1437690878101929', 'is_elite: False']\n", + "Id: 56_24 Identity: {'ancestor_count': 52, 'ancestor_ids': ['52_33', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_24', 'origin': '52_33~CUW~54_51#MGNP'} Metrics: ['ELUC: -11.730223942514451', 'NSGA-II_crowding_distance: 0.09848641076409873', 'NSGA-II_rank: 1', 'change: 0.14128753278853584', 'is_elite: False']\n", + "Id: 56_88 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_91', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_88', 'origin': '55_91~CUW~55_37#MGNP'} Metrics: ['ELUC: -11.777368435453518', 'NSGA-II_crowding_distance: 0.7041747440811331', 'NSGA-II_rank: 4', 'change: 0.2879114087027398', 'is_elite: False']\n", + "Id: 56_43 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_44', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_43', 'origin': '55_44~CUW~55_91#MGNP'} Metrics: ['ELUC: -12.04998242282343', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2908841763653222', 'is_elite: False']\n", + "Id: 56_34 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_23', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_34', 'origin': '55_23~CUW~55_91#MGNP'} Metrics: ['ELUC: -12.192675553700663', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2900354867598593', 'is_elite: False']\n", + "Id: 56_16 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_37', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_16', 'origin': '55_37~CUW~55_37#MGNP'} Metrics: ['ELUC: -12.41826223998174', 'NSGA-II_crowding_distance: 0.15880862482409386', 'NSGA-II_rank: 2', 'change: 0.15460541441064313', 'is_elite: False']\n", + "Id: 55_37 Identity: {'ancestor_count': 52, 'ancestor_ids': ['54_51', '54_17'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_37', 'origin': '54_51~CUW~54_17#MGNP'} Metrics: ['ELUC: -12.523039998723924', 'NSGA-II_crowding_distance: 0.1268245588696291', 'NSGA-II_rank: 1', 'change: 0.15288856433011014', 'is_elite: False']\n", + "Id: 56_28 Identity: {'ancestor_count': 52, 'ancestor_ids': ['52_33', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_28', 'origin': '52_33~CUW~54_51#MGNP'} Metrics: ['ELUC: -12.67233631262654', 'NSGA-II_crowding_distance: 0.6172384149113483', 'NSGA-II_rank: 2', 'change: 0.16928662630944938', 'is_elite: False']\n", + "Id: 56_66 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_37', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_66', 'origin': '55_37~CUW~55_37#MGNP'} Metrics: ['ELUC: -12.956629783299643', 'NSGA-II_crowding_distance: 0.12480866649670233', 'NSGA-II_rank: 1', 'change: 0.15831666973342962', 'is_elite: False']\n", + "Id: 56_76 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_37', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_76', 'origin': '55_37~CUW~54_51#MGNP'} Metrics: ['ELUC: -13.183631675370703', 'NSGA-II_crowding_distance: 0.1239327201677756', 'NSGA-II_rank: 1', 'change: 0.17891824464750558', 'is_elite: False']\n", + "Id: 54_51 Identity: {'ancestor_count': 51, 'ancestor_ids': ['53_75', '51_44'], 'birth_generation': 54, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '54_51', 'origin': '53_75~CUW~51_44#MGNP'} Metrics: ['ELUC: -13.65168050911476', 'NSGA-II_crowding_distance: 0.05536797601248438', 'NSGA-II_rank: 1', 'change: 0.18350020650372928', 'is_elite: False']\n", + "Id: 56_23 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_37', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_23', 'origin': '55_37~CUW~55_37#MGNP'} Metrics: ['ELUC: -13.72760662470803', 'NSGA-II_crowding_distance: 0.10872606658595269', 'NSGA-II_rank: 1', 'change: 0.1862073922537186', 'is_elite: False']\n", + "Id: 56_80 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_35', '55_13'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_80', 'origin': '55_35~CUW~55_13#MGNP'} Metrics: ['ELUC: -14.363282535253985', 'NSGA-II_crowding_distance: 0.3756610691590233', 'NSGA-II_rank: 1', 'change: 0.20386553606794738', 'is_elite: True']\n", + "Id: 56_52 Identity: {'ancestor_count': 50, 'ancestor_ids': ['54_58', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_52', 'origin': '54_58~CUW~55_91#MGNP'} Metrics: ['ELUC: -14.470745740059845', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2783281524865007', 'is_elite: False']\n", + "Id: 56_33 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '55_16'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_33', 'origin': '2_49~CUW~55_16#MGNP'} Metrics: ['ELUC: -14.82882970994781', 'NSGA-II_crowding_distance: 0.6686151179596815', 'NSGA-II_rank: 2', 'change: 0.27818002664194463', 'is_elite: False']\n", + "Id: 56_86 Identity: {'ancestor_count': 4, 'ancestor_ids': ['55_91', '1_1'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_86', 'origin': '55_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.460907538440422', 'NSGA-II_crowding_distance: 0.22427534449772674', 'NSGA-II_rank: 2', 'change: 0.30038961575370227', 'is_elite: False']\n", + "Id: 56_77 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_49', '55_14'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_77', 'origin': '55_49~CUW~55_14#MGNP'} Metrics: ['ELUC: -16.07387106886112', 'NSGA-II_crowding_distance: 0.31714985073387925', 'NSGA-II_rank: 1', 'change: 0.25847945278770185', 'is_elite: True']\n", + "Id: 56_56 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_14', '55_37'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_56', 'origin': '55_14~CUW~55_37#MGNP'} Metrics: ['ELUC: -16.32252780421842', 'NSGA-II_crowding_distance: 0.09027592861766681', 'NSGA-II_rank: 1', 'change: 0.2652469876528839', 'is_elite: False']\n", + "Id: 56_82 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_16', '54_51'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_82', 'origin': '55_16~CUW~54_51#MGNP'} Metrics: ['ELUC: -16.65070300555222', 'NSGA-II_crowding_distance: 0.19893460719455358', 'NSGA-II_rank: 1', 'change: 0.27562676230482225', 'is_elite: False']\n", + "Id: 56_59 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_59', 'origin': '1_1~CUW~55_91#MGNP'} Metrics: ['ELUC: -16.857609946117613', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30515612268387377', 'is_elite: False']\n", + "Id: 56_41 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_37', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_41', 'origin': '55_37~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.596228551474955', 'NSGA-II_crowding_distance: 0.14564856056753517', 'NSGA-II_rank: 1', 'change: 0.30298954686269164', 'is_elite: False']\n", + "Id: 56_40 Identity: {'ancestor_count': 50, 'ancestor_ids': ['55_91', '54_58'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_40', 'origin': '55_91~CUW~54_58#MGNP'} Metrics: ['ELUC: -17.597358477769706', 'NSGA-II_crowding_distance: 0.000169489043103949', 'NSGA-II_rank: 1', 'change: 0.3030200118163471', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 55_91 Identity: {'ancestor_count': 3, 'ancestor_ids': ['54_77', '54_77'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_91', 'origin': '54_77~CUW~54_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 56_21 Identity: {'ancestor_count': 4, 'ancestor_ids': ['55_91', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_21', 'origin': '55_91~CUW~55_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 56_25 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_25', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 56_45 Identity: {'ancestor_count': 4, 'ancestor_ids': ['55_91', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_45', 'origin': '55_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 56_81 Identity: {'ancestor_count': 4, 'ancestor_ids': ['55_91', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_81', 'origin': '55_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 56_97 Identity: {'ancestor_count': 4, 'ancestor_ids': ['55_91', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_97', 'origin': '55_91~CUW~55_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 56_99 Identity: {'ancestor_count': 4, 'ancestor_ids': ['55_91', '55_91'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_99', 'origin': '55_91~CUW~55_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 56_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 56.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 57...:\n", + "PopulationResponse:\n", + " Generation: 57\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/57/20240220-023143\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 57 and asking ESP for generation 58...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 57 data persisted.\n", + "Evaluated candidates:\n", + "Id: 57_18 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_22', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_18', 'origin': '56_22~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 17', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 57_49 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_100', '56_80'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_49', 'origin': '56_100~CUW~56_80#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: 0', 'NSGA-II_rank: 17', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 57_51 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_49', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_51', 'origin': '56_49~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 17', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 57_92 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_92', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 22.13319381820052', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 16', 'change: 0.3001023976253923', 'is_elite: False']\n", + "Id: 57_71 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_71', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 16.639816203873526', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.276545647485434', 'is_elite: False']\n", + "Id: 57_48 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '56_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_48', 'origin': '2_49~CUW~56_77#MGNP'} Metrics: ['ELUC: 16.624999658847848', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 15', 'change: 0.3031527827782247', 'is_elite: False']\n", + "Id: 57_97 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_97', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 11.593424145169879', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.25965636167312495', 'is_elite: False']\n", + "Id: 57_98 Identity: {'ancestor_count': 52, 'ancestor_ids': ['2_49', '56_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_98', 'origin': '2_49~CUW~56_84#MGNP'} Metrics: ['ELUC: 10.87265714345634', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.2748730208173491', 'is_elite: False']\n", + "Id: 57_85 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_66', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_85', 'origin': '56_66~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.831000551548746', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 13', 'change: 0.2673433740352524', 'is_elite: False']\n", + "Id: 57_55 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_55', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.529316557895191', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.35172693340886096', 'is_elite: False']\n", + "Id: 57_15 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_82', '1_1'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_15', 'origin': '56_82~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.113497073467546', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06976761349151558', 'is_elite: False']\n", + "Id: 57_35 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '56_22'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_35', 'origin': '2_49~CUW~56_22#MGNP'} Metrics: ['ELUC: 0.8652712862173508', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.304239631313615', 'is_elite: False']\n", + "Id: 57_69 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_98', '1_1'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_69', 'origin': '56_98~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.014966737347133774', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.044307445443992545', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 57_23 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_23', 'origin': '1_1~CUW~55_77#MGNP'} Metrics: ['ELUC: -0.06574149469758496', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0420904946530059', 'is_elite: False']\n", + "Id: 57_47 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_77', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_47', 'origin': '56_77~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 57_28 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_100', '56_98'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_28', 'origin': '56_100~CUW~56_98#MGNP'} Metrics: ['ELUC: -0.5681133465449928', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.23867677775406143', 'is_elite: False']\n", + "Id: 57_78 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_98', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_78', 'origin': '56_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.6103298699905457', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23822430799941252', 'is_elite: False']\n", + "Id: 57_40 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_40', 'origin': '1_1~CUW~55_77#MGNP'} Metrics: ['ELUC: -0.747207715371363', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03906097959942278', 'is_elite: False']\n", + "Id: 57_70 Identity: {'ancestor_count': 52, 'ancestor_ids': ['55_77', '56_98'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_70', 'origin': '55_77~CUW~56_98#MGNP'} Metrics: ['ELUC: -0.7743205449987787', 'NSGA-II_crowding_distance: 0.4114140497729626', 'NSGA-II_rank: 4', 'change: 0.0697124216294502', 'is_elite: False']\n", + "Id: 57_39 Identity: {'ancestor_count': 3, 'ancestor_ids': ['55_77', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_39', 'origin': '55_77~CUW~55_77#MGNP'} Metrics: ['ELUC: -0.8745601535806878', 'NSGA-II_crowding_distance: 0.21103671221627435', 'NSGA-II_rank: 1', 'change: 0.032418143141609755', 'is_elite: False']\n", + "Id: 57_65 Identity: {'ancestor_count': 3, 'ancestor_ids': ['55_77', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_65', 'origin': '55_77~CUW~55_77#MGNP'} Metrics: ['ELUC: -1.0079879122144293', 'NSGA-II_crowding_distance: 0.27821504215829534', 'NSGA-II_rank: 3', 'change: 0.0570968925131891', 'is_elite: False']\n", + "Id: 57_89 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_89', 'origin': '2_49~CUW~55_77#MGNP'} Metrics: ['ELUC: -1.0347445151623291', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23634359399735827', 'is_elite: False']\n", + "Id: 57_57 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_49', '1_1'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_57', 'origin': '56_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6521794701600991', 'NSGA-II_crowding_distance: 0.16072018864662188', 'NSGA-II_rank: 2', 'change: 0.04529292545668304', 'is_elite: False']\n", + "Id: 55_77 Identity: {'ancestor_count': 2, 'ancestor_ids': ['50_89', '50_89'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_77', 'origin': '50_89~CUW~50_89#MGNP'} Metrics: ['ELUC: -1.7228911037057053', 'NSGA-II_crowding_distance: 0.0766572577998752', 'NSGA-II_rank: 1', 'change: 0.038628769851003185', 'is_elite: False']\n", + "Id: 57_88 Identity: {'ancestor_count': 3, 'ancestor_ids': ['55_77', '1_1'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_88', 'origin': '55_77~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.739164863375477', 'NSGA-II_crowding_distance: 0.05304304644943681', 'NSGA-II_rank: 1', 'change: 0.040618352145439005', 'is_elite: False']\n", + "Id: 57_58 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_49', '55_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_58', 'origin': '56_49~CUW~55_84#MGNP'} Metrics: ['ELUC: -2.041136634809877', 'NSGA-II_crowding_distance: 0.37857266124950084', 'NSGA-II_rank: 3', 'change: 0.08528384480449641', 'is_elite: False']\n", + "Id: 57_43 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '56_98'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_43', 'origin': '1_1~CUW~56_98#MGNP'} Metrics: ['ELUC: -2.240770555569203', 'NSGA-II_crowding_distance: 0.10622881884267375', 'NSGA-II_rank: 1', 'change: 0.045667058922040316', 'is_elite: False']\n", + "Id: 57_84 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_98', '56_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_84', 'origin': '56_98~CUW~56_49#MGNP'} Metrics: ['ELUC: -2.283319567224226', 'NSGA-II_crowding_distance: 0.12762127516642918', 'NSGA-II_rank: 2', 'change: 0.05742127412110412', 'is_elite: False']\n", + "Id: 57_74 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '55_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_74', 'origin': '1_1~CUW~55_84#MGNP'} Metrics: ['ELUC: -2.6045312449197975', 'NSGA-II_crowding_distance: 0.14175954897520926', 'NSGA-II_rank: 2', 'change: 0.06406109870713776', 'is_elite: False']\n", + "Id: 57_33 Identity: {'ancestor_count': 55, 'ancestor_ids': ['55_77', '56_80'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_33', 'origin': '55_77~CUW~56_80#MGNP'} Metrics: ['ELUC: -2.693760491471098', 'NSGA-II_crowding_distance: 0.30832946286590013', 'NSGA-II_rank: 4', 'change: 0.11068431293328954', 'is_elite: False']\n", + "Id: 57_72 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_90', '56_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_72', 'origin': '56_90~CUW~56_84#MGNP'} Metrics: ['ELUC: -2.8462512837709943', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1328537994973589', 'is_elite: False']\n", + "Id: 57_64 Identity: {'ancestor_count': 54, 'ancestor_ids': ['1_1', '56_22'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_64', 'origin': '1_1~CUW~56_22#MGNP'} Metrics: ['ELUC: -2.865483541557193', 'NSGA-II_crowding_distance: 0.14740357261554027', 'NSGA-II_rank: 1', 'change: 0.053200689248299446', 'is_elite: False']\n", + "Id: 57_42 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_84', '56_98'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_42', 'origin': '56_84~CUW~56_98#MGNP'} Metrics: ['ELUC: -3.0047410031939377', 'NSGA-II_crowding_distance: 0.10199477199093465', 'NSGA-II_rank: 4', 'change: 0.11647686641909022', 'is_elite: False']\n", + "Id: 57_94 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '56_80'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_94', 'origin': '1_1~CUW~56_80#MGNP'} Metrics: ['ELUC: -3.0998472281425635', 'NSGA-II_crowding_distance: 0.4354351461252107', 'NSGA-II_rank: 2', 'change: 0.08204907449768341', 'is_elite: False']\n", + "Id: 57_25 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_98', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_25', 'origin': '56_98~CUW~56_90#MGNP'} Metrics: ['ELUC: -3.1765722955744446', 'NSGA-II_crowding_distance: 0.2461017140367875', 'NSGA-II_rank: 1', 'change: 0.0737681560975586', 'is_elite: True']\n", + "Id: 57_27 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_77', '56_98'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_27', 'origin': '56_77~CUW~56_98#MGNP'} Metrics: ['ELUC: -3.7678969483903857', 'NSGA-II_crowding_distance: 0.12237797699511863', 'NSGA-II_rank: 4', 'change: 0.12115112373987054', 'is_elite: False']\n", + "Id: 57_24 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_77', '56_22'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_24', 'origin': '56_77~CUW~56_22#MGNP'} Metrics: ['ELUC: -3.8720741274833372', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.147372369520407', 'is_elite: False']\n", + "Id: 57_62 Identity: {'ancestor_count': 55, 'ancestor_ids': ['55_77', '56_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_62', 'origin': '55_77~CUW~56_77#MGNP'} Metrics: ['ELUC: -4.090982895386125', 'NSGA-II_crowding_distance: 0.34248655663623934', 'NSGA-II_rank: 3', 'change: 0.10999126191963594', 'is_elite: False']\n", + "Id: 57_37 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_77', '55_37'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_37', 'origin': '55_77~CUW~55_37#MGNP'} Metrics: ['ELUC: -4.741572449992504', 'NSGA-II_crowding_distance: 0.3112194688789303', 'NSGA-II_rank: 4', 'change: 0.12237086150887089', 'is_elite: False']\n", + "Id: 57_80 Identity: {'ancestor_count': 55, 'ancestor_ids': ['55_77', '56_80'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_80', 'origin': '55_77~CUW~56_80#MGNP'} Metrics: ['ELUC: -5.3980180489575655', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.13218143593965342', 'is_elite: False']\n", + "Id: 55_84 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_84', 'origin': '1_1~CUW~52_33#MGNP'} Metrics: ['ELUC: -5.592011266999677', 'NSGA-II_crowding_distance: 0.3025526912676571', 'NSGA-II_rank: 1', 'change: 0.08036194045690388', 'is_elite: True']\n", + "Id: 57_96 Identity: {'ancestor_count': 3, 'ancestor_ids': ['55_77', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_96', 'origin': '55_77~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.792544933945751', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2915097453408176', 'is_elite: False']\n", + "Id: 57_34 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_82', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_34', 'origin': '56_82~CUW~55_77#MGNP'} Metrics: ['ELUC: -6.079505305229266', 'NSGA-II_crowding_distance: 0.2318332315118291', 'NSGA-II_rank: 3', 'change: 0.11454257127032307', 'is_elite: False']\n", + "Id: 57_86 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '56_82'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_86', 'origin': '2_49~CUW~56_82#MGNP'} Metrics: ['ELUC: -6.506054198816165', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2370063146286593', 'is_elite: False']\n", + "Id: 57_45 Identity: {'ancestor_count': 55, 'ancestor_ids': ['55_37', '56_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_45', 'origin': '55_37~CUW~56_49#MGNP'} Metrics: ['ELUC: -7.089162355263111', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1439933722283354', 'is_elite: False']\n", + "Id: 57_59 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_22', '56_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_59', 'origin': '56_22~CUW~56_84#MGNP'} Metrics: ['ELUC: -7.132221855244991', 'NSGA-II_crowding_distance: 0.417903117409141', 'NSGA-II_rank: 2', 'change: 0.10807167546924132', 'is_elite: False']\n", + "Id: 56_22 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_49', '55_84'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_22', 'origin': '55_49~CUW~55_84#MGNP'} Metrics: ['ELUC: -7.190135053074711', 'NSGA-II_crowding_distance: 0.2648832623999763', 'NSGA-II_rank: 1', 'change: 0.09593173974959476', 'is_elite: True']\n", + "Id: 57_56 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_84', '1_1'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_56', 'origin': '56_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.2579557496730605', 'NSGA-II_crowding_distance: 1.1249532283381591', 'NSGA-II_rank: 6', 'change: 0.14384800799438874', 'is_elite: False']\n", + "Id: 57_54 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_90', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_54', 'origin': '56_90~CUW~55_77#MGNP'} Metrics: ['ELUC: -7.655097050714251', 'NSGA-II_crowding_distance: 0.20107862054595313', 'NSGA-II_rank: 3', 'change: 0.11743586756767882', 'is_elite: False']\n", + "Id: 57_20 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_90', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_20', 'origin': '56_90~CUW~56_90#MGNP'} Metrics: ['ELUC: -8.00632903364141', 'NSGA-II_crowding_distance: 0.2221744154467922', 'NSGA-II_rank: 2', 'change: 0.11549811093438199', 'is_elite: False']\n", + "Id: 57_17 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_84', '56_76'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_17', 'origin': '55_84~CUW~56_76#MGNP'} Metrics: ['ELUC: -8.061819624096136', 'NSGA-II_crowding_distance: 0.9955618515156888', 'NSGA-II_rank: 5', 'change: 0.13046455259876724', 'is_elite: False']\n", + "Id: 57_81 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_90', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_81', 'origin': '56_90~CUW~56_90#MGNP'} Metrics: ['ELUC: -8.25542068037421', 'NSGA-II_crowding_distance: 0.13811074339039595', 'NSGA-II_rank: 1', 'change: 0.1141983243453254', 'is_elite: False']\n", + "Id: 57_53 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_84', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_53', 'origin': '56_84~CUW~55_77#MGNP'} Metrics: ['ELUC: -8.31801103423311', 'NSGA-II_crowding_distance: 0.9102390617453145', 'NSGA-II_rank: 5', 'change: 0.13599838952990126', 'is_elite: False']\n", + "Id: 56_90 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '55_55'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_90', 'origin': '55_84~CUW~55_55#MGNP'} Metrics: ['ELUC: -8.362820093278753', 'NSGA-II_crowding_distance: 0.1649416139200311', 'NSGA-II_rank: 1', 'change: 0.11724008117666955', 'is_elite: False']\n", + "Id: 57_91 Identity: {'ancestor_count': 51, 'ancestor_ids': ['2_49', '55_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_91', 'origin': '2_49~CUW~55_84#MGNP'} Metrics: ['ELUC: -8.543966636036043', 'NSGA-II_crowding_distance: 1.0914341245645451', 'NSGA-II_rank: 6', 'change: 0.26235551781553', 'is_elite: False']\n", + "Id: 57_14 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_84', '56_14'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_14', 'origin': '55_84~CUW~56_14#MGNP'} Metrics: ['ELUC: -8.832099774003359', 'NSGA-II_crowding_distance: 0.3269165147986129', 'NSGA-II_rank: 4', 'change: 0.12651196839857087', 'is_elite: False']\n", + "Id: 57_19 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_22', '56_80'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_19', 'origin': '56_22~CUW~56_80#MGNP'} Metrics: ['ELUC: -8.941256194321149', 'NSGA-II_crowding_distance: 0.6260738527817908', 'NSGA-II_rank: 4', 'change: 0.14466140664748733', 'is_elite: False']\n", + "Id: 57_52 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_90', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_52', 'origin': '56_90~CUW~56_90#MGNP'} Metrics: ['ELUC: -8.942495741495675', 'NSGA-II_crowding_distance: 0.15747152841028417', 'NSGA-II_rank: 3', 'change: 0.12439778938547041', 'is_elite: False']\n", + "Id: 57_100 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_90', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_100', 'origin': '56_90~CUW~56_90#MGNP'} Metrics: ['ELUC: -9.299869491059138', 'NSGA-II_crowding_distance: 0.11581020003953998', 'NSGA-II_rank: 3', 'change: 0.13404445702518178', 'is_elite: False']\n", + "Id: 57_13 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_37', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_13', 'origin': '55_37~CUW~55_77#MGNP'} Metrics: ['ELUC: -9.302832469225757', 'NSGA-II_crowding_distance: 0.5858145737839942', 'NSGA-II_rank: 3', 'change: 0.1492530363630175', 'is_elite: False']\n", + "Id: 57_95 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_100', '56_22'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_95', 'origin': '56_100~CUW~56_22#MGNP'} Metrics: ['ELUC: -9.720598912185999', 'NSGA-II_crowding_distance: 0.8750467716618407', 'NSGA-II_rank: 6', 'change: 0.2850968758663075', 'is_elite: False']\n", + "Id: 57_83 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_66', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_83', 'origin': '56_66~CUW~56_90#MGNP'} Metrics: ['ELUC: -9.969322461608751', 'NSGA-II_crowding_distance: 0.1507858959866653', 'NSGA-II_rank: 2', 'change: 0.12227329770078063', 'is_elite: False']\n", + "Id: 57_75 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_22', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_75', 'origin': '56_22~CUW~56_90#MGNP'} Metrics: ['ELUC: -9.997751370384856', 'NSGA-II_crowding_distance: 0.33083173405013844', 'NSGA-II_rank: 2', 'change: 0.12410367841152692', 'is_elite: False']\n", + "Id: 56_84 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '52_33'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_84', 'origin': '55_84~CUW~52_33#MGNP'} Metrics: ['ELUC: -10.771223220008585', 'NSGA-II_crowding_distance: 0.30942276602523955', 'NSGA-II_rank: 1', 'change: 0.12071928172471472', 'is_elite: True']\n", + "Id: 57_87 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_87', 'origin': '56_80~CUW~56_84#MGNP'} Metrics: ['ELUC: -11.188067523511563', 'NSGA-II_crowding_distance: 0.2768088329332768', 'NSGA-II_rank: 1', 'change: 0.1616196193367384', 'is_elite: True']\n", + "Id: 57_46 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '55_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_46', 'origin': '56_80~CUW~55_84#MGNP'} Metrics: ['ELUC: -11.882325520262349', 'NSGA-II_crowding_distance: 0.5684980657168185', 'NSGA-II_rank: 2', 'change: 0.17963211178374217', 'is_elite: False']\n", + "Id: 57_50 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_41', '56_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_50', 'origin': '56_41~CUW~56_84#MGNP'} Metrics: ['ELUC: -11.987209165557022', 'NSGA-II_crowding_distance: 1.0044381484843115', 'NSGA-II_rank: 5', 'change: 0.25927575402349323', 'is_elite: False']\n", + "Id: 57_60 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_60', 'origin': '56_80~CUW~56_84#MGNP'} Metrics: ['ELUC: -12.531453914465729', 'NSGA-II_crowding_distance: 0.20390846001639992', 'NSGA-II_rank: 1', 'change: 0.1734412112821159', 'is_elite: False']\n", + "Id: 57_26 Identity: {'ancestor_count': 3, 'ancestor_ids': ['55_77', '56_100'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_26', 'origin': '55_77~CUW~56_100#MGNP'} Metrics: ['ELUC: -12.75682457009661', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.31882559777753094', 'is_elite: False']\n", + "Id: 57_32 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_100'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_32', 'origin': '56_80~CUW~56_100#MGNP'} Metrics: ['ELUC: -12.938756058817837', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2739392328651972', 'is_elite: False']\n", + "Id: 57_31 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '56_82'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_31', 'origin': '1_1~CUW~56_82#MGNP'} Metrics: ['ELUC: -13.130267649613756', 'NSGA-II_crowding_distance: 0.13696775260620414', 'NSGA-II_rank: 1', 'change: 0.1895016249141355', 'is_elite: False']\n", + "Id: 57_93 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_82', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_93', 'origin': '56_82~CUW~55_77#MGNP'} Metrics: ['ELUC: -13.21971267293421', 'NSGA-II_crowding_distance: 0.7867017599716366', 'NSGA-II_rank: 4', 'change: 0.22357119438652656', 'is_elite: False']\n", + "Id: 57_77 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '56_82'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_77', 'origin': '1_1~CUW~56_82#MGNP'} Metrics: ['ELUC: -13.673373345678364', 'NSGA-II_crowding_distance: 0.7082214582427214', 'NSGA-II_rank: 3', 'change: 0.22180686032850153', 'is_elite: False']\n", + "Id: 57_41 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_82', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_41', 'origin': '56_82~CUW~56_90#MGNP'} Metrics: ['ELUC: -13.908292141827372', 'NSGA-II_crowding_distance: 0.44738373678442667', 'NSGA-II_rank: 2', 'change: 0.2129051749453774', 'is_elite: False']\n", + "Id: 57_44 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_44', 'origin': '56_80~CUW~56_84#MGNP'} Metrics: ['ELUC: -13.950670686049516', 'NSGA-II_crowding_distance: 0.11826806104751911', 'NSGA-II_rank: 1', 'change: 0.1902247902767892', 'is_elite: False']\n", + "Id: 57_36 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_100', '56_80'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_36', 'origin': '56_100~CUW~56_80#MGNP'} Metrics: ['ELUC: -14.192944251126502', 'NSGA-II_crowding_distance: 0.5492978565753817', 'NSGA-II_rank: 4', 'change: 0.2705142670207533', 'is_elite: False']\n", + "Id: 56_80 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_35', '55_13'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_80', 'origin': '55_35~CUW~55_13#MGNP'} Metrics: ['ELUC: -14.363282535253985', 'NSGA-II_crowding_distance: 0.28376862114693285', 'NSGA-II_rank: 1', 'change: 0.20386553606794738', 'is_elite: True']\n", + "Id: 57_63 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_82', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_63', 'origin': '56_82~CUW~55_77#MGNP'} Metrics: ['ELUC: -15.008727408162798', 'NSGA-II_crowding_distance: 0.5350498794156453', 'NSGA-II_rank: 3', 'change: 0.24912402734693723', 'is_elite: False']\n", + "Id: 57_66 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_82'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_66', 'origin': '56_80~CUW~56_82#MGNP'} Metrics: ['ELUC: -15.01782219469302', 'NSGA-II_crowding_distance: 0.22045143406259038', 'NSGA-II_rank: 2', 'change: 0.2486054655951452', 'is_elite: False']\n", + "Id: 57_99 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_77', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_99', 'origin': '56_77~CUW~56_90#MGNP'} Metrics: ['ELUC: -15.181290840362808', 'NSGA-II_crowding_distance: 0.15361715018557467', 'NSGA-II_rank: 2', 'change: 0.2511537861021499', 'is_elite: False']\n", + "Id: 57_67 Identity: {'ancestor_count': 3, 'ancestor_ids': ['55_77', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_67', 'origin': '55_77~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.511544703164404', 'NSGA-II_crowding_distance: 0.20301503918330766', 'NSGA-II_rank: 2', 'change: 0.28141996147501697', 'is_elite: False']\n", + "Id: 57_76 Identity: {'ancestor_count': 55, 'ancestor_ids': ['55_37', '56_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_76', 'origin': '55_37~CUW~56_77#MGNP'} Metrics: ['ELUC: -15.572389082606916', 'NSGA-II_crowding_distance: 0.2803263355618409', 'NSGA-II_rank: 1', 'change: 0.24737396191429387', 'is_elite: True']\n", + "Id: 57_82 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_100'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_82', 'origin': '56_80~CUW~56_100#MGNP'} Metrics: ['ELUC: -15.97462470394047', 'NSGA-II_crowding_distance: 0.20562011070592506', 'NSGA-II_rank: 2', 'change: 0.292313885327793', 'is_elite: False']\n", + "Id: 56_77 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_49', '55_14'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_77', 'origin': '55_49~CUW~55_14#MGNP'} Metrics: ['ELUC: -16.07387106886112', 'NSGA-II_crowding_distance: 0.07823518232348325', 'NSGA-II_rank: 1', 'change: 0.25847945278770185', 'is_elite: False']\n", + "Id: 57_61 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_77', '56_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_61', 'origin': '56_77~CUW~56_77#MGNP'} Metrics: ['ELUC: -16.150430128006136', 'NSGA-II_crowding_distance: 0.05578780450158173', 'NSGA-II_rank: 1', 'change: 0.26090806212542805', 'is_elite: False']\n", + "Id: 57_12 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_77', '56_82'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_12', 'origin': '56_77~CUW~56_82#MGNP'} Metrics: ['ELUC: -16.446033636055944', 'NSGA-II_crowding_distance: 0.06967958813295648', 'NSGA-II_rank: 1', 'change: 0.2688095769309291', 'is_elite: False']\n", + "Id: 57_79 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_82', '56_82'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_79', 'origin': '56_82~CUW~56_82#MGNP'} Metrics: ['ELUC: -16.602845130808774', 'NSGA-II_crowding_distance: 0.1722694510732211', 'NSGA-II_rank: 1', 'change: 0.27402127635366186', 'is_elite: False']\n", + "Id: 57_29 Identity: {'ancestor_count': 3, 'ancestor_ids': ['55_77', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_29', 'origin': '55_77~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.41515222684477', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.303582894757314', 'is_elite: False']\n", + "Id: 57_73 Identity: {'ancestor_count': 3, 'ancestor_ids': ['56_100', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_73', 'origin': '56_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.49954448982421', 'NSGA-II_crowding_distance: 0.15367624852755668', 'NSGA-II_rank: 1', 'change: 0.30233253815179983', 'is_elite: False']\n", + "Id: 57_21 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '56_22'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_21', 'origin': '2_49~CUW~56_22#MGNP'} Metrics: ['ELUC: -17.59646611525537', 'NSGA-II_crowding_distance: 0.007869701971898489', 'NSGA-II_rank: 1', 'change: 0.3030127898346074', 'is_elite: False']\n", + "Id: 57_11 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_11', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.59684915597743', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30302135068447716', 'is_elite: False']\n", + "Id: 57_38 Identity: {'ancestor_count': 3, 'ancestor_ids': ['56_100', '56_100'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_38', 'origin': '56_100~CUW~56_100#MGNP'} Metrics: ['ELUC: -17.597380824017247', 'NSGA-II_crowding_distance: 7.807972811450454e-05', 'NSGA-II_rank: 1', 'change: 0.30302036909770236', 'is_elite: False']\n", + "Id: 57_90 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_66', '2_49'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_90', 'origin': '56_66~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59738719044365', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 56_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 57_16 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '56_100'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_16', 'origin': '2_49~CUW~56_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 57_22 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '56_100'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_22', 'origin': '2_49~CUW~56_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 57_30 Identity: {'ancestor_count': 3, 'ancestor_ids': ['56_100', '55_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_30', 'origin': '56_100~CUW~55_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 57_68 Identity: {'ancestor_count': 3, 'ancestor_ids': ['56_100', '56_100'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_68', 'origin': '56_100~CUW~56_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 57.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 58...:\n", + "PopulationResponse:\n", + " Generation: 58\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/58/20240220-023856\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 58 and asking ESP for generation 59...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 58 data persisted.\n", + "Evaluated candidates:\n", + "Id: 58_99 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '57_68'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_99', 'origin': '1_1~CUW~57_68#MGNP'} Metrics: ['ELUC: 22.957255214451802', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.29482486854137036', 'is_elite: False']\n", + "Id: 58_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_54', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 19.616294329480162', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2722442626728905', 'is_elite: False']\n", + "Id: 58_47 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '57_68'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_47', 'origin': '57_76~CUW~57_68#MGNP'} Metrics: ['ELUC: 17.132287497171966', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28637325459673385', 'is_elite: False']\n", + "Id: 58_62 Identity: {'ancestor_count': 56, 'ancestor_ids': ['2_49', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_62', 'origin': '2_49~CUW~57_76#MGNP'} Metrics: ['ELUC: 12.805086076925049', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24593836588145676', 'is_elite: False']\n", + "Id: 58_22 Identity: {'ancestor_count': 51, 'ancestor_ids': ['57_68', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_22', 'origin': '57_68~CUW~55_84#MGNP'} Metrics: ['ELUC: 12.025207767316157', 'NSGA-II_crowding_distance: 1.0780580782855604', 'NSGA-II_rank: 10', 'change: 0.25710365459896006', 'is_elite: False']\n", + "Id: 58_30 Identity: {'ancestor_count': 4, 'ancestor_ids': ['57_39', '2_49'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_30', 'origin': '57_39~CUW~2_49#MGNP'} Metrics: ['ELUC: 10.646610153698914', 'NSGA-II_crowding_distance: 1.7570718237570817', 'NSGA-II_rank: 10', 'change: 0.3007534244131005', 'is_elite: False']\n", + "Id: 58_38 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '57_39'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_38', 'origin': '1_1~CUW~57_39#MGNP'} Metrics: ['ELUC: 1.3812206740749575', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06452036879550778', 'is_elite: False']\n", + "Id: 58_15 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_87', '1_1'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_15', 'origin': '57_87~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.0639766826813013', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.093313911525588', 'is_elite: False']\n", + "Id: 58_97 Identity: {'ancestor_count': 56, 'ancestor_ids': ['1_1', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_97', 'origin': '1_1~CUW~57_87#MGNP'} Metrics: ['ELUC: 0.9865789712999085', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11358675235771301', 'is_elite: False']\n", + "Id: 58_93 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_93', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.5447755665650147', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03348548174646771', 'is_elite: False']\n", + "Id: 58_84 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_84', 'origin': '1_1~CUW~55_84#MGNP'} Metrics: ['ELUC: 0.08536218774321311', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06433151592457287', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 58_61 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_61', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5618404104098266', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23629097560625534', 'is_elite: False']\n", + "Id: 58_19 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_25', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_19', 'origin': '57_25~CUW~57_87#MGNP'} Metrics: ['ELUC: -0.9033877939663338', 'NSGA-II_crowding_distance: 0.7446476899525222', 'NSGA-II_rank: 6', 'change: 0.12771316056120613', 'is_elite: False']\n", + "Id: 58_78 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '57_68'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_78', 'origin': '57_76~CUW~57_68#MGNP'} Metrics: ['ELUC: -1.3240354837184893', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2516450148388864', 'is_elite: False']\n", + "Id: 58_21 Identity: {'ancestor_count': 52, 'ancestor_ids': ['57_73', '56_90'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_21', 'origin': '57_73~CUW~56_90#MGNP'} Metrics: ['ELUC: -1.7725560925495243', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3048798900380377', 'is_elite: False']\n", + "Id: 58_79 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_79', 'origin': '1_1~CUW~55_84#MGNP'} Metrics: ['ELUC: -1.970898184381996', 'NSGA-II_crowding_distance: 0.4164701676532093', 'NSGA-II_rank: 1', 'change: 0.05749453171041659', 'is_elite: True']\n", + "Id: 58_39 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '57_64'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_39', 'origin': '57_76~CUW~57_64#MGNP'} Metrics: ['ELUC: -2.1993341460042104', 'NSGA-II_crowding_distance: 0.7262430279901038', 'NSGA-II_rank: 5', 'change: 0.0938763004059679', 'is_elite: False']\n", + "Id: 58_17 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '1_1'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_17', 'origin': '55_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2231987622671956', 'NSGA-II_crowding_distance: 0.41650328340173637', 'NSGA-II_rank: 4', 'change: 0.0732231787103575', 'is_elite: False']\n", + "Id: 58_26 Identity: {'ancestor_count': 53, 'ancestor_ids': ['57_25', '57_25'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_26', 'origin': '57_25~CUW~57_25#MGNP'} Metrics: ['ELUC: -2.360656265697533', 'NSGA-II_crowding_distance: 0.2665191603511068', 'NSGA-II_rank: 3', 'change: 0.07234238901648245', 'is_elite: False']\n", + "Id: 58_90 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_90', 'origin': '1_1~CUW~55_84#MGNP'} Metrics: ['ELUC: -2.634485564564398', 'NSGA-II_crowding_distance: 0.31765316226760965', 'NSGA-II_rank: 2', 'change: 0.06381438639143243', 'is_elite: False']\n", + "Id: 58_34 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '56_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_34', 'origin': '1_1~CUW~56_84#MGNP'} Metrics: ['ELUC: -2.659500160457383', 'NSGA-II_crowding_distance: 0.23499939338851883', 'NSGA-II_rank: 4', 'change: 0.09335445429178696', 'is_elite: False']\n", + "Id: 58_82 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_82', 'origin': '1_1~CUW~55_84#MGNP'} Metrics: ['ELUC: -2.8637465749487907', 'NSGA-II_crowding_distance: 0.06938160393559482', 'NSGA-II_rank: 2', 'change: 0.06444803252912222', 'is_elite: False']\n", + "Id: 58_81 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_90', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_81', 'origin': '56_90~CUW~57_87#MGNP'} Metrics: ['ELUC: -2.87116616055518', 'NSGA-II_crowding_distance: 0.14179402104954142', 'NSGA-II_rank: 4', 'change: 0.11196143929916355', 'is_elite: False']\n", + "Id: 57_25 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_98', '56_90'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_25', 'origin': '56_98~CUW~56_90#MGNP'} Metrics: ['ELUC: -3.1765722955744446', 'NSGA-II_crowding_distance: 0.2057847614597741', 'NSGA-II_rank: 3', 'change: 0.0737681560975586', 'is_elite: False']\n", + "Id: 58_85 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '57_25'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_85', 'origin': '56_80~CUW~57_25#MGNP'} Metrics: ['ELUC: -3.3304806289886515', 'NSGA-II_crowding_distance: 0.10812138491772316', 'NSGA-II_rank: 4', 'change: 0.11287289984067952', 'is_elite: False']\n", + "Id: 58_72 Identity: {'ancestor_count': 53, 'ancestor_ids': ['57_25', '57_39'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_72', 'origin': '57_25~CUW~57_39#MGNP'} Metrics: ['ELUC: -3.4332567330855737', 'NSGA-II_crowding_distance: 0.12708816295151484', 'NSGA-II_rank: 2', 'change: 0.06973012555538133', 'is_elite: False']\n", + "Id: 58_46 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '56_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_46', 'origin': '1_1~CUW~56_84#MGNP'} Metrics: ['ELUC: -3.508141883787093', 'NSGA-II_crowding_distance: 0.2865338911178557', 'NSGA-II_rank: 3', 'change: 0.10094169381012073', 'is_elite: False']\n", + "Id: 58_29 Identity: {'ancestor_count': 56, 'ancestor_ids': ['1_1', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_29', 'origin': '1_1~CUW~57_87#MGNP'} Metrics: ['ELUC: -3.842658805665682', 'NSGA-II_crowding_distance: 0.34006617634857883', 'NSGA-II_rank: 4', 'change: 0.12051298965451353', 'is_elite: False']\n", + "Id: 58_65 Identity: {'ancestor_count': 54, 'ancestor_ids': ['57_39', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_65', 'origin': '57_39~CUW~56_22#MGNP'} Metrics: ['ELUC: -3.8923608700709917', 'NSGA-II_crowding_distance: 0.2239301889136833', 'NSGA-II_rank: 1', 'change: 0.0631089642439499', 'is_elite: True']\n", + "Id: 58_55 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_25', '57_60'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_55', 'origin': '57_25~CUW~57_60#MGNP'} Metrics: ['ELUC: -4.343703603017242', 'NSGA-II_crowding_distance: 0.43070374797980954', 'NSGA-II_rank: 3', 'change: 0.12028345088891733', 'is_elite: False']\n", + "Id: 58_36 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_36', 'origin': '1_1~CUW~55_84#MGNP'} Metrics: ['ELUC: -4.469373048910574', 'NSGA-II_crowding_distance: 0.24262175120126775', 'NSGA-II_rank: 2', 'change: 0.0730604558418456', 'is_elite: False']\n", + "Id: 58_27 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_22', '57_64'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_27', 'origin': '56_22~CUW~57_64#MGNP'} Metrics: ['ELUC: -5.043439252962956', 'NSGA-II_crowding_distance: 0.1544906506282584', 'NSGA-II_rank: 1', 'change: 0.07216834086538636', 'is_elite: False']\n", + "Id: 55_84 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_84', 'origin': '1_1~CUW~52_33#MGNP'} Metrics: ['ELUC: -5.592011266999677', 'NSGA-II_crowding_distance: 0.17504377784984176', 'NSGA-II_rank: 1', 'change: 0.08036194045690388', 'is_elite: True']\n", + "Id: 58_59 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_22', '56_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_59', 'origin': '56_22~CUW~56_84#MGNP'} Metrics: ['ELUC: -5.977813370211692', 'NSGA-II_crowding_distance: 0.2503083310002514', 'NSGA-II_rank: 2', 'change: 0.09429754874618737', 'is_elite: False']\n", + "Id: 58_53 Identity: {'ancestor_count': 56, 'ancestor_ids': ['2_49', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_53', 'origin': '2_49~CUW~57_87#MGNP'} Metrics: ['ELUC: -6.105578384288559', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2551171036475193', 'is_elite: False']\n", + "Id: 58_40 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_84', '57_39'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_40', 'origin': '56_84~CUW~57_39#MGNP'} Metrics: ['ELUC: -6.342477760358057', 'NSGA-II_crowding_distance: 0.5977933721617108', 'NSGA-II_rank: 5', 'change: 0.1285689233708437', 'is_elite: False']\n", + "Id: 58_41 Identity: {'ancestor_count': 56, 'ancestor_ids': ['1_1', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_41', 'origin': '1_1~CUW~57_76#MGNP'} Metrics: ['ELUC: -6.347006565073077', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.1803061928923011', 'is_elite: False']\n", + "Id: 58_86 Identity: {'ancestor_count': 56, 'ancestor_ids': ['55_84', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_86', 'origin': '55_84~CUW~57_87#MGNP'} Metrics: ['ELUC: -6.515400966419681', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1405545885830721', 'is_elite: False']\n", + "Id: 58_44 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_44', 'origin': '57_76~CUW~56_22#MGNP'} Metrics: ['ELUC: -6.617696162942445', 'NSGA-II_crowding_distance: 0.70729196164893', 'NSGA-II_rank: 6', 'change: 0.1381170828167213', 'is_elite: False']\n", + "Id: 58_43 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_64', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_43', 'origin': '57_64~CUW~57_76#MGNP'} Metrics: ['ELUC: -6.852299253294782', 'NSGA-II_crowding_distance: 0.5236721643175459', 'NSGA-II_rank: 6', 'change: 0.16908492082350118', 'is_elite: False']\n", + "Id: 58_75 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_22', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_75', 'origin': '56_22~CUW~56_22#MGNP'} Metrics: ['ELUC: -6.909728408597612', 'NSGA-II_crowding_distance: 0.1406681797148396', 'NSGA-II_rank: 1', 'change: 0.09272600111398288', 'is_elite: False']\n", + "Id: 58_23 Identity: {'ancestor_count': 53, 'ancestor_ids': ['56_84', '57_25'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_23', 'origin': '56_84~CUW~57_25#MGNP'} Metrics: ['ELUC: -7.025154729388813', 'NSGA-II_crowding_distance: 0.12765345858322263', 'NSGA-II_rank: 2', 'change: 0.09948901316245376', 'is_elite: False']\n", + "Id: 58_67 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_60', '57_79'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_67', 'origin': '57_60~CUW~57_79#MGNP'} Metrics: ['ELUC: -7.167131770011', 'NSGA-II_crowding_distance: 0.8281008361593166', 'NSGA-II_rank: 6', 'change: 0.22343833736094396', 'is_elite: False']\n", + "Id: 58_80 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_22', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_80', 'origin': '56_22~CUW~56_22#MGNP'} Metrics: ['ELUC: -7.168668990250707', 'NSGA-II_crowding_distance: 0.026692093346983678', 'NSGA-II_rank: 1', 'change: 0.09557782296642399', 'is_elite: False']\n", + "Id: 56_22 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_49', '55_84'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_22', 'origin': '55_49~CUW~55_84#MGNP'} Metrics: ['ELUC: -7.190135053074711', 'NSGA-II_crowding_distance: 0.06064531708712176', 'NSGA-II_rank: 1', 'change: 0.09593173974959476', 'is_elite: False']\n", + "Id: 58_37 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '56_90'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_37', 'origin': '1_1~CUW~56_90#MGNP'} Metrics: ['ELUC: -7.204693994537621', 'NSGA-II_crowding_distance: 0.07499046057227239', 'NSGA-II_rank: 2', 'change: 0.10896992673860904', 'is_elite: False']\n", + "Id: 58_66 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_90', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_66', 'origin': '56_90~CUW~56_22#MGNP'} Metrics: ['ELUC: -7.411741931424799', 'NSGA-II_crowding_distance: 0.1468972732287937', 'NSGA-II_rank: 2', 'change: 0.11332261675158317', 'is_elite: False']\n", + "Id: 58_42 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_60', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_42', 'origin': '57_60~CUW~56_22#MGNP'} Metrics: ['ELUC: -7.5550105779102985', 'NSGA-II_crowding_distance: 0.15747948879667312', 'NSGA-II_rank: 5', 'change: 0.13339030438313987', 'is_elite: False']\n", + "Id: 58_83 Identity: {'ancestor_count': 54, 'ancestor_ids': ['56_22', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_83', 'origin': '56_22~CUW~56_22#MGNP'} Metrics: ['ELUC: -7.631160287709301', 'NSGA-II_crowding_distance: 0.08939362233573836', 'NSGA-II_rank: 1', 'change: 0.10582441422347591', 'is_elite: False']\n", + "Id: 58_95 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_80', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_95', 'origin': '56_80~CUW~57_76#MGNP'} Metrics: ['ELUC: -7.6550885269051685', 'NSGA-II_crowding_distance: 1.0590549213531992', 'NSGA-II_rank: 5', 'change: 0.14037026045917736', 'is_elite: False']\n", + "Id: 58_20 Identity: {'ancestor_count': 53, 'ancestor_ids': ['56_84', '57_25'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_20', 'origin': '56_84~CUW~57_25#MGNP'} Metrics: ['ELUC: -7.675441312534275', 'NSGA-II_crowding_distance: 0.4594543770490912', 'NSGA-II_rank: 4', 'change: 0.12201571702155035', 'is_elite: False']\n", + "Id: 58_31 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_25', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_31', 'origin': '57_25~CUW~57_76#MGNP'} Metrics: ['ELUC: -7.949371685729034', 'NSGA-II_crowding_distance: 0.07488479775679172', 'NSGA-II_rank: 1', 'change: 0.10972032483317974', 'is_elite: False']\n", + "Id: 58_73 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_79', '57_25'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_73', 'origin': '57_79~CUW~57_25#MGNP'} Metrics: ['ELUC: -8.397323155317178', 'NSGA-II_crowding_distance: 0.11826653353108896', 'NSGA-II_rank: 1', 'change: 0.11516634904935451', 'is_elite: False']\n", + "Id: 58_60 Identity: {'ancestor_count': 52, 'ancestor_ids': ['57_39', '56_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_60', 'origin': '57_39~CUW~56_84#MGNP'} Metrics: ['ELUC: -8.452586597368217', 'NSGA-II_crowding_distance: 0.3416677392624481', 'NSGA-II_rank: 3', 'change: 0.1212738076923716', 'is_elite: False']\n", + "Id: 58_87 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '56_80'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_87', 'origin': '1_1~CUW~56_80#MGNP'} Metrics: ['ELUC: -8.542402150476228', 'NSGA-II_crowding_distance: 0.9172865630927028', 'NSGA-II_rank: 4', 'change: 0.1489838722048497', 'is_elite: False']\n", + "Id: 58_14 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_84', '56_80'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_14', 'origin': '56_84~CUW~56_80#MGNP'} Metrics: ['ELUC: -8.970227691437238', 'NSGA-II_crowding_distance: 0.4583950026292074', 'NSGA-II_rank: 3', 'change: 0.12546608206724247', 'is_elite: False']\n", + "Id: 58_12 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '56_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_12', 'origin': '57_76~CUW~56_84#MGNP'} Metrics: ['ELUC: -9.207563073499166', 'NSGA-II_crowding_distance: 0.31629323773743756', 'NSGA-II_rank: 2', 'change: 0.11663126359206123', 'is_elite: False']\n", + "Id: 58_32 Identity: {'ancestor_count': 56, 'ancestor_ids': ['2_49', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_32', 'origin': '2_49~CUW~57_87#MGNP'} Metrics: ['ELUC: -9.62723074077338', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2959611020129381', 'is_elite: False']\n", + "Id: 58_28 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_73', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_28', 'origin': '57_73~CUW~57_76#MGNP'} Metrics: ['ELUC: -9.630577825157138', 'NSGA-II_crowding_distance: 0.731680145729932', 'NSGA-II_rank: 6', 'change: 0.27691818432690696', 'is_elite: False']\n", + "Id: 58_96 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_84', '56_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_96', 'origin': '56_84~CUW~56_84#MGNP'} Metrics: ['ELUC: -9.682574872224208', 'NSGA-II_crowding_distance: 0.15362658176125432', 'NSGA-II_rank: 1', 'change: 0.11559543060267435', 'is_elite: False']\n", + "Id: 58_56 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_90', '56_80'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_56', 'origin': '56_90~CUW~56_80#MGNP'} Metrics: ['ELUC: -9.964201753844302', 'NSGA-II_crowding_distance: 0.2864813030836299', 'NSGA-II_rank: 2', 'change: 0.15728346036707172', 'is_elite: False']\n", + "Id: 58_100 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '56_80'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_100', 'origin': '2_49~CUW~56_80#MGNP'} Metrics: ['ELUC: -10.657651745362395', 'NSGA-II_crowding_distance: 0.909804596273378', 'NSGA-II_rank: 4', 'change: 0.2669881342150363', 'is_elite: False']\n", + "Id: 56_84 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '52_33'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_84', 'origin': '55_84~CUW~52_33#MGNP'} Metrics: ['ELUC: -10.771223220008585', 'NSGA-II_crowding_distance: 0.23663541707654667', 'NSGA-II_rank: 1', 'change: 0.12071928172471472', 'is_elite: True']\n", + "Id: 57_87 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_84'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_87', 'origin': '56_80~CUW~56_84#MGNP'} Metrics: ['ELUC: -11.188067523511563', 'NSGA-II_crowding_distance: 0.24397765776928376', 'NSGA-II_rank: 2', 'change: 0.1616196193367384', 'is_elite: False']\n", + "Id: 58_58 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_87', '57_25'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_58', 'origin': '57_87~CUW~57_25#MGNP'} Metrics: ['ELUC: -11.387125559021607', 'NSGA-II_crowding_distance: 0.7118233642935585', 'NSGA-II_rank: 3', 'change: 0.17909714388427325', 'is_elite: False']\n", + "Id: 58_57 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_87', '1_1'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_57', 'origin': '57_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.417450918470212', 'NSGA-II_crowding_distance: 0.23487180171056768', 'NSGA-II_rank: 1', 'change: 0.15676078435182736', 'is_elite: True']\n", + "Id: 58_51 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_90', '57_73'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_51', 'origin': '56_90~CUW~57_73#MGNP'} Metrics: ['ELUC: -11.547416150231093', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29139992190928865', 'is_elite: False']\n", + "Id: 58_92 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_60', '1_1'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_92', 'origin': '57_60~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.274172503992675', 'NSGA-II_crowding_distance: 0.16787642368559896', 'NSGA-II_rank: 1', 'change: 0.165294280579888', 'is_elite: False']\n", + "Id: 58_25 Identity: {'ancestor_count': 56, 'ancestor_ids': ['2_49', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_25', 'origin': '2_49~CUW~57_76#MGNP'} Metrics: ['ELUC: -12.515333644496947', 'NSGA-II_crowding_distance: 1.116277483213223', 'NSGA-II_rank: 5', 'change: 0.26753614096895434', 'is_elite: False']\n", + "Id: 58_49 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '56_80'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_49', 'origin': '2_49~CUW~56_80#MGNP'} Metrics: ['ELUC: -12.561090706468043', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2863305275767397', 'is_elite: False']\n", + "Id: 58_48 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_87', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_48', 'origin': '57_87~CUW~57_76#MGNP'} Metrics: ['ELUC: -12.755702958992554', 'NSGA-II_crowding_distance: 0.2550409828535335', 'NSGA-II_rank: 2', 'change: 0.17835659958274758', 'is_elite: False']\n", + "Id: 58_88 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_25', '57_31'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_88', 'origin': '57_25~CUW~57_31#MGNP'} Metrics: ['ELUC: -13.04618109709288', 'NSGA-II_crowding_distance: 0.17802123467199077', 'NSGA-II_rank: 2', 'change: 0.20018880246875093', 'is_elite: False']\n", + "Id: 58_68 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_22', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_68', 'origin': '56_22~CUW~57_87#MGNP'} Metrics: ['ELUC: -13.279738335616294', 'NSGA-II_crowding_distance: 0.2087070956067718', 'NSGA-II_rank: 1', 'change: 0.1752477765821551', 'is_elite: True']\n", + "Id: 58_52 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '57_68'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_52', 'origin': '1_1~CUW~57_68#MGNP'} Metrics: ['ELUC: -13.348188940670552', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.26733000290936787', 'is_elite: False']\n", + "Id: 58_98 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_98', 'origin': '57_76~CUW~56_22#MGNP'} Metrics: ['ELUC: -13.48713000732383', 'NSGA-II_crowding_distance: 0.7011205153342305', 'NSGA-II_rank: 3', 'change: 0.21587982451087445', 'is_elite: False']\n", + "Id: 58_63 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_80', '57_79'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_63', 'origin': '56_80~CUW~57_79#MGNP'} Metrics: ['ELUC: -13.82205524968963', 'NSGA-II_crowding_distance: 0.17059268845694486', 'NSGA-II_rank: 2', 'change: 0.20887719096495538', 'is_elite: False']\n", + "Id: 58_35 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_35', 'origin': '57_76~CUW~55_84#MGNP'} Metrics: ['ELUC: -13.871140571539271', 'NSGA-II_crowding_distance: 0.1748684057704895', 'NSGA-II_rank: 2', 'change: 0.23250830595170116', 'is_elite: False']\n", + "Id: 58_11 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_80'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_11', 'origin': '56_80~CUW~56_80#MGNP'} Metrics: ['ELUC: -14.018294323535153', 'NSGA-II_crowding_distance: 0.1575380338505816', 'NSGA-II_rank: 1', 'change: 0.19796954198053016', 'is_elite: False']\n", + "Id: 56_80 Identity: {'ancestor_count': 54, 'ancestor_ids': ['55_35', '55_13'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_80', 'origin': '55_35~CUW~55_13#MGNP'} Metrics: ['ELUC: -14.363282535253985', 'NSGA-II_crowding_distance: 0.16991639452066187', 'NSGA-II_rank: 1', 'change: 0.20386553606794738', 'is_elite: False']\n", + "Id: 58_18 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_79', '2_49'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_18', 'origin': '57_79~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.431473635710084', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.28998557025650024', 'is_elite: False']\n", + "Id: 58_70 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '56_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_70', 'origin': '57_76~CUW~56_84#MGNP'} Metrics: ['ELUC: -15.013784620605927', 'NSGA-II_crowding_distance: 0.2866780483416078', 'NSGA-II_rank: 2', 'change: 0.23660608162333202', 'is_elite: False']\n", + "Id: 58_13 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_13', 'origin': '57_76~CUW~57_87#MGNP'} Metrics: ['ELUC: -15.069680338591505', 'NSGA-II_crowding_distance: 0.14592788469234932', 'NSGA-II_rank: 1', 'change: 0.2308264627332065', 'is_elite: False']\n", + "Id: 58_89 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_84', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_89', 'origin': '56_84~CUW~57_76#MGNP'} Metrics: ['ELUC: -15.194317675537576', 'NSGA-II_crowding_distance: 0.02871334044197856', 'NSGA-II_rank: 1', 'change: 0.23330424233678948', 'is_elite: False']\n", + "Id: 58_91 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_76', '56_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_91', 'origin': '57_76~CUW~56_84#MGNP'} Metrics: ['ELUC: -15.292611748167527', 'NSGA-II_crowding_distance: 0.06865696356707651', 'NSGA-II_rank: 1', 'change: 0.23561066890549578', 'is_elite: False']\n", + "Id: 58_94 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '56_80'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_94', 'origin': '2_49~CUW~56_80#MGNP'} Metrics: ['ELUC: -15.56728736205509', 'NSGA-II_crowding_distance: 0.31679934725915004', 'NSGA-II_rank: 2', 'change: 0.2819860862426105', 'is_elite: False']\n", + "Id: 57_76 Identity: {'ancestor_count': 55, 'ancestor_ids': ['55_37', '56_77'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_76', 'origin': '55_37~CUW~56_77#MGNP'} Metrics: ['ELUC: -15.572389082606916', 'NSGA-II_crowding_distance: 0.08504757777847681', 'NSGA-II_rank: 1', 'change: 0.24737396191429387', 'is_elite: False']\n", + "Id: 58_69 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_60', '57_79'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_69', 'origin': '57_60~CUW~57_79#MGNP'} Metrics: ['ELUC: -15.846050005124852', 'NSGA-II_crowding_distance: 0.17327771874692033', 'NSGA-II_rank: 1', 'change: 0.25159495300354157', 'is_elite: False']\n", + "Id: 58_33 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_84', '57_68'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_33', 'origin': '56_84~CUW~57_68#MGNP'} Metrics: ['ELUC: -16.431944359863493', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.29840136486686103', 'is_elite: False']\n", + "Id: 58_24 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_80', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_24', 'origin': '56_80~CUW~57_76#MGNP'} Metrics: ['ELUC: -16.76960734662505', 'NSGA-II_crowding_distance: 0.24739240398400192', 'NSGA-II_rank: 1', 'change: 0.2787590087011766', 'is_elite: True']\n", + "Id: 58_76 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_68', '57_79'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_76', 'origin': '57_68~CUW~57_79#MGNP'} Metrics: ['ELUC: -17.272925675460126', 'NSGA-II_crowding_distance: 0.1261826985063671', 'NSGA-II_rank: 1', 'change: 0.3011968132146943', 'is_elite: False']\n", + "Id: 58_50 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_68', '57_79'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_50', 'origin': '57_68~CUW~57_79#MGNP'} Metrics: ['ELUC: -17.572139622122716', 'NSGA-II_crowding_distance: 0.023271640071640304', 'NSGA-II_rank: 1', 'change: 0.3027898938450637', 'is_elite: False']\n", + "Id: 58_71 Identity: {'ancestor_count': 51, 'ancestor_ids': ['2_49', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_71', 'origin': '2_49~CUW~55_84#MGNP'} Metrics: ['ELUC: -17.5752848013556', 'NSGA-II_crowding_distance: 0.002208681458823507', 'NSGA-II_rank: 1', 'change: 0.30300942444517176', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 57_68 Identity: {'ancestor_count': 3, 'ancestor_ids': ['56_100', '56_100'], 'birth_generation': 57, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '57_68', 'origin': '56_100~CUW~56_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 58_16 Identity: {'ancestor_count': 4, 'ancestor_ids': ['57_68', '57_68'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_16', 'origin': '57_68~CUW~57_68#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 58_45 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_45', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 58_64 Identity: {'ancestor_count': 53, 'ancestor_ids': ['57_25', '2_49'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_64', 'origin': '57_25~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 58_74 Identity: {'ancestor_count': 4, 'ancestor_ids': ['57_68', '57_68'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_74', 'origin': '57_68~CUW~57_68#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 58_77 Identity: {'ancestor_count': 4, 'ancestor_ids': ['57_39', '57_73'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_77', 'origin': '57_39~CUW~57_73#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 58.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 59...:\n", + "PopulationResponse:\n", + " Generation: 59\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/59/20240220-024613\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 59 and asking ESP for generation 60...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 59 data persisted.\n", + "Evaluated candidates:\n", + "Id: 59_89 Identity: {'ancestor_count': 53, 'ancestor_ids': ['2_49', '58_96'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_89', 'origin': '2_49~CUW~58_96#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 59_100 Identity: {'ancestor_count': 5, 'ancestor_ids': ['1_1', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_100', 'origin': '1_1~CUW~58_77#MGNP'} Metrics: ['ELUC: 22.747414613876707', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3041432951711245', 'is_elite: False']\n", + "Id: 59_24 Identity: {'ancestor_count': 52, 'ancestor_ids': ['2_49', '58_79'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_24', 'origin': '2_49~CUW~58_79#MGNP'} Metrics: ['ELUC: 8.171404554781152', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2724335630092303', 'is_elite: False']\n", + "Id: 59_65 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_77', '58_79'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_65', 'origin': '58_77~CUW~58_79#MGNP'} Metrics: ['ELUC: 6.220564577015342', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.24189731950905846', 'is_elite: False']\n", + "Id: 59_76 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_11', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_76', 'origin': '58_11~CUW~2_49#MGNP'} Metrics: ['ELUC: 5.619937572126056', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24072073070008312', 'is_elite: False']\n", + "Id: 59_68 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_77', '58_79'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_68', 'origin': '58_77~CUW~58_79#MGNP'} Metrics: ['ELUC: 4.569983366331422', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2632741801864773', 'is_elite: False']\n", + "Id: 59_96 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_24', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_96', 'origin': '58_24~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.3507990983082157', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.09204853570552643', 'is_elite: False']\n", + "Id: 59_21 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_21', 'origin': '55_84~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.0116418866305046', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3233906127740207', 'is_elite: False']\n", + "Id: 59_99 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_24', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_99', 'origin': '58_24~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.8885340934854979', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.11724209238517172', 'is_elite: False']\n", + "Id: 59_34 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_11', '58_27'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_34', 'origin': '58_11~CUW~58_27#MGNP'} Metrics: ['ELUC: 0.7292012495004649', 'NSGA-II_crowding_distance: 0.4230821911228376', 'NSGA-II_rank: 6', 'change: 0.10880140217844499', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 59_20 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_11', '58_79'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_20', 'origin': '58_11~CUW~58_79#MGNP'} Metrics: ['ELUC: -0.09352528362734773', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07248343850054177', 'is_elite: False']\n", + "Id: 59_38 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_38', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.21061610719476098', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.05135888838528398', 'is_elite: False']\n", + "Id: 59_66 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_79', '58_24'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_66', 'origin': '58_79~CUW~58_24#MGNP'} Metrics: ['ELUC: -0.21820877282505693', 'NSGA-II_crowding_distance: 0.35150822839310936', 'NSGA-II_rank: 6', 'change: 0.13018122960839806', 'is_elite: False']\n", + "Id: 59_88 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_24', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_88', 'origin': '58_24~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8793453142326397', 'NSGA-II_crowding_distance: 0.28516658873669587', 'NSGA-II_rank: 5', 'change: 0.08311434329356264', 'is_elite: False']\n", + "Id: 59_98 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '58_79'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_98', 'origin': '58_79~CUW~58_79#MGNP'} Metrics: ['ELUC: -1.1848975062708507', 'NSGA-II_crowding_distance: 0.28836996243839985', 'NSGA-II_rank: 1', 'change: 0.05028526523146936', 'is_elite: True']\n", + "Id: 59_40 Identity: {'ancestor_count': 57, 'ancestor_ids': ['1_1', '58_57'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_40', 'origin': '1_1~CUW~58_57#MGNP'} Metrics: ['ELUC: -1.2813715612861236', 'NSGA-II_crowding_distance: 0.6008304044820633', 'NSGA-II_rank: 6', 'change: 0.14238186291826394', 'is_elite: False']\n", + "Id: 59_74 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_74', 'origin': '58_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4520996283159486', 'NSGA-II_crowding_distance: 1.2295983035067732', 'NSGA-II_rank: 7', 'change: 0.14811811927668372', 'is_elite: False']\n", + "Id: 59_83 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_65', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_83', 'origin': '58_65~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4833298454134585', 'NSGA-II_crowding_distance: 0.13505028533101773', 'NSGA-II_rank: 2', 'change: 0.06154479370448518', 'is_elite: False']\n", + "Id: 59_79 Identity: {'ancestor_count': 56, 'ancestor_ids': ['1_1', '58_27'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_79', 'origin': '1_1~CUW~58_27#MGNP'} Metrics: ['ELUC: -1.7300424646626098', 'NSGA-II_crowding_distance: 0.1237319307351466', 'NSGA-II_rank: 2', 'change: 0.0633529275115545', 'is_elite: False']\n", + "Id: 58_79 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '55_84'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_79', 'origin': '1_1~CUW~55_84#MGNP'} Metrics: ['ELUC: -1.970898184381996', 'NSGA-II_crowding_distance: 0.13622289440755192', 'NSGA-II_rank: 1', 'change: 0.05749453171041659', 'is_elite: False']\n", + "Id: 59_53 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_68', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_53', 'origin': '58_68~CUW~56_84#MGNP'} Metrics: ['ELUC: -2.674404519213993', 'NSGA-II_crowding_distance: 0.20508761896007632', 'NSGA-II_rank: 5', 'change: 0.10079450022026507', 'is_elite: False']\n", + "Id: 59_11 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_11', 'origin': '56_80~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.6751341487658773', 'NSGA-II_crowding_distance: 0.43894874321533833', 'NSGA-II_rank: 5', 'change: 0.10438030204743572', 'is_elite: False']\n", + "Id: 59_14 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '58_79'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_14', 'origin': '58_79~CUW~58_79#MGNP'} Metrics: ['ELUC: -2.895794059792959', 'NSGA-II_crowding_distance: 0.12810020521480953', 'NSGA-II_rank: 1', 'change: 0.06189669935347563', 'is_elite: False']\n", + "Id: 59_16 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_27', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_16', 'origin': '58_27~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.043070398550322', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06999356656554061', 'is_elite: False']\n", + "Id: 59_41 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_65', '58_27'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_41', 'origin': '58_65~CUW~58_27#MGNP'} Metrics: ['ELUC: -3.092635560267702', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06899760028541903', 'is_elite: False']\n", + "Id: 59_61 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_79', '58_27'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_61', 'origin': '58_79~CUW~58_27#MGNP'} Metrics: ['ELUC: -3.1204150419981502', 'NSGA-II_crowding_distance: 0.14204799312851135', 'NSGA-II_rank: 2', 'change: 0.06898738364494111', 'is_elite: False']\n", + "Id: 59_77 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_77', 'origin': '58_79~CUW~56_84#MGNP'} Metrics: ['ELUC: -3.295137639701637', 'NSGA-II_crowding_distance: 0.33802344155894054', 'NSGA-II_rank: 4', 'change: 0.11384142370091441', 'is_elite: False']\n", + "Id: 59_58 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_58', 'origin': '58_79~CUW~56_84#MGNP'} Metrics: ['ELUC: -3.4299643833083397', 'NSGA-II_crowding_distance: 0.24690840605610398', 'NSGA-II_rank: 3', 'change: 0.07456938387001946', 'is_elite: False']\n", + "Id: 59_84 Identity: {'ancestor_count': 53, 'ancestor_ids': ['58_96', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_84', 'origin': '58_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.647892651710984', 'NSGA-II_crowding_distance: 0.6293235798882397', 'NSGA-II_rank: 3', 'change: 0.11338450091822994', 'is_elite: False']\n", + "Id: 59_86 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '55_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_86', 'origin': '55_84~CUW~55_84#MGNP'} Metrics: ['ELUC: -3.7668883848693073', 'NSGA-II_crowding_distance: 0.29609922955054013', 'NSGA-II_rank: 2', 'change: 0.06961863058182419', 'is_elite: False']\n", + "Id: 58_65 Identity: {'ancestor_count': 54, 'ancestor_ids': ['57_39', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_65', 'origin': '57_39~CUW~56_22#MGNP'} Metrics: ['ELUC: -3.8923608700709917', 'NSGA-II_crowding_distance: 0.21523349400324654', 'NSGA-II_rank: 1', 'change: 0.0631089642439499', 'is_elite: True']\n", + "Id: 59_82 Identity: {'ancestor_count': 57, 'ancestor_ids': ['1_1', '58_24'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_82', 'origin': '1_1~CUW~58_24#MGNP'} Metrics: ['ELUC: -3.909822314041114', 'NSGA-II_crowding_distance: 0.42729597624586346', 'NSGA-II_rank: 4', 'change: 0.12933016466371985', 'is_elite: False']\n", + "Id: 59_49 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_65', '58_92'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_49', 'origin': '58_65~CUW~58_92#MGNP'} Metrics: ['ELUC: -4.784161762807185', 'NSGA-II_crowding_distance: 0.6034820766225187', 'NSGA-II_rank: 2', 'change: 0.11942230322755622', 'is_elite: False']\n", + "Id: 59_56 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_24', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_56', 'origin': '58_24~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.5298672092607415', 'NSGA-II_crowding_distance: 0.8459358474457226', 'NSGA-II_rank: 7', 'change: 0.16148066593792812', 'is_elite: False']\n", + "Id: 55_84 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_84', 'origin': '1_1~CUW~52_33#MGNP'} Metrics: ['ELUC: -5.592011266999677', 'NSGA-II_crowding_distance: 0.22545359047794133', 'NSGA-II_rank: 1', 'change: 0.08036194045690388', 'is_elite: True']\n", + "Id: 59_93 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '58_65'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_93', 'origin': '58_69~CUW~58_65#MGNP'} Metrics: ['ELUC: -5.809385491264231', 'NSGA-II_crowding_distance: 0.7704016964932269', 'NSGA-II_rank: 7', 'change: 0.17978042086961404', 'is_elite: False']\n", + "Id: 59_67 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_67', 'origin': '58_79~CUW~56_84#MGNP'} Metrics: ['ELUC: -5.9431176582783705', 'NSGA-II_crowding_distance: 0.42982487632000743', 'NSGA-II_rank: 1', 'change: 0.09557731659472814', 'is_elite: True']\n", + "Id: 59_23 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_23', 'origin': '58_79~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 59_44 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_27', '56_80'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_44', 'origin': '58_27~CUW~56_80#MGNP'} Metrics: ['ELUC: -6.524372172281972', 'NSGA-II_crowding_distance: 0.9147442280928721', 'NSGA-II_rank: 6', 'change: 0.14357942634740828', 'is_elite: False']\n", + "Id: 59_26 Identity: {'ancestor_count': 57, 'ancestor_ids': ['56_80', '58_92'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_26', 'origin': '56_80~CUW~58_92#MGNP'} Metrics: ['ELUC: -6.906467668843794', 'NSGA-II_crowding_distance: 0.6378972587971447', 'NSGA-II_rank: 5', 'change: 0.1404823336972592', 'is_elite: False']\n", + "Id: 59_92 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_27', '58_92'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_92', 'origin': '58_27~CUW~58_92#MGNP'} Metrics: ['ELUC: -7.817605961318005', 'NSGA-II_crowding_distance: 0.5544533330053993', 'NSGA-II_rank: 4', 'change: 0.12987104681386577', 'is_elite: False']\n", + "Id: 59_69 Identity: {'ancestor_count': 57, 'ancestor_ids': ['1_1', '58_69'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_69', 'origin': '1_1~CUW~58_69#MGNP'} Metrics: ['ELUC: -8.421129833817334', 'NSGA-II_crowding_distance: 0.5764524520151367', 'NSGA-II_rank: 3', 'change: 0.12893381013114757', 'is_elite: False']\n", + "Id: 59_91 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_65', '58_24'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_91', 'origin': '58_65~CUW~58_24#MGNP'} Metrics: ['ELUC: -9.349875396737005', 'NSGA-II_crowding_distance: 0.9760874043950992', 'NSGA-II_rank: 6', 'change: 0.18627808943469135', 'is_elite: False']\n", + "Id: 59_85 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_77', '58_79'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_85', 'origin': '58_77~CUW~58_79#MGNP'} Metrics: ['ELUC: -9.5992090956472', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2752884079448099', 'is_elite: False']\n", + "Id: 59_13 Identity: {'ancestor_count': 53, 'ancestor_ids': ['1_1', '58_96'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_13', 'origin': '1_1~CUW~58_96#MGNP'} Metrics: ['ELUC: -9.622895171113312', 'NSGA-II_crowding_distance: 0.196454050821067', 'NSGA-II_rank: 3', 'change: 0.14012100040119274', 'is_elite: False']\n", + "Id: 59_37 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_57', '55_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_37', 'origin': '58_57~CUW~55_84#MGNP'} Metrics: ['ELUC: -9.691542932775919', 'NSGA-II_crowding_distance: 1.1350304901475203', 'NSGA-II_rank: 5', 'change: 0.14906394850556678', 'is_elite: False']\n", + "Id: 59_50 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_79', '58_68'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_50', 'origin': '58_79~CUW~58_68#MGNP'} Metrics: ['ELUC: -9.94966070663254', 'NSGA-II_crowding_distance: 0.25132124124860705', 'NSGA-II_rank: 4', 'change: 0.14717754389646354', 'is_elite: False']\n", + "Id: 59_39 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_96', '58_57'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_39', 'origin': '58_96~CUW~58_57#MGNP'} Metrics: ['ELUC: -10.018863617205128', 'NSGA-II_crowding_distance: 0.08723195647962538', 'NSGA-II_rank: 4', 'change: 0.1471938299852829', 'is_elite: False']\n", + "Id: 59_57 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '56_80'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_57', 'origin': '1_1~CUW~56_80#MGNP'} Metrics: ['ELUC: -10.075706140914074', 'NSGA-II_crowding_distance: 0.8832821301651758', 'NSGA-II_rank: 4', 'change: 0.16417056374087116', 'is_elite: False']\n", + "Id: 59_72 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_92', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_72', 'origin': '58_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.248579275383888', 'NSGA-II_crowding_distance: 0.9787707740227665', 'NSGA-II_rank: 3', 'change: 0.14147750806088935', 'is_elite: False']\n", + "Id: 59_46 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_84', '55_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_46', 'origin': '56_84~CUW~55_84#MGNP'} Metrics: ['ELUC: -10.623628360335061', 'NSGA-II_crowding_distance: 0.5316082175953282', 'NSGA-II_rank: 2', 'change: 0.12224403516688384', 'is_elite: False']\n", + "Id: 56_84 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '52_33'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_84', 'origin': '55_84~CUW~52_33#MGNP'} Metrics: ['ELUC: -10.771223220008585', 'NSGA-II_crowding_distance: 0.3697483225277377', 'NSGA-II_rank: 1', 'change: 0.12071928172471472', 'is_elite: True']\n", + "Id: 59_19 Identity: {'ancestor_count': 52, 'ancestor_ids': ['56_84', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_19', 'origin': '56_84~CUW~56_84#MGNP'} Metrics: ['ELUC: -10.886751321315213', 'NSGA-II_crowding_distance: 0.13640384713185452', 'NSGA-II_rank: 1', 'change: 0.12200698923308659', 'is_elite: False']\n", + "Id: 59_81 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_57', '56_80'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_81', 'origin': '58_57~CUW~56_80#MGNP'} Metrics: ['ELUC: -10.93981785760586', 'NSGA-II_crowding_distance: 0.2136360332035551', 'NSGA-II_rank: 2', 'change: 0.1641076531008587', 'is_elite: False']\n", + "Id: 59_90 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_92', '58_57'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_90', 'origin': '58_92~CUW~58_57#MGNP'} Metrics: ['ELUC: -11.192087865114562', 'NSGA-II_crowding_distance: 0.14665951483339415', 'NSGA-II_rank: 1', 'change: 0.15427694713917506', 'is_elite: False']\n", + "Id: 59_55 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_24', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_55', 'origin': '58_24~CUW~56_84#MGNP'} Metrics: ['ELUC: -11.232225583765036', 'NSGA-II_crowding_distance: 0.10026680431575478', 'NSGA-II_rank: 2', 'change: 0.16719889347925973', 'is_elite: False']\n", + "Id: 58_57 Identity: {'ancestor_count': 56, 'ancestor_ids': ['57_87', '1_1'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_57', 'origin': '57_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.417450918470212', 'NSGA-II_crowding_distance: 0.13006391318007954', 'NSGA-II_rank: 1', 'change: 0.15676078435182736', 'is_elite: False']\n", + "Id: 59_87 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_57', '58_57'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_87', 'origin': '58_57~CUW~58_57#MGNP'} Metrics: ['ELUC: -12.145718400395976', 'NSGA-II_crowding_distance: 0.2699939790544348', 'NSGA-II_rank: 2', 'change: 0.17188615363257131', 'is_elite: False']\n", + "Id: 59_48 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_68', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_48', 'origin': '58_68~CUW~56_84#MGNP'} Metrics: ['ELUC: -12.584412725473886', 'NSGA-II_crowding_distance: 0.16787642368559896', 'NSGA-II_rank: 1', 'change: 0.16945693832618594', 'is_elite: False']\n", + "Id: 59_29 Identity: {'ancestor_count': 57, 'ancestor_ids': ['2_49', '58_57'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_29', 'origin': '2_49~CUW~58_57#MGNP'} Metrics: ['ELUC: -13.168979063428871', 'NSGA-II_crowding_distance: 1.0202912689560348', 'NSGA-II_rank: 4', 'change: 0.28700972220521276', 'is_elite: False']\n", + "Id: 58_68 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_22', '57_87'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_68', 'origin': '56_22~CUW~57_87#MGNP'} Metrics: ['ELUC: -13.279738335616294', 'NSGA-II_crowding_distance: 0.07399935101050548', 'NSGA-II_rank: 1', 'change: 0.1752477765821551', 'is_elite: False']\n", + "Id: 59_80 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_68', '58_69'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_80', 'origin': '58_68~CUW~58_69#MGNP'} Metrics: ['ELUC: -13.370809361942948', 'NSGA-II_crowding_distance: 0.05053328466026493', 'NSGA-II_rank: 1', 'change: 0.1781913022827377', 'is_elite: False']\n", + "Id: 59_62 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_96', '58_24'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_62', 'origin': '58_96~CUW~58_24#MGNP'} Metrics: ['ELUC: -13.46003879477161', 'NSGA-II_crowding_distance: 0.12408767286474065', 'NSGA-II_rank: 1', 'change: 0.1872660282041655', 'is_elite: False']\n", + "Id: 59_42 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_57', '58_24'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_42', 'origin': '58_57~CUW~58_24#MGNP'} Metrics: ['ELUC: -13.534459423959614', 'NSGA-II_crowding_distance: 0.4680632421687366', 'NSGA-II_rank: 2', 'change: 0.20182233862320545', 'is_elite: False']\n", + "Id: 59_17 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_24', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_17', 'origin': '58_24~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.623018999373528', 'NSGA-II_crowding_distance: 1.0616325311493777', 'NSGA-II_rank: 5', 'change: 0.3065026463490265', 'is_elite: False']\n", + "Id: 59_60 Identity: {'ancestor_count': 57, 'ancestor_ids': ['2_49', '58_24'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_60', 'origin': '2_49~CUW~58_24#MGNP'} Metrics: ['ELUC: -14.19929533831648', 'NSGA-II_crowding_distance: 0.9999759566630966', 'NSGA-II_rank: 3', 'change: 0.27703768103721393', 'is_elite: False']\n", + "Id: 59_52 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_80'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_52', 'origin': '56_80~CUW~56_80#MGNP'} Metrics: ['ELUC: -14.228735743292848', 'NSGA-II_crowding_distance: 0.21788795542135064', 'NSGA-II_rank: 1', 'change: 0.20065702341712963', 'is_elite: True']\n", + "Id: 59_43 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_43', 'origin': '58_69~CUW~56_84#MGNP'} Metrics: ['ELUC: -14.930627277590144', 'NSGA-II_crowding_distance: 0.21288418280829252', 'NSGA-II_rank: 1', 'change: 0.2273225985906412', 'is_elite: True']\n", + "Id: 59_73 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_77', '58_69'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_73', 'origin': '58_77~CUW~58_69#MGNP'} Metrics: ['ELUC: -15.060446845379948', 'NSGA-II_crowding_distance: 0.16386396152225435', 'NSGA-II_rank: 3', 'change: 0.2791201256366406', 'is_elite: False']\n", + "Id: 59_71 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_24', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_71', 'origin': '58_24~CUW~56_84#MGNP'} Metrics: ['ELUC: -15.441333355330407', 'NSGA-II_crowding_distance: 0.4652944381038294', 'NSGA-II_rank: 2', 'change: 0.24197734227605766', 'is_elite: False']\n", + "Id: 59_36 Identity: {'ancestor_count': 57, 'ancestor_ids': ['55_84', '58_13'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_36', 'origin': '55_84~CUW~58_13#MGNP'} Metrics: ['ELUC: -15.543816055078995', 'NSGA-II_crowding_distance: 0.10941130346830982', 'NSGA-II_rank: 1', 'change: 0.24185960115311655', 'is_elite: False']\n", + "Id: 59_32 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '58_65'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_32', 'origin': '58_69~CUW~58_65#MGNP'} Metrics: ['ELUC: -15.752784246309053', 'NSGA-II_crowding_distance: 0.06280733721596701', 'NSGA-II_rank: 1', 'change: 0.24601623612456597', 'is_elite: False']\n", + "Id: 59_12 Identity: {'ancestor_count': 57, 'ancestor_ids': ['2_49', '58_57'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_12', 'origin': '2_49~CUW~58_57#MGNP'} Metrics: ['ELUC: -15.763023967593766', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.3075092156180777', 'is_elite: False']\n", + "Id: 59_78 Identity: {'ancestor_count': 53, 'ancestor_ids': ['2_49', '58_96'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_78', 'origin': '2_49~CUW~58_96#MGNP'} Metrics: ['ELUC: -15.806685928707852', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28966484165689', 'is_elite: False']\n", + "Id: 59_45 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_92', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_45', 'origin': '58_92~CUW~58_77#MGNP'} Metrics: ['ELUC: -15.856150276396855', 'NSGA-II_crowding_distance: 0.12295807949539599', 'NSGA-II_rank: 3', 'change: 0.2853218184773127', 'is_elite: False']\n", + "Id: 59_75 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '1_1'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_75', 'origin': '58_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.972698446432645', 'NSGA-II_crowding_distance: 0.05678880351828863', 'NSGA-II_rank: 1', 'change: 0.25332164452842615', 'is_elite: False']\n", + "Id: 59_35 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '58_11'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_35', 'origin': '58_69~CUW~58_11#MGNP'} Metrics: ['ELUC: -16.07412461701993', 'NSGA-II_crowding_distance: 0.06549984693324261', 'NSGA-II_rank: 1', 'change: 0.2575075044025867', 'is_elite: False']\n", + "Id: 59_64 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_64', 'origin': '2_49~CUW~58_77#MGNP'} Metrics: ['ELUC: -16.279888542053882', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.28572753537485457', 'is_elite: False']\n", + "Id: 59_33 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_24', '58_57'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_33', 'origin': '58_24~CUW~58_57#MGNP'} Metrics: ['ELUC: -16.391170190959382', 'NSGA-II_crowding_distance: 0.08007666060131143', 'NSGA-II_rank: 1', 'change: 0.2657637446839822', 'is_elite: False']\n", + "Id: 59_54 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_77', '58_24'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_54', 'origin': '58_77~CUW~58_24#MGNP'} Metrics: ['ELUC: -16.396235508467363', 'NSGA-II_crowding_distance: 0.3040795187088667', 'NSGA-II_rank: 2', 'change: 0.277496327331286', 'is_elite: False']\n", + "Id: 59_18 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_18', 'origin': '56_80~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.48477462243398', 'NSGA-II_crowding_distance: 0.06507677428865173', 'NSGA-II_rank: 1', 'change: 0.2744317382264097', 'is_elite: False']\n", + "Id: 58_24 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_80', '57_76'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_24', 'origin': '56_80~CUW~57_76#MGNP'} Metrics: ['ELUC: -16.76960734662505', 'NSGA-II_crowding_distance: 0.08332280568807128', 'NSGA-II_rank: 1', 'change: 0.2787590087011766', 'is_elite: False']\n", + "Id: 59_31 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_31', 'origin': '58_69~CUW~58_77#MGNP'} Metrics: ['ELUC: -16.772099745708605', 'NSGA-II_crowding_distance: 0.07300548371241183', 'NSGA-II_rank: 1', 'change: 0.2944174106564111', 'is_elite: False']\n", + "Id: 59_27 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_92', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_27', 'origin': '58_92~CUW~58_77#MGNP'} Metrics: ['ELUC: -16.810598490893824', 'NSGA-II_crowding_distance: 0.17049519455613268', 'NSGA-II_rank: 2', 'change: 0.29868306924972976', 'is_elite: False']\n", + "Id: 59_95 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_77', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_95', 'origin': '58_77~CUW~56_84#MGNP'} Metrics: ['ELUC: -16.974806634875325', 'NSGA-II_crowding_distance: 0.07560816579785634', 'NSGA-II_rank: 1', 'change: 0.29705992291053696', 'is_elite: False']\n", + "Id: 59_22 Identity: {'ancestor_count': 5, 'ancestor_ids': ['58_77', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_22', 'origin': '58_77~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.595029515614772', 'NSGA-II_crowding_distance: 0.05538589625277879', 'NSGA-II_rank: 1', 'change: 0.30301183055929726', 'is_elite: False']\n", + "Id: 59_30 Identity: {'ancestor_count': 5, 'ancestor_ids': ['58_77', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_30', 'origin': '58_77~CUW~58_77#MGNP'} Metrics: ['ELUC: -17.59716629194258', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302055649427034', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 58_77 Identity: {'ancestor_count': 4, 'ancestor_ids': ['57_39', '57_73'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_77', 'origin': '57_39~CUW~57_73#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_15 Identity: {'ancestor_count': 5, 'ancestor_ids': ['2_49', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_15', 'origin': '2_49~CUW~58_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_25 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_25', 'origin': '58_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_28 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_77', '58_92'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_28', 'origin': '58_77~CUW~58_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_47 Identity: {'ancestor_count': 53, 'ancestor_ids': ['58_96', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_47', 'origin': '58_96~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_51 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_11', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_51', 'origin': '58_11~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_59 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_59', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_63 Identity: {'ancestor_count': 5, 'ancestor_ids': ['58_77', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_63', 'origin': '58_77~CUW~58_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_70 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_92', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_70', 'origin': '58_92~CUW~58_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_94 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_68', '58_77'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_94', 'origin': '58_68~CUW~58_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 59_97 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_77', '58_65'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_97', 'origin': '58_77~CUW~58_65#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 59.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 60...:\n", + "PopulationResponse:\n", + " Generation: 60\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/60/20240220-025330\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 60 and asking ESP for generation 61...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 60 data persisted.\n", + "Evaluated candidates:\n", + "Id: 60_46 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_97', '59_14'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_46', 'origin': '59_97~CUW~59_14#MGNP'} Metrics: ['ELUC: 23.727766624730897', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3032918524458054', 'is_elite: False']\n", + "Id: 60_74 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_67', '59_97'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_74', 'origin': '59_67~CUW~59_97#MGNP'} Metrics: ['ELUC: 22.604566093086397', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2865277635107305', 'is_elite: False']\n", + "Id: 60_32 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_98', '59_97'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_32', 'origin': '59_98~CUW~59_97#MGNP'} Metrics: ['ELUC: 8.47926429873656', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24598458191443245', 'is_elite: False']\n", + "Id: 60_35 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '58_79'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_35', 'origin': '1_1~CUW~58_79#MGNP'} Metrics: ['ELUC: 2.0496770422894097', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06856154193355146', 'is_elite: False']\n", + "Id: 60_73 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '2_49'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_73', 'origin': '58_79~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.8391151956310842', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.28877157076367066', 'is_elite: False']\n", + "Id: 60_14 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_65', '59_52'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_14', 'origin': '58_65~CUW~59_52#MGNP'} Metrics: ['ELUC: 0.7987247447795653', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.11119319557735165', 'is_elite: False']\n", + "Id: 60_44 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_90', '2_49'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_44', 'origin': '59_90~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.7123771784380237', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3024407404838154', 'is_elite: False']\n", + "Id: 60_38 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_38', 'origin': '59_67~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.4026045794416572', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.061012066521860295', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 60_50 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_65', '59_98'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_50', 'origin': '58_65~CUW~59_98#MGNP'} Metrics: ['ELUC: -0.09376729433985263', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05278350837830978', 'is_elite: False']\n", + "Id: 60_84 Identity: {'ancestor_count': 51, 'ancestor_ids': ['1_1', '55_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_84', 'origin': '1_1~CUW~55_84#MGNP'} Metrics: ['ELUC: -0.19959508657039565', 'NSGA-II_crowding_distance: 0.5986781879329006', 'NSGA-II_rank: 5', 'change: 0.09586418374076629', 'is_elite: False']\n", + "Id: 60_80 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_80', 'origin': '58_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.40997449258747337', 'NSGA-II_crowding_distance: 0.16340940685213254', 'NSGA-II_rank: 3', 'change: 0.05613280406326196', 'is_elite: False']\n", + "Id: 60_57 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_57', 'origin': '59_67~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.4169910859547102', 'NSGA-II_crowding_distance: 0.21295673429238335', 'NSGA-II_rank: 1', 'change: 0.04210233883091324', 'is_elite: True']\n", + "Id: 60_11 Identity: {'ancestor_count': 57, 'ancestor_ids': ['59_97', '58_57'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_11', 'origin': '59_97~CUW~58_57#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 60_62 Identity: {'ancestor_count': 51, 'ancestor_ids': ['2_49', '55_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_62', 'origin': '2_49~CUW~55_84#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 60_96 Identity: {'ancestor_count': 52, 'ancestor_ids': ['2_49', '56_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_96', 'origin': '2_49~CUW~56_84#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 60_24 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_65', '56_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_24', 'origin': '58_65~CUW~56_84#MGNP'} Metrics: ['ELUC: -0.8844480892781535', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10349620519670767', 'is_elite: False']\n", + "Id: 59_98 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '58_79'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_98', 'origin': '58_79~CUW~58_79#MGNP'} Metrics: ['ELUC: -1.1848975062708507', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.05028526523146936', 'is_elite: False']\n", + "Id: 60_79 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_98', '58_79'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_79', 'origin': '59_98~CUW~58_79#MGNP'} Metrics: ['ELUC: -1.3513854855516747', 'NSGA-II_crowding_distance: 0.074380219876839', 'NSGA-II_rank: 2', 'change: 0.053316645602368935', 'is_elite: False']\n", + "Id: 60_39 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_36', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_39', 'origin': '59_36~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.3518910505032622', 'NSGA-II_crowding_distance: 0.33802898247314334', 'NSGA-II_rank: 3', 'change: 0.06970593659595992', 'is_elite: False']\n", + "Id: 60_28 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_28', 'origin': '58_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4516464580377302', 'NSGA-II_crowding_distance: 0.19202864402438927', 'NSGA-II_rank: 2', 'change: 0.062314693182867024', 'is_elite: False']\n", + "Id: 60_30 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '58_65'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_30', 'origin': '1_1~CUW~58_65#MGNP'} Metrics: ['ELUC: -1.498145669815188', 'NSGA-II_crowding_distance: 0.13999748859197164', 'NSGA-II_rank: 1', 'change: 0.04301566092205462', 'is_elite: False']\n", + "Id: 60_29 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_90', '59_67'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_29', 'origin': '59_90~CUW~59_67#MGNP'} Metrics: ['ELUC: -1.723166518253107', 'NSGA-II_crowding_distance: 0.23496317102793124', 'NSGA-II_rank: 5', 'change: 0.09995120296031283', 'is_elite: False']\n", + "Id: 60_60 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_60', 'origin': '55_84~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.012870453708362', 'NSGA-II_crowding_distance: 0.3444496843637449', 'NSGA-II_rank: 4', 'change: 0.08937219165251964', 'is_elite: False']\n", + "Id: 60_63 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_62', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_63', 'origin': '59_62~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0743181288453245', 'NSGA-II_crowding_distance: 0.3257026056792889', 'NSGA-II_rank: 5', 'change: 0.10473420763737254', 'is_elite: False']\n", + "Id: 60_56 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_84', '58_65'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_56', 'origin': '56_84~CUW~58_65#MGNP'} Metrics: ['ELUC: -2.102963130341836', 'NSGA-II_crowding_distance: 0.23006154473811363', 'NSGA-II_rank: 4', 'change: 0.09690074536715593', 'is_elite: False']\n", + "Id: 60_100 Identity: {'ancestor_count': 53, 'ancestor_ids': ['1_1', '59_14'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_100', 'origin': '1_1~CUW~59_14#MGNP'} Metrics: ['ELUC: -2.491890822134257', 'NSGA-II_crowding_distance: 0.20351343336082606', 'NSGA-II_rank: 1', 'change: 0.04866278155458055', 'is_elite: True']\n", + "Id: 60_72 Identity: {'ancestor_count': 53, 'ancestor_ids': ['55_84', '59_98'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_72', 'origin': '55_84~CUW~59_98#MGNP'} Metrics: ['ELUC: -3.3829396544585073', 'NSGA-II_crowding_distance: 0.2500477176618797', 'NSGA-II_rank: 2', 'change: 0.06402882965054214', 'is_elite: False']\n", + "Id: 60_70 Identity: {'ancestor_count': 57, 'ancestor_ids': ['59_67', '58_57'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_70', 'origin': '59_67~CUW~58_57#MGNP'} Metrics: ['ELUC: -3.5212980948086714', 'NSGA-II_crowding_distance: 0.2856861376042327', 'NSGA-II_rank: 3', 'change: 0.08230074486628947', 'is_elite: False']\n", + "Id: 60_58 Identity: {'ancestor_count': 53, 'ancestor_ids': ['56_84', '59_98'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_58', 'origin': '56_84~CUW~59_98#MGNP'} Metrics: ['ELUC: -3.5894247216127275', 'NSGA-II_crowding_distance: 0.37766452174747167', 'NSGA-II_rank: 6', 'change: 0.1131579110505347', 'is_elite: False']\n", + "Id: 60_54 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_52', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_54', 'origin': '59_52~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.765913408523132', 'NSGA-II_crowding_distance: 0.6647396605089988', 'NSGA-II_rank: 6', 'change: 0.11581126520386806', 'is_elite: False']\n", + "Id: 60_48 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_98', '59_67'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_48', 'origin': '59_98~CUW~59_67#MGNP'} Metrics: ['ELUC: -3.8120091387432793', 'NSGA-II_crowding_distance: 0.15821300256553217', 'NSGA-II_rank: 2', 'change: 0.08058112232815651', 'is_elite: False']\n", + "Id: 58_65 Identity: {'ancestor_count': 54, 'ancestor_ids': ['57_39', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_65', 'origin': '57_39~CUW~56_22#MGNP'} Metrics: ['ELUC: -3.8923608700709917', 'NSGA-II_crowding_distance: 0.22207924471676793', 'NSGA-II_rank: 1', 'change: 0.0631089642439499', 'is_elite: True']\n", + "Id: 60_67 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_57', '58_79'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_67', 'origin': '58_57~CUW~58_79#MGNP'} Metrics: ['ELUC: -4.0434652425158575', 'NSGA-II_crowding_distance: 0.19319837443895016', 'NSGA-II_rank: 3', 'change: 0.09074431051456747', 'is_elite: False']\n", + "Id: 60_89 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '59_14'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_89', 'origin': '59_67~CUW~59_14#MGNP'} Metrics: ['ELUC: -4.386983669160364', 'NSGA-II_crowding_distance: 0.21883706524532248', 'NSGA-II_rank: 2', 'change: 0.08300134202947371', 'is_elite: False']\n", + "Id: 60_85 Identity: {'ancestor_count': 58, 'ancestor_ids': ['1_1', '59_48'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_85', 'origin': '1_1~CUW~59_48#MGNP'} Metrics: ['ELUC: -4.460089013617567', 'NSGA-II_crowding_distance: 0.6519865483773715', 'NSGA-II_rank: 5', 'change: 0.11103667716552064', 'is_elite: False']\n", + "Id: 60_34 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_67', '59_52'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_34', 'origin': '59_67~CUW~59_52#MGNP'} Metrics: ['ELUC: -4.4744393042179285', 'NSGA-II_crowding_distance: 0.28945765154184816', 'NSGA-II_rank: 4', 'change: 0.099731421421772', 'is_elite: False']\n", + "Id: 60_81 Identity: {'ancestor_count': 52, 'ancestor_ids': ['1_1', '56_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_81', 'origin': '1_1~CUW~56_84#MGNP'} Metrics: ['ELUC: -4.703528708800846', 'NSGA-II_crowding_distance: 0.1544906506282584', 'NSGA-II_rank: 1', 'change: 0.07739410251040314', 'is_elite: False']\n", + "Id: 60_42 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_97', '59_43'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_42', 'origin': '59_97~CUW~59_43#MGNP'} Metrics: ['ELUC: -4.804259247228523', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.21600988490173373', 'is_elite: False']\n", + "Id: 60_20 Identity: {'ancestor_count': 57, 'ancestor_ids': ['1_1', '58_57'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_20', 'origin': '1_1~CUW~58_57#MGNP'} Metrics: ['ELUC: -4.866539533251944', 'NSGA-II_crowding_distance: 0.8555274134125278', 'NSGA-II_rank: 5', 'change: 0.15044561734279582', 'is_elite: False']\n", + "Id: 60_47 Identity: {'ancestor_count': 55, 'ancestor_ids': ['59_19', '58_65'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_47', 'origin': '59_19~CUW~58_65#MGNP'} Metrics: ['ELUC: -5.332370223576526', 'NSGA-II_crowding_distance: 0.16358154119023666', 'NSGA-II_rank: 4', 'change: 0.1076490545605198', 'is_elite: False']\n", + "Id: 60_91 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_43', '59_67'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_91', 'origin': '59_43~CUW~59_67#MGNP'} Metrics: ['ELUC: -5.376754080181927', 'NSGA-II_crowding_distance: 0.16686082129354493', 'NSGA-II_rank: 3', 'change: 0.09591585342080648', 'is_elite: False']\n", + "Id: 60_40 Identity: {'ancestor_count': 58, 'ancestor_ids': ['58_65', '59_62'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_40', 'origin': '58_65~CUW~59_62#MGNP'} Metrics: ['ELUC: -5.475318351262904', 'NSGA-II_crowding_distance: 0.5133412376230184', 'NSGA-II_rank: 4', 'change: 0.12004007076369175', 'is_elite: False']\n", + "Id: 55_84 Identity: {'ancestor_count': 50, 'ancestor_ids': ['1_1', '52_33'], 'birth_generation': 55, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '55_84', 'origin': '1_1~CUW~52_33#MGNP'} Metrics: ['ELUC: -5.592011266999677', 'NSGA-II_crowding_distance: 0.08295431541895457', 'NSGA-II_rank: 1', 'change: 0.08036194045690388', 'is_elite: False']\n", + "Id: 60_66 Identity: {'ancestor_count': 55, 'ancestor_ids': ['59_14', '58_65'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_66', 'origin': '59_14~CUW~58_65#MGNP'} Metrics: ['ELUC: -5.925871200815017', 'NSGA-II_crowding_distance: 0.42712786619247123', 'NSGA-II_rank: 3', 'change: 0.097641312993578', 'is_elite: False']\n", + "Id: 59_67 Identity: {'ancestor_count': 52, 'ancestor_ids': ['58_79', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_67', 'origin': '58_79~CUW~56_84#MGNP'} Metrics: ['ELUC: -5.9431176582783705', 'NSGA-II_crowding_distance: 0.28454650227817746', 'NSGA-II_rank: 2', 'change: 0.09557731659472814', 'is_elite: False']\n", + "Id: 60_52 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '59_14'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_52', 'origin': '59_67~CUW~59_14#MGNP'} Metrics: ['ELUC: -5.955742226797737', 'NSGA-II_crowding_distance: 0.1792293720541928', 'NSGA-II_rank: 1', 'change: 0.08089537225012855', 'is_elite: False']\n", + "Id: 60_59 Identity: {'ancestor_count': 57, 'ancestor_ids': ['1_1', '58_57'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_59', 'origin': '1_1~CUW~58_57#MGNP'} Metrics: ['ELUC: -6.10557000137382', 'NSGA-II_crowding_distance: 0.12122121590815155', 'NSGA-II_rank: 2', 'change: 0.1184443564293069', 'is_elite: False']\n", + "Id: 60_13 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_98', '59_90'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_13', 'origin': '59_98~CUW~59_90#MGNP'} Metrics: ['ELUC: -6.123711437725532', 'NSGA-II_crowding_distance: 0.22332987312358404', 'NSGA-II_rank: 2', 'change: 0.11903245666890366', 'is_elite: False']\n", + "Id: 60_25 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_90', '59_97'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_25', 'origin': '59_90~CUW~59_97#MGNP'} Metrics: ['ELUC: -6.6557919370288605', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2408137784931736', 'is_elite: False']\n", + "Id: 60_41 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '56_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_41', 'origin': '59_67~CUW~56_84#MGNP'} Metrics: ['ELUC: -7.219014948557207', 'NSGA-II_crowding_distance: 0.32250332440003426', 'NSGA-II_rank: 1', 'change: 0.1062292369726629', 'is_elite: True']\n", + "Id: 60_69 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_67', '59_97'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_69', 'origin': '59_67~CUW~59_97#MGNP'} Metrics: ['ELUC: -7.360675511741216', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1742997953788201', 'is_elite: False']\n", + "Id: 60_92 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_48', '59_14'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_92', 'origin': '59_48~CUW~59_14#MGNP'} Metrics: ['ELUC: -7.373006894894765', 'NSGA-II_crowding_distance: 1.6223354782525283', 'NSGA-II_rank: 6', 'change: 0.1600972380712405', 'is_elite: False']\n", + "Id: 60_51 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_36', '59_52'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_51', 'origin': '59_36~CUW~59_52#MGNP'} Metrics: ['ELUC: -8.3889638874659', 'NSGA-II_crowding_distance: 0.5626178686606719', 'NSGA-II_rank: 3', 'change: 0.14494885759583823', 'is_elite: False']\n", + "Id: 60_76 Identity: {'ancestor_count': 53, 'ancestor_ids': ['1_1', '59_19'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_76', 'origin': '1_1~CUW~59_19#MGNP'} Metrics: ['ELUC: -8.8715447597672', 'NSGA-II_crowding_distance: 0.2682658259509488', 'NSGA-II_rank: 2', 'change: 0.12479318810247238', 'is_elite: False']\n", + "Id: 60_86 Identity: {'ancestor_count': 57, 'ancestor_ids': ['59_19', '58_57'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_86', 'origin': '59_19~CUW~58_57#MGNP'} Metrics: ['ELUC: -9.073870745197201', 'NSGA-II_crowding_distance: 0.14539419409086735', 'NSGA-II_rank: 2', 'change: 0.13229981050092612', 'is_elite: False']\n", + "Id: 60_31 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_52', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_31', 'origin': '59_52~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.38474712443352', 'NSGA-II_crowding_distance: 0.22001963252176293', 'NSGA-II_rank: 2', 'change: 0.14843220471016597', 'is_elite: False']\n", + "Id: 60_45 Identity: {'ancestor_count': 56, 'ancestor_ids': ['56_84', '59_52'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_45', 'origin': '56_84~CUW~59_52#MGNP'} Metrics: ['ELUC: -9.502793378647874', 'NSGA-II_crowding_distance: 0.5211166550455899', 'NSGA-II_rank: 4', 'change: 0.1535989152695589', 'is_elite: False']\n", + "Id: 60_33 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_19', '59_98'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_33', 'origin': '59_19~CUW~59_98#MGNP'} Metrics: ['ELUC: -9.70343618658159', 'NSGA-II_crowding_distance: 0.18576565320805818', 'NSGA-II_rank: 1', 'change: 0.11352365564595365', 'is_elite: True']\n", + "Id: 60_71 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_57', '55_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_71', 'origin': '58_57~CUW~55_84#MGNP'} Metrics: ['ELUC: -9.722375146154867', 'NSGA-II_crowding_distance: 0.08484648777090162', 'NSGA-II_rank: 1', 'change: 0.11917477397751543', 'is_elite: False']\n", + "Id: 60_64 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_43', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_64', 'origin': '59_43~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.738244383591658', 'NSGA-II_crowding_distance: 0.6763153472947154', 'NSGA-II_rank: 5', 'change: 0.1568856665867265', 'is_elite: False']\n", + "Id: 60_65 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_52', '59_97'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_65', 'origin': '59_52~CUW~59_97#MGNP'} Metrics: ['ELUC: -10.1768609854797', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2857348234338591', 'is_elite: False']\n", + "Id: 60_68 Identity: {'ancestor_count': 56, 'ancestor_ids': ['1_1', '59_52'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_68', 'origin': '1_1~CUW~59_52#MGNP'} Metrics: ['ELUC: -10.2409663449936', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.17616746078308337', 'is_elite: False']\n", + "Id: 60_95 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_48', '58_79'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_95', 'origin': '59_48~CUW~58_79#MGNP'} Metrics: ['ELUC: -10.316691454687552', 'NSGA-II_crowding_distance: 0.6223101201161525', 'NSGA-II_rank: 4', 'change: 0.15618863491892718', 'is_elite: False']\n", + "Id: 60_83 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_48', '59_90'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_83', 'origin': '59_48~CUW~59_90#MGNP'} Metrics: ['ELUC: -10.599470398231094', 'NSGA-II_crowding_distance: 0.645467798099483', 'NSGA-II_rank: 3', 'change: 0.14996625479538267', 'is_elite: False']\n", + "Id: 56_84 Identity: {'ancestor_count': 51, 'ancestor_ids': ['55_84', '52_33'], 'birth_generation': 56, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '56_84', 'origin': '55_84~CUW~52_33#MGNP'} Metrics: ['ELUC: -10.771223220008585', 'NSGA-II_crowding_distance: 0.11038602125787345', 'NSGA-II_rank: 1', 'change: 0.12071928172471472', 'is_elite: False']\n", + "Id: 60_87 Identity: {'ancestor_count': 53, 'ancestor_ids': ['56_84', '59_67'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_87', 'origin': '56_84~CUW~59_67#MGNP'} Metrics: ['ELUC: -10.885708044157095', 'NSGA-II_crowding_distance: 0.11338781380658149', 'NSGA-II_rank: 1', 'change: 0.13236938491826195', 'is_elite: False']\n", + "Id: 60_15 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_65', '2_49'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_15', 'origin': '58_65~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.911936002986696', 'NSGA-II_crowding_distance: 0.7803186723168855', 'NSGA-II_rank: 4', 'change: 0.27228402948366115', 'is_elite: False']\n", + "Id: 60_78 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_57', '58_57'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_78', 'origin': '58_57~CUW~58_57#MGNP'} Metrics: ['ELUC: -11.097778284738059', 'NSGA-II_crowding_distance: 0.16333746516214412', 'NSGA-II_rank: 2', 'change: 0.14917558126713115', 'is_elite: False']\n", + "Id: 60_21 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_90', '59_48'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_21', 'origin': '59_90~CUW~59_48#MGNP'} Metrics: ['ELUC: -11.29177247824847', 'NSGA-II_crowding_distance: 0.1884231328187708', 'NSGA-II_rank: 2', 'change: 0.15483194681153872', 'is_elite: False']\n", + "Id: 60_90 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_57', '58_65'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_90', 'origin': '58_57~CUW~58_65#MGNP'} Metrics: ['ELUC: -11.679771616072433', 'NSGA-II_crowding_distance: 0.3096630654064116', 'NSGA-II_rank: 2', 'change: 0.18106927665994704', 'is_elite: False']\n", + "Id: 60_55 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_19', '59_43'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_55', 'origin': '59_19~CUW~59_43#MGNP'} Metrics: ['ELUC: -11.700535993478535', 'NSGA-II_crowding_distance: 0.22811535118312698', 'NSGA-II_rank: 1', 'change: 0.13878095429595477', 'is_elite: True']\n", + "Id: 60_26 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_97', '59_43'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_26', 'origin': '59_97~CUW~59_43#MGNP'} Metrics: ['ELUC: -12.044658354986566', 'NSGA-II_crowding_distance: 0.7108760551970241', 'NSGA-II_rank: 3', 'change: 0.23461636006360564', 'is_elite: False']\n", + "Id: 60_16 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_52', '59_62'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_16', 'origin': '59_52~CUW~59_62#MGNP'} Metrics: ['ELUC: -12.304910176409003', 'NSGA-II_crowding_distance: 0.24223286177371048', 'NSGA-II_rank: 1', 'change: 0.1763496244808586', 'is_elite: True']\n", + "Id: 60_27 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '2_49'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_27', 'origin': '59_67~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.830714049349032', 'NSGA-II_crowding_distance: 0.358915800646906', 'NSGA-II_rank: 3', 'change: 0.2798995158154752', 'is_elite: False']\n", + "Id: 60_98 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_97', '2_49'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_98', 'origin': '59_97~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.904084689841852', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.29083811330710085', 'is_elite: False']\n", + "Id: 60_99 Identity: {'ancestor_count': 56, 'ancestor_ids': ['55_84', '59_52'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_99', 'origin': '55_84~CUW~59_52#MGNP'} Metrics: ['ELUC: -13.283064916773851', 'NSGA-II_crowding_distance: 0.6588051900163248', 'NSGA-II_rank: 2', 'change: 0.19157021803736887', 'is_elite: False']\n", + "Id: 60_82 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_52', '59_19'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_82', 'origin': '59_52~CUW~59_19#MGNP'} Metrics: ['ELUC: -13.605553886347403', 'NSGA-II_crowding_distance: 0.1435991121909', 'NSGA-II_rank: 1', 'change: 0.17872910123074037', 'is_elite: False']\n", + "Id: 60_94 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_52', '59_19'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_94', 'origin': '59_52~CUW~59_19#MGNP'} Metrics: ['ELUC: -13.66952000065208', 'NSGA-II_crowding_distance: 0.10893410860688824', 'NSGA-II_rank: 1', 'change: 0.19603855011607432', 'is_elite: False']\n", + "Id: 60_37 Identity: {'ancestor_count': 56, 'ancestor_ids': ['2_49', '59_97'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_37', 'origin': '2_49~CUW~59_97#MGNP'} Metrics: ['ELUC: -13.754525959215979', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2900855847806826', 'is_elite: False']\n", + "Id: 59_52 Identity: {'ancestor_count': 55, 'ancestor_ids': ['56_80', '56_80'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_52', 'origin': '56_80~CUW~56_80#MGNP'} Metrics: ['ELUC: -14.228735743292848', 'NSGA-II_crowding_distance: 0.13731042629386683', 'NSGA-II_rank: 1', 'change: 0.20065702341712963', 'is_elite: False']\n", + "Id: 60_61 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_43', '59_67'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_61', 'origin': '59_43~CUW~59_67#MGNP'} Metrics: ['ELUC: -14.51498940391376', 'NSGA-II_crowding_distance: 0.10144730320537156', 'NSGA-II_rank: 1', 'change: 0.2226610449533609', 'is_elite: False']\n", + "Id: 60_19 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_43', '59_43'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_19', 'origin': '59_43~CUW~59_43#MGNP'} Metrics: ['ELUC: -14.699486851953434', 'NSGA-II_crowding_distance: 0.039262504790011074', 'NSGA-II_rank: 1', 'change: 0.2229378464925089', 'is_elite: False']\n", + "Id: 59_43 Identity: {'ancestor_count': 57, 'ancestor_ids': ['58_69', '56_84'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_43', 'origin': '58_69~CUW~56_84#MGNP'} Metrics: ['ELUC: -14.930627277590144', 'NSGA-II_crowding_distance: 0.07451152672707581', 'NSGA-II_rank: 1', 'change: 0.2273225985906412', 'is_elite: False']\n", + "Id: 60_77 Identity: {'ancestor_count': 58, 'ancestor_ids': ['56_84', '59_36'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_77', 'origin': '56_84~CUW~59_36#MGNP'} Metrics: ['ELUC: -15.252714809139702', 'NSGA-II_crowding_distance: 0.08341924230980684', 'NSGA-II_rank: 1', 'change: 0.23578197661124517', 'is_elite: False']\n", + "Id: 60_49 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_97', '59_67'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_49', 'origin': '59_97~CUW~59_67#MGNP'} Metrics: ['ELUC: -15.446517588608375', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2663455880364411', 'is_elite: False']\n", + "Id: 60_36 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_62', '59_43'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_36', 'origin': '59_62~CUW~59_43#MGNP'} Metrics: ['ELUC: -15.489619334239734', 'NSGA-II_crowding_distance: 0.04841924593428201', 'NSGA-II_rank: 1', 'change: 0.2427267739810329', 'is_elite: False']\n", + "Id: 60_12 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_43', '56_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_12', 'origin': '59_43~CUW~56_84#MGNP'} Metrics: ['ELUC: -15.589628975467935', 'NSGA-II_crowding_distance: 0.04673065524713563', 'NSGA-II_rank: 1', 'change: 0.24451166331606913', 'is_elite: False']\n", + "Id: 60_53 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_43', '59_19'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_53', 'origin': '59_43~CUW~59_19#MGNP'} Metrics: ['ELUC: -15.84631167742115', 'NSGA-II_crowding_distance: 0.1111354433032589', 'NSGA-II_rank: 1', 'change: 0.2506169810999184', 'is_elite: False']\n", + "Id: 60_18 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_98', '2_49'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_18', 'origin': '59_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.962478815527215', 'NSGA-II_crowding_distance: 0.13348969613080633', 'NSGA-II_rank: 1', 'change: 0.27134462618856586', 'is_elite: False']\n", + "Id: 60_75 Identity: {'ancestor_count': 56, 'ancestor_ids': ['2_49', '59_52'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_75', 'origin': '2_49~CUW~59_52#MGNP'} Metrics: ['ELUC: -16.009295915987977', 'NSGA-II_crowding_distance: 0.10574428326984817', 'NSGA-II_rank: 1', 'change: 0.28768143876876584', 'is_elite: False']\n", + "Id: 60_88 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_97', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_88', 'origin': '59_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.449784558977846', 'NSGA-II_crowding_distance: 0.13757889560394088', 'NSGA-II_rank: 1', 'change: 0.29462663510029596', 'is_elite: False']\n", + "Id: 60_93 Identity: {'ancestor_count': 58, 'ancestor_ids': ['2_49', '59_48'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_93', 'origin': '2_49~CUW~59_48#MGNP'} Metrics: ['ELUC: -17.55343862544332', 'NSGA-II_crowding_distance: 0.09178443338330296', 'NSGA-II_rank: 1', 'change: 0.30252733755042216', 'is_elite: False']\n", + "Id: 60_17 Identity: {'ancestor_count': 58, 'ancestor_ids': ['2_49', '59_48'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_17', 'origin': '2_49~CUW~59_48#MGNP'} Metrics: ['ELUC: -17.579256700215506', 'NSGA-II_crowding_distance: 0.0032152224144676765', 'NSGA-II_rank: 1', 'change: 0.30284557424441466', 'is_elite: False']\n", + "Id: 60_22 Identity: {'ancestor_count': 52, 'ancestor_ids': ['2_49', '58_79'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_22', 'origin': '2_49~CUW~58_79#MGNP'} Metrics: ['ELUC: -17.58327063647928', 'NSGA-II_crowding_distance: 0.0016172853882050922', 'NSGA-II_rank: 1', 'change: 0.30298042984510454', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 59_97 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_77', '58_65'], 'birth_generation': 59, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '59_97', 'origin': '58_77~CUW~58_65#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 60_23 Identity: {'ancestor_count': 58, 'ancestor_ids': ['2_49', '59_62'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_23', 'origin': '2_49~CUW~59_62#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 60_43 Identity: {'ancestor_count': 56, 'ancestor_ids': ['59_97', '59_52'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_43', 'origin': '59_97~CUW~59_52#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 60_97 Identity: {'ancestor_count': 57, 'ancestor_ids': ['2_49', '58_57'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_97', 'origin': '2_49~CUW~58_57#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 60.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 61...:\n", + "PopulationResponse:\n", + " Generation: 61\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/61/20240220-030047\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 61 and asking ESP for generation 62...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 61 data persisted.\n", + "Evaluated candidates:\n", + "Id: 61_93 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_52', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_93', 'origin': '60_52~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 61_94 Identity: {'ancestor_count': 53, 'ancestor_ids': ['60_81', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_94', 'origin': '60_81~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 61_79 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_97', '60_30'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_79', 'origin': '60_97~CUW~60_30#MGNP'} Metrics: ['ELUC: 10.384947966596881', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24927484492793003', 'is_elite: False']\n", + "Id: 61_40 Identity: {'ancestor_count': 57, 'ancestor_ids': ['60_82', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_40', 'origin': '60_82~CUW~60_100#MGNP'} Metrics: ['ELUC: 1.0772520884885861', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.11093483392255707', 'is_elite: False']\n", + "Id: 61_56 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_57', '60_97'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_56', 'origin': '60_57~CUW~60_97#MGNP'} Metrics: ['ELUC: 0.787231532902641', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2429023387230917', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 61_17 Identity: {'ancestor_count': 54, 'ancestor_ids': ['1_1', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_17', 'origin': '1_1~CUW~60_100#MGNP'} Metrics: ['ELUC: -0.09001621676002855', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.044614487564164224', 'is_elite: False']\n", + "Id: 61_70 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_70', 'origin': '60_16~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.24573281004562475', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.09837113277702747', 'is_elite: False']\n", + "Id: 60_57 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_57', 'origin': '59_67~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.4169910859547102', 'NSGA-II_crowding_distance: 0.23184068418385825', 'NSGA-II_rank: 1', 'change: 0.04210233883091324', 'is_elite: True']\n", + "Id: 61_41 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_41', 'origin': '2_49~CUW~60_100#MGNP'} Metrics: ['ELUC: -0.7192519037275099', 'NSGA-II_crowding_distance: 1.4998050850938718', 'NSGA-II_rank: 8', 'change: 0.23129106233899296', 'is_elite: False']\n", + "Id: 61_69 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '58_65'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_69', 'origin': '1_1~CUW~58_65#MGNP'} Metrics: ['ELUC: -0.7731551202932083', 'NSGA-II_crowding_distance: 0.1537694532514354', 'NSGA-II_rank: 2', 'change: 0.04659323226069087', 'is_elite: False']\n", + "Id: 61_95 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_41', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_95', 'origin': '60_41~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.886652905658149', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.0873583130545291', 'is_elite: False']\n", + "Id: 61_61 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '60_57'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_61', 'origin': '60_55~CUW~60_57#MGNP'} Metrics: ['ELUC: -1.1241324455779576', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.07660106254812726', 'is_elite: False']\n", + "Id: 61_88 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '60_57'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_88', 'origin': '60_57~CUW~60_57#MGNP'} Metrics: ['ELUC: -1.1623391223512904', 'NSGA-II_crowding_distance: 1.2841453321307665', 'NSGA-II_rank: 6', 'change: 0.07675302423970325', 'is_elite: False']\n", + "Id: 61_67 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_52', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_67', 'origin': '60_52~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1867377158457053', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07629573329262572', 'is_elite: False']\n", + "Id: 61_73 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_73', 'origin': '60_57~CUW~60_100#MGNP'} Metrics: ['ELUC: -1.1911183078484529', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0487696783978016', 'is_elite: False']\n", + "Id: 61_85 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_85', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.5014583243776765', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.29086436748662997', 'is_elite: False']\n", + "Id: 61_15 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_100', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_15', 'origin': '60_100~CUW~60_100#MGNP'} Metrics: ['ELUC: -1.5225078381472752', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05316374146057843', 'is_elite: False']\n", + "Id: 61_58 Identity: {'ancestor_count': 56, 'ancestor_ids': ['60_57', '60_30'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_58', 'origin': '60_57~CUW~60_30#MGNP'} Metrics: ['ELUC: -1.5792003008079798', 'NSGA-II_crowding_distance: 0.5006142447347621', 'NSGA-II_rank: 4', 'change: 0.05386053097783922', 'is_elite: False']\n", + "Id: 61_80 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_100', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_80', 'origin': '60_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8396226219100624', 'NSGA-II_crowding_distance: 0.12969754598689653', 'NSGA-II_rank: 1', 'change: 0.042855241619738624', 'is_elite: False']\n", + "Id: 61_46 Identity: {'ancestor_count': 56, 'ancestor_ids': ['60_30', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_46', 'origin': '60_30~CUW~60_100#MGNP'} Metrics: ['ELUC: -2.0513628052484734', 'NSGA-II_crowding_distance: 0.16314112470235403', 'NSGA-II_rank: 3', 'change: 0.0502601624902584', 'is_elite: False']\n", + "Id: 61_65 Identity: {'ancestor_count': 56, 'ancestor_ids': ['60_52', '60_30'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_65', 'origin': '60_52~CUW~60_30#MGNP'} Metrics: ['ELUC: -2.278782474844029', 'NSGA-II_crowding_distance: 0.1179074381377917', 'NSGA-II_rank: 3', 'change: 0.07325413222637403', 'is_elite: False']\n", + "Id: 61_71 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_100', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_71', 'origin': '60_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.4184891290870967', 'NSGA-II_crowding_distance: 1.0999590816079217', 'NSGA-II_rank: 8', 'change: 0.26229712944636513', 'is_elite: False']\n", + "Id: 61_75 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_52', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_75', 'origin': '60_52~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.434200593667449', 'NSGA-II_crowding_distance: 0.10978737952046658', 'NSGA-II_rank: 3', 'change: 0.07432206396148074', 'is_elite: False']\n", + "Id: 60_100 Identity: {'ancestor_count': 53, 'ancestor_ids': ['1_1', '59_14'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_100', 'origin': '1_1~CUW~59_14#MGNP'} Metrics: ['ELUC: -2.491890822134257', 'NSGA-II_crowding_distance: 0.286923615745172', 'NSGA-II_rank: 2', 'change: 0.04866278155458055', 'is_elite: False']\n", + "Id: 61_62 Identity: {'ancestor_count': 56, 'ancestor_ids': ['1_1', '60_30'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_62', 'origin': '1_1~CUW~60_30#MGNP'} Metrics: ['ELUC: -2.540727774061076', 'NSGA-II_crowding_distance: 0.08592637241288154', 'NSGA-II_rank: 1', 'change: 0.044760730097731356', 'is_elite: False']\n", + "Id: 61_20 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_100', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_20', 'origin': '60_100~CUW~60_100#MGNP'} Metrics: ['ELUC: -2.5564895253322604', 'NSGA-II_crowding_distance: 0.13836778796346771', 'NSGA-II_rank: 1', 'change: 0.05632830395823944', 'is_elite: False']\n", + "Id: 61_68 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_68', 'origin': '60_55~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.0411063639595888', 'NSGA-II_crowding_distance: 0.2847689264775153', 'NSGA-II_rank: 3', 'change: 0.08925172757825277', 'is_elite: False']\n", + "Id: 61_45 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_65', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_45', 'origin': '58_65~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.579410853028609', 'NSGA-II_crowding_distance: 0.3156837525004259', 'NSGA-II_rank: 2', 'change: 0.07896927278189947', 'is_elite: False']\n", + "Id: 61_26 Identity: {'ancestor_count': 55, 'ancestor_ids': ['60_41', '58_65'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_26', 'origin': '60_41~CUW~58_65#MGNP'} Metrics: ['ELUC: -3.7192055298453104', 'NSGA-II_crowding_distance: 0.770661717816036', 'NSGA-II_rank: 4', 'change: 0.10073965868434229', 'is_elite: False']\n", + "Id: 58_65 Identity: {'ancestor_count': 54, 'ancestor_ids': ['57_39', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_65', 'origin': '57_39~CUW~56_22#MGNP'} Metrics: ['ELUC: -3.8923608700709917', 'NSGA-II_crowding_distance: 0.2557143952661717', 'NSGA-II_rank: 1', 'change: 0.0631089642439499', 'is_elite: True']\n", + "Id: 61_18 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_18', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.321484725836063', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2679418475004934', 'is_elite: False']\n", + "Id: 61_82 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_82', 'origin': '60_55~CUW~60_100#MGNP'} Metrics: ['ELUC: -4.832533849499337', 'NSGA-II_crowding_distance: 0.9150031125378985', 'NSGA-II_rank: 5', 'change: 0.12270707115367055', 'is_elite: False']\n", + "Id: 61_72 Identity: {'ancestor_count': 57, 'ancestor_ids': ['60_88', '60_52'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_72', 'origin': '60_88~CUW~60_52#MGNP'} Metrics: ['ELUC: -5.112483626258861', 'NSGA-II_crowding_distance: 1.5196166367494128', 'NSGA-II_rank: 6', 'change: 0.23456207364664514', 'is_elite: False']\n", + "Id: 61_86 Identity: {'ancestor_count': 55, 'ancestor_ids': ['60_41', '58_65'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_86', 'origin': '60_41~CUW~58_65#MGNP'} Metrics: ['ELUC: -5.2347712385585545', 'NSGA-II_crowding_distance: 0.1477965607653184', 'NSGA-II_rank: 2', 'change: 0.08939024859729766', 'is_elite: False']\n", + "Id: 61_44 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_52', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_44', 'origin': '60_52~CUW~60_100#MGNP'} Metrics: ['ELUC: -5.355640622507547', 'NSGA-II_crowding_distance: 0.027941047180906384', 'NSGA-II_rank: 2', 'change: 0.09074703094220081', 'is_elite: False']\n", + "Id: 61_66 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '60_81'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_66', 'origin': '60_55~CUW~60_81#MGNP'} Metrics: ['ELUC: -5.378171447202663', 'NSGA-II_crowding_distance: 0.31726917496751506', 'NSGA-II_rank: 3', 'change: 0.10055658134698692', 'is_elite: False']\n", + "Id: 61_43 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_81', '60_52'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_43', 'origin': '60_81~CUW~60_52#MGNP'} Metrics: ['ELUC: -5.405072234796236', 'NSGA-II_crowding_distance: 0.49061393515623286', 'NSGA-II_rank: 4', 'change: 0.12008873700825251', 'is_elite: False']\n", + "Id: 61_34 Identity: {'ancestor_count': 55, 'ancestor_ids': ['60_41', '58_65'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_34', 'origin': '60_41~CUW~58_65#MGNP'} Metrics: ['ELUC: -5.490077186028394', 'NSGA-II_crowding_distance: 0.21147762269912954', 'NSGA-II_rank: 1', 'change: 0.08284389411059444', 'is_elite: True']\n", + "Id: 61_21 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_41', '60_52'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_21', 'origin': '60_41~CUW~60_52#MGNP'} Metrics: ['ELUC: -5.596842262323476', 'NSGA-II_crowding_distance: 0.08230333860073899', 'NSGA-II_rank: 2', 'change: 0.091227601935244', 'is_elite: False']\n", + "Id: 61_78 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_41', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_78', 'origin': '60_41~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.6842534525888615', 'NSGA-II_crowding_distance: 1.560942027322048', 'NSGA-II_rank: 7', 'change: 0.2512547539123035', 'is_elite: False']\n", + "Id: 61_48 Identity: {'ancestor_count': 57, 'ancestor_ids': ['60_81', '60_88'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_48', 'origin': '60_81~CUW~60_88#MGNP'} Metrics: ['ELUC: -5.728589235834302', 'NSGA-II_crowding_distance: 0.9349887456619045', 'NSGA-II_rank: 5', 'change: 0.1775955469406343', 'is_elite: False']\n", + "Id: 61_39 Identity: {'ancestor_count': 56, 'ancestor_ids': ['2_49', '59_52'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_39', 'origin': '2_49~CUW~59_52#MGNP'} Metrics: ['ELUC: -6.044331521976985', 'NSGA-II_crowding_distance: 0.5449013278559546', 'NSGA-II_rank: 7', 'change: 0.2628517756704326', 'is_elite: False']\n", + "Id: 61_16 Identity: {'ancestor_count': 56, 'ancestor_ids': ['60_30', '60_41'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_16', 'origin': '60_30~CUW~60_41#MGNP'} Metrics: ['ELUC: -6.207080152268464', 'NSGA-II_crowding_distance: 0.15144963737695447', 'NSGA-II_rank: 2', 'change: 0.09934554009003589', 'is_elite: False']\n", + "Id: 61_89 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_52', '60_52'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_89', 'origin': '60_52~CUW~60_52#MGNP'} Metrics: ['ELUC: -6.234012635498089', 'NSGA-II_crowding_distance: 0.10565005522047427', 'NSGA-II_rank: 1', 'change: 0.08647062186484353', 'is_elite: False']\n", + "Id: 61_84 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_41'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_84', 'origin': '60_16~CUW~60_41#MGNP'} Metrics: ['ELUC: -6.336325773933395', 'NSGA-II_crowding_distance: 1.2196506365542503', 'NSGA-II_rank: 4', 'change: 0.14003623561542258', 'is_elite: False']\n", + "Id: 61_28 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_41', '60_52'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_28', 'origin': '60_41~CUW~60_52#MGNP'} Metrics: ['ELUC: -6.492196694222276', 'NSGA-II_crowding_distance: 0.05204372231283544', 'NSGA-II_rank: 1', 'change: 0.09736123923558425', 'is_elite: False']\n", + "Id: 61_96 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_52', '60_81'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_96', 'origin': '60_52~CUW~60_81#MGNP'} Metrics: ['ELUC: -6.4963153129687505', 'NSGA-II_crowding_distance: 0.09421866746042215', 'NSGA-II_rank: 1', 'change: 0.09754795150607266', 'is_elite: False']\n", + "Id: 61_37 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_88'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_37', 'origin': '60_16~CUW~60_88#MGNP'} Metrics: ['ELUC: -6.5606209199914405', 'NSGA-II_crowding_distance: 0.634787993180904', 'NSGA-II_rank: 6', 'change: 0.24703437645025791', 'is_elite: False']\n", + "Id: 61_27 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_41', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_27', 'origin': '60_41~CUW~60_16#MGNP'} Metrics: ['ELUC: -6.592670500356175', 'NSGA-II_crowding_distance: 0.6167639623314303', 'NSGA-II_rank: 3', 'change: 0.11419254283246219', 'is_elite: False']\n", + "Id: 60_41 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '56_84'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_41', 'origin': '59_67~CUW~56_84#MGNP'} Metrics: ['ELUC: -7.219014948557207', 'NSGA-II_crowding_distance: 0.3048490034623826', 'NSGA-II_rank: 2', 'change: 0.1062292369726629', 'is_elite: False']\n", + "Id: 61_14 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_41', '60_55'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_14', 'origin': '60_41~CUW~60_55#MGNP'} Metrics: ['ELUC: -7.627080750127646', 'NSGA-II_crowding_distance: 0.11267094291740673', 'NSGA-II_rank: 1', 'change: 0.10621465772019302', 'is_elite: False']\n", + "Id: 61_42 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_41', '60_41'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_42', 'origin': '60_41~CUW~60_41#MGNP'} Metrics: ['ELUC: -7.9633506744724', 'NSGA-II_crowding_distance: 0.1425890322867657', 'NSGA-II_rank: 1', 'change: 0.1062704077521606', 'is_elite: False']\n", + "Id: 61_23 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_23', 'origin': '2_49~CUW~60_100#MGNP'} Metrics: ['ELUC: -8.034510540727169', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2964353696440984', 'is_elite: False']\n", + "Id: 61_52 Identity: {'ancestor_count': 59, 'ancestor_ids': ['2_49', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_52', 'origin': '2_49~CUW~60_16#MGNP'} Metrics: ['ELUC: -8.818523759508972', 'NSGA-II_crowding_distance: 0.47491569174937254', 'NSGA-II_rank: 6', 'change: 0.27010265243046633', 'is_elite: False']\n", + "Id: 61_83 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_97', '60_55'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_83', 'origin': '60_97~CUW~60_55#MGNP'} Metrics: ['ELUC: -9.194744795360108', 'NSGA-II_crowding_distance: 0.8109862206538578', 'NSGA-II_rank: 5', 'change: 0.23220802653419795', 'is_elite: False']\n", + "Id: 61_29 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_29', 'origin': '60_55~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.24497004178103', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2757903176429706', 'is_elite: False']\n", + "Id: 60_33 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_19', '59_98'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_33', 'origin': '59_19~CUW~59_98#MGNP'} Metrics: ['ELUC: -9.70343618658159', 'NSGA-II_crowding_distance: 0.19526721608179826', 'NSGA-II_rank: 1', 'change: 0.11352365564595365', 'is_elite: True']\n", + "Id: 61_22 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '60_33'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_22', 'origin': '60_55~CUW~60_33#MGNP'} Metrics: ['ELUC: -9.901863611434788', 'NSGA-II_crowding_distance: 0.3125265932310518', 'NSGA-II_rank: 2', 'change: 0.12317810997055607', 'is_elite: False']\n", + "Id: 61_97 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_41', '60_33'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_97', 'origin': '60_41~CUW~60_33#MGNP'} Metrics: ['ELUC: -10.415423142223812', 'NSGA-II_crowding_distance: 0.14964507501732466', 'NSGA-II_rank: 1', 'change: 0.12292136795096867', 'is_elite: False']\n", + "Id: 61_90 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_33', '60_81'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_90', 'origin': '60_33~CUW~60_81#MGNP'} Metrics: ['ELUC: -10.94637245095375', 'NSGA-II_crowding_distance: 0.1529955319825047', 'NSGA-II_rank: 2', 'change: 0.13155801601406236', 'is_elite: False']\n", + "Id: 61_57 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_53', '1_1'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_57', 'origin': '60_53~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.043857357644736', 'NSGA-II_crowding_distance: 0.5781535751753727', 'NSGA-II_rank: 3', 'change: 0.16859282395902966', 'is_elite: False']\n", + "Id: 61_81 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_18', '60_41'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_81', 'origin': '60_18~CUW~60_41#MGNP'} Metrics: ['ELUC: -11.083791396425985', 'NSGA-II_crowding_distance: 0.4911404722539009', 'NSGA-II_rank: 5', 'change: 0.2388234288277355', 'is_elite: False']\n", + "Id: 61_99 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_33', '60_53'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_99', 'origin': '60_33~CUW~60_53#MGNP'} Metrics: ['ELUC: -11.28280331899918', 'NSGA-II_crowding_distance: 0.1141289227910221', 'NSGA-II_rank: 1', 'change: 0.13137206414948369', 'is_elite: False']\n", + "Id: 61_19 Identity: {'ancestor_count': 57, 'ancestor_ids': ['60_82', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_19', 'origin': '60_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.305476331038774', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.29360847237271', 'is_elite: False']\n", + "Id: 61_12 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_53', '60_33'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_12', 'origin': '60_53~CUW~60_33#MGNP'} Metrics: ['ELUC: -11.697502500560638', 'NSGA-II_crowding_distance: 0.0713746809489925', 'NSGA-II_rank: 2', 'change: 0.13600828550500033', 'is_elite: False']\n", + "Id: 60_55 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_19', '59_43'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_55', 'origin': '59_19~CUW~59_43#MGNP'} Metrics: ['ELUC: -11.700535993478535', 'NSGA-II_crowding_distance: 0.1561258937697889', 'NSGA-II_rank: 2', 'change: 0.13878095429595477', 'is_elite: False']\n", + "Id: 61_74 Identity: {'ancestor_count': 59, 'ancestor_ids': ['56_84', '60_55'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_74', 'origin': '56_84~CUW~60_55#MGNP'} Metrics: ['ELUC: -11.83742990430741', 'NSGA-II_crowding_distance: 0.0789763981721581', 'NSGA-II_rank: 1', 'change: 0.13284300210787192', 'is_elite: False']\n", + "Id: 61_54 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_88', '60_55'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_54', 'origin': '60_88~CUW~60_55#MGNP'} Metrics: ['ELUC: -11.93117118954042', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.21746274474529936', 'is_elite: False']\n", + "Id: 61_55 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_55', 'origin': '60_16~CUW~60_16#MGNP'} Metrics: ['ELUC: -12.020873191955092', 'NSGA-II_crowding_distance: 0.5325341704506642', 'NSGA-II_rank: 3', 'change: 0.1761194028701436', 'is_elite: False']\n", + "Id: 61_50 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '60_55'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_50', 'origin': '60_55~CUW~60_55#MGNP'} Metrics: ['ELUC: -12.030274133756391', 'NSGA-II_crowding_distance: 0.05557238994093661', 'NSGA-II_rank: 1', 'change: 0.14225205125259135', 'is_elite: False']\n", + "Id: 61_13 Identity: {'ancestor_count': 57, 'ancestor_ids': ['60_52', '60_82'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_13', 'origin': '60_52~CUW~60_82#MGNP'} Metrics: ['ELUC: -12.041785251289843', 'NSGA-II_crowding_distance: 0.06322491869131924', 'NSGA-II_rank: 1', 'change: 0.14595659158664395', 'is_elite: False']\n", + "Id: 61_59 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_59', 'origin': '60_16~CUW~60_16#MGNP'} Metrics: ['ELUC: -12.127066953305821', 'NSGA-II_crowding_distance: 0.18050418896558312', 'NSGA-II_rank: 2', 'change: 0.16988358623389363', 'is_elite: False']\n", + "Id: 61_60 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_41', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_60', 'origin': '60_41~CUW~60_16#MGNP'} Metrics: ['ELUC: -12.159163999266042', 'NSGA-II_crowding_distance: 0.10988670012598428', 'NSGA-II_rank: 1', 'change: 0.15892965724570202', 'is_elite: False']\n", + "Id: 61_77 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_77', 'origin': '60_16~CUW~60_16#MGNP'} Metrics: ['ELUC: -12.292745259017233', 'NSGA-II_crowding_distance: 0.0700471811290553', 'NSGA-II_rank: 1', 'change: 0.17448546534126527', 'is_elite: False']\n", + "Id: 60_16 Identity: {'ancestor_count': 58, 'ancestor_ids': ['59_52', '59_62'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_16', 'origin': '59_52~CUW~59_62#MGNP'} Metrics: ['ELUC: -12.304910176409003', 'NSGA-II_crowding_distance: 0.17911165998683115', 'NSGA-II_rank: 2', 'change: 0.1763496244808586', 'is_elite: False']\n", + "Id: 61_98 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_98', 'origin': '60_16~CUW~60_16#MGNP'} Metrics: ['ELUC: -12.416283425151745', 'NSGA-II_crowding_distance: 0.033590889846323885', 'NSGA-II_rank: 1', 'change: 0.1754667791560275', 'is_elite: False']\n", + "Id: 61_47 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_47', 'origin': '60_55~CUW~60_16#MGNP'} Metrics: ['ELUC: -12.558769145859516', 'NSGA-II_crowding_distance: 0.0325609396336435', 'NSGA-II_rank: 1', 'change: 0.17999373093763937', 'is_elite: False']\n", + "Id: 61_100 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_41', '60_97'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_100', 'origin': '60_41~CUW~60_97#MGNP'} Metrics: ['ELUC: -12.60950750963914', 'NSGA-II_crowding_distance: 0.5035437705687443', 'NSGA-II_rank: 3', 'change: 0.2798499251802013', 'is_elite: False']\n", + "Id: 61_25 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_25', 'origin': '60_16~CUW~60_16#MGNP'} Metrics: ['ELUC: -12.66698227866497', 'NSGA-II_crowding_distance: 0.06948992644246117', 'NSGA-II_rank: 1', 'change: 0.18092780110030082', 'is_elite: False']\n", + "Id: 61_36 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_41', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_36', 'origin': '60_41~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.072246326983882', 'NSGA-II_crowding_distance: 0.35583248676261325', 'NSGA-II_rank: 3', 'change: 0.2880931988519351', 'is_elite: False']\n", + "Id: 61_24 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_55', '60_16'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_24', 'origin': '60_55~CUW~60_16#MGNP'} Metrics: ['ELUC: -13.42291141867369', 'NSGA-II_crowding_distance: 0.5669510512078365', 'NSGA-II_rank: 2', 'change: 0.19684925706245202', 'is_elite: False']\n", + "Id: 61_51 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_82'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_51', 'origin': '60_16~CUW~60_82#MGNP'} Metrics: ['ELUC: -13.65856940310432', 'NSGA-II_crowding_distance: 0.29261605026883286', 'NSGA-II_rank: 1', 'change: 0.18206402707296074', 'is_elite: True']\n", + "Id: 61_53 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_53', '60_81'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_53', 'origin': '60_53~CUW~60_81#MGNP'} Metrics: ['ELUC: -14.671480366057644', 'NSGA-II_crowding_distance: 0.4651273883727987', 'NSGA-II_rank: 1', 'change: 0.23422095910340845', 'is_elite: True']\n", + "Id: 61_91 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_97', '60_100'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_91', 'origin': '60_97~CUW~60_100#MGNP'} Metrics: ['ELUC: -14.72094330527499', 'NSGA-II_crowding_distance: 0.6170197263922078', 'NSGA-II_rank: 2', 'change: 0.2866799627980015', 'is_elite: False']\n", + "Id: 61_31 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_31', 'origin': '60_57~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.744869910992922', 'NSGA-II_crowding_distance: 0.3514154605546576', 'NSGA-II_rank: 1', 'change: 0.2854425115582287', 'is_elite: True']\n", + "Id: 61_76 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_41', '60_97'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_76', 'origin': '60_41~CUW~60_97#MGNP'} Metrics: ['ELUC: -16.99911775734116', 'NSGA-II_crowding_distance: 0.32810497506554726', 'NSGA-II_rank: 3', 'change: 0.3014069676778308', 'is_elite: False']\n", + "Id: 61_35 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_100', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_35', 'origin': '60_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.10847042711518', 'NSGA-II_crowding_distance: 0.21701107730136404', 'NSGA-II_rank: 2', 'change: 0.30127614259546387', 'is_elite: False']\n", + "Id: 61_92 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_33', '60_97'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_92', 'origin': '60_33~CUW~60_97#MGNP'} Metrics: ['ELUC: -17.265977142409493', 'NSGA-II_crowding_distance: 0.15164393009756938', 'NSGA-II_rank: 1', 'change: 0.2950460911838097', 'is_elite: False']\n", + "Id: 61_64 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_41'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_64', 'origin': '2_49~CUW~60_41#MGNP'} Metrics: ['ELUC: -17.36473002115662', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30410380616072025', 'is_elite: False']\n", + "Id: 61_32 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_57'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_32', 'origin': '2_49~CUW~60_57#MGNP'} Metrics: ['ELUC: -17.448553755319058', 'NSGA-II_crowding_distance: 0.025929707003123203', 'NSGA-II_rank: 2', 'change: 0.30220214583829424', 'is_elite: False']\n", + "Id: 61_33 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_41'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_33', 'origin': '2_49~CUW~60_41#MGNP'} Metrics: ['ELUC: -17.487047853905775', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3023505595587059', 'is_elite: False']\n", + "Id: 61_30 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_97', '60_57'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_30', 'origin': '60_97~CUW~60_57#MGNP'} Metrics: ['ELUC: -17.50676119535754', 'NSGA-II_crowding_distance: 0.0417151267626544', 'NSGA-II_rank: 1', 'change: 0.30078984276535004', 'is_elite: False']\n", + "Id: 61_38 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_41'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_38', 'origin': '2_49~CUW~60_41#MGNP'} Metrics: ['ELUC: -17.529868246364863', 'NSGA-II_crowding_distance: 0.01263018071852445', 'NSGA-II_rank: 1', 'change: 0.3030146420051475', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 60_97 Identity: {'ancestor_count': 57, 'ancestor_ids': ['2_49', '58_57'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_97', 'origin': '2_49~CUW~58_57#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 61_11 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_97', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_11', 'origin': '60_97~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 61_49 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_33', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_49', 'origin': '60_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 61_63 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_57', '60_97'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_63', 'origin': '60_57~CUW~60_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 61_87 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_97', '60_97'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_87', 'origin': '60_97~CUW~60_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 61.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 62...:\n", + "PopulationResponse:\n", + " Generation: 62\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/62/20240220-030801\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 62 and asking ESP for generation 63...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 62 data persisted.\n", + "Evaluated candidates:\n", + "Id: 62_21 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '61_31'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_21', 'origin': '1_1~CUW~61_31#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 62_77 Identity: {'ancestor_count': 59, 'ancestor_ids': ['1_1', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_77', 'origin': '1_1~CUW~61_87#MGNP'} Metrics: ['ELUC: 21.312260739570306', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2867974729222322', 'is_elite: False']\n", + "Id: 62_42 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_14', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_42', 'origin': '61_14~CUW~61_87#MGNP'} Metrics: ['ELUC: 18.896882484620235', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.28131164920724944', 'is_elite: False']\n", + "Id: 62_48 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_31', '61_97'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_48', 'origin': '61_31~CUW~61_97#MGNP'} Metrics: ['ELUC: 15.783340953812877', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.2974072476027655', 'is_elite: False']\n", + "Id: 62_70 Identity: {'ancestor_count': 60, 'ancestor_ids': ['2_49', '61_14'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_70', 'origin': '2_49~CUW~61_14#MGNP'} Metrics: ['ELUC: 14.150133735734926', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2693230921129941', 'is_elite: False']\n", + "Id: 62_62 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_62', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 10.97109972307019', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.24128830237818796', 'is_elite: False']\n", + "Id: 62_58 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_92', '58_65'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_58', 'origin': '61_92~CUW~58_65#MGNP'} Metrics: ['ELUC: 3.4499779939383224', 'NSGA-II_crowding_distance: 1.4926423890326974', 'NSGA-II_rank: 6', 'change: 0.25860029813759794', 'is_elite: False']\n", + "Id: 62_93 Identity: {'ancestor_count': 55, 'ancestor_ids': ['60_33', '61_80'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_93', 'origin': '60_33~CUW~61_80#MGNP'} Metrics: ['ELUC: 2.1304105703158016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0797559736784738', 'is_elite: False']\n", + "Id: 62_64 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_14', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_64', 'origin': '61_14~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.65275333719232', 'NSGA-II_crowding_distance: 0.2069316500059744', 'NSGA-II_rank: 3', 'change: 0.07976685523708894', 'is_elite: False']\n", + "Id: 62_40 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_20', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_40', 'origin': '61_20~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.406700803270689', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.041129096780423306', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 60_57 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_67', '1_1'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_57', 'origin': '59_67~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.4169910859547102', 'NSGA-II_crowding_distance: 0.20495414588004485', 'NSGA-II_rank: 1', 'change: 0.04210233883091324', 'is_elite: False']\n", + "Id: 62_11 Identity: {'ancestor_count': 56, 'ancestor_ids': ['61_34', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_11', 'origin': '61_34~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 62_53 Identity: {'ancestor_count': 60, 'ancestor_ids': ['60_57', '61_53'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_53', 'origin': '60_57~CUW~61_53#MGNP'} Metrics: ['ELUC: -0.696574171023812', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09881959338655241', 'is_elite: False']\n", + "Id: 62_25 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_25', 'origin': '60_57~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8181810886103418', 'NSGA-II_crowding_distance: 0.16490003558141844', 'NSGA-II_rank: 2', 'change: 0.046116635788150874', 'is_elite: False']\n", + "Id: 62_79 Identity: {'ancestor_count': 56, 'ancestor_ids': ['60_57', '61_34'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_79', 'origin': '60_57~CUW~61_34#MGNP'} Metrics: ['ELUC: -1.2657842702932953', 'NSGA-II_crowding_distance: 0.05863006601242397', 'NSGA-II_rank: 2', 'change: 0.04747877729836437', 'is_elite: False']\n", + "Id: 62_20 Identity: {'ancestor_count': 54, 'ancestor_ids': ['1_1', '60_57'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_20', 'origin': '1_1~CUW~60_57#MGNP'} Metrics: ['ELUC: -1.360523244105897', 'NSGA-II_crowding_distance: 0.09749237526631716', 'NSGA-II_rank: 1', 'change: 0.04296336185760715', 'is_elite: False']\n", + "Id: 62_52 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_42', '58_65'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_52', 'origin': '61_42~CUW~58_65#MGNP'} Metrics: ['ELUC: -1.5632203773672253', 'NSGA-II_crowding_distance: 0.1462600862217573', 'NSGA-II_rank: 2', 'change: 0.05120220070539189', 'is_elite: False']\n", + "Id: 62_67 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_33', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_67', 'origin': '60_33~CUW~61_87#MGNP'} Metrics: ['ELUC: -1.6387142117031739', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3194728793740743', 'is_elite: False']\n", + "Id: 62_65 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_97', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_65', 'origin': '61_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8273688461745863', 'NSGA-II_crowding_distance: 0.23804688799202572', 'NSGA-II_rank: 3', 'change: 0.08013152074043114', 'is_elite: False']\n", + "Id: 62_30 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_30', 'origin': '60_57~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8302981175632846', 'NSGA-II_crowding_distance: 0.07002372939964002', 'NSGA-II_rank: 1', 'change: 0.04720763506947917', 'is_elite: False']\n", + "Id: 62_23 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_51', '58_65'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_23', 'origin': '61_51~CUW~58_65#MGNP'} Metrics: ['ELUC: -1.886971565165286', 'NSGA-II_crowding_distance: 0.226927541479102', 'NSGA-II_rank: 2', 'change: 0.07722183525080151', 'is_elite: False']\n", + "Id: 62_47 Identity: {'ancestor_count': 55, 'ancestor_ids': ['1_1', '58_65'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_47', 'origin': '1_1~CUW~58_65#MGNP'} Metrics: ['ELUC: -2.1118762260659487', 'NSGA-II_crowding_distance: 0.17260762235092356', 'NSGA-II_rank: 3', 'change: 0.08940314673136335', 'is_elite: False']\n", + "Id: 62_82 Identity: {'ancestor_count': 56, 'ancestor_ids': ['61_34', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_82', 'origin': '61_34~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.3334934768736235', 'NSGA-II_crowding_distance: 0.08940690843384577', 'NSGA-II_rank: 1', 'change: 0.04734527749952752', 'is_elite: False']\n", + "Id: 62_98 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_65', '61_42'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_98', 'origin': '58_65~CUW~61_42#MGNP'} Metrics: ['ELUC: -2.9728127476092054', 'NSGA-II_crowding_distance: 0.1414922923735245', 'NSGA-II_rank: 1', 'change: 0.05449583869896279', 'is_elite: False']\n", + "Id: 62_26 Identity: {'ancestor_count': 56, 'ancestor_ids': ['61_34', '61_42'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_26', 'origin': '61_34~CUW~61_42#MGNP'} Metrics: ['ELUC: -3.833113070758701', 'NSGA-II_crowding_distance: 0.11952536700877739', 'NSGA-II_rank: 2', 'change: 0.0793462432658921', 'is_elite: False']\n", + "Id: 62_97 Identity: {'ancestor_count': 56, 'ancestor_ids': ['61_34', '61_20'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_97', 'origin': '61_34~CUW~61_20#MGNP'} Metrics: ['ELUC: -3.8781076393479657', 'NSGA-II_crowding_distance: 0.12752533363246554', 'NSGA-II_rank: 2', 'change: 0.08107963098084549', 'is_elite: False']\n", + "Id: 58_65 Identity: {'ancestor_count': 54, 'ancestor_ids': ['57_39', '56_22'], 'birth_generation': 58, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '58_65', 'origin': '57_39~CUW~56_22#MGNP'} Metrics: ['ELUC: -3.8923608700709917', 'NSGA-II_crowding_distance: 0.12611501035051553', 'NSGA-II_rank: 1', 'change: 0.0631089642439499', 'is_elite: False']\n", + "Id: 62_54 Identity: {'ancestor_count': 59, 'ancestor_ids': ['1_1', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_54', 'origin': '1_1~CUW~61_87#MGNP'} Metrics: ['ELUC: -4.039756542112996', 'NSGA-II_crowding_distance: 0.8050828604962886', 'NSGA-II_rank: 5', 'change: 0.24752523107735044', 'is_elite: False']\n", + "Id: 62_15 Identity: {'ancestor_count': 56, 'ancestor_ids': ['61_34', '61_20'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_15', 'origin': '61_34~CUW~61_20#MGNP'} Metrics: ['ELUC: -4.055384743526967', 'NSGA-II_crowding_distance: 0.13824980791129843', 'NSGA-II_rank: 1', 'change: 0.0737541668508523', 'is_elite: False']\n", + "Id: 62_17 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '61_80'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_17', 'origin': '2_49~CUW~61_80#MGNP'} Metrics: ['ELUC: -4.0741830695379', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3145321641821872', 'is_elite: False']\n", + "Id: 62_44 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_14', '60_57'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_44', 'origin': '61_14~CUW~60_57#MGNP'} Metrics: ['ELUC: -4.184928092841655', 'NSGA-II_crowding_distance: 0.44224617488608114', 'NSGA-II_rank: 3', 'change: 0.09146451272247105', 'is_elite: False']\n", + "Id: 62_63 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_53', '60_57'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_63', 'origin': '61_53~CUW~60_57#MGNP'} Metrics: ['ELUC: -4.711070077746804', 'NSGA-II_crowding_distance: 0.7807415912643043', 'NSGA-II_rank: 4', 'change: 0.13741899698842688', 'is_elite: False']\n", + "Id: 62_87 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_42', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_87', 'origin': '61_42~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.295733750632025', 'NSGA-II_crowding_distance: 0.11206232410938782', 'NSGA-II_rank: 1', 'change: 0.08054395568349054', 'is_elite: False']\n", + "Id: 61_34 Identity: {'ancestor_count': 55, 'ancestor_ids': ['60_41', '58_65'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_34', 'origin': '60_41~CUW~58_65#MGNP'} Metrics: ['ELUC: -5.490077186028394', 'NSGA-II_crowding_distance: 0.035201759024037715', 'NSGA-II_rank: 1', 'change: 0.08284389411059444', 'is_elite: False']\n", + "Id: 62_50 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_42', '61_97'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_50', 'origin': '61_42~CUW~61_97#MGNP'} Metrics: ['ELUC: -5.627316002637507', 'NSGA-II_crowding_distance: 0.335781449939935', 'NSGA-II_rank: 2', 'change: 0.08801376651017491', 'is_elite: False']\n", + "Id: 62_18 Identity: {'ancestor_count': 55, 'ancestor_ids': ['58_65', '60_33'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_18', 'origin': '58_65~CUW~60_33#MGNP'} Metrics: ['ELUC: -5.6328159483228815', 'NSGA-II_crowding_distance: 0.11948412815513831', 'NSGA-II_rank: 1', 'change: 0.08532698731027809', 'is_elite: False']\n", + "Id: 62_19 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '61_97'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_19', 'origin': '2_49~CUW~61_97#MGNP'} Metrics: ['ELUC: -6.519441974851394', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30551280781608603', 'is_elite: False']\n", + "Id: 62_24 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_24', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.561953945597375', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2683125672407065', 'is_elite: False']\n", + "Id: 62_86 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_87', '61_51'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_86', 'origin': '61_87~CUW~61_51#MGNP'} Metrics: ['ELUC: -6.708058604655743', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2654889145287872', 'is_elite: False']\n", + "Id: 62_75 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_96', '61_99'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_75', 'origin': '61_96~CUW~61_99#MGNP'} Metrics: ['ELUC: -7.124197798873134', 'NSGA-II_crowding_distance: 0.1631837910105581', 'NSGA-II_rank: 1', 'change: 0.09076376478995594', 'is_elite: False']\n", + "Id: 62_55 Identity: {'ancestor_count': 60, 'ancestor_ids': ['1_1', '61_53'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_55', 'origin': '1_1~CUW~61_53#MGNP'} Metrics: ['ELUC: -7.168114268998704', 'NSGA-II_crowding_distance: 0.8550838201697062', 'NSGA-II_rank: 4', 'change: 0.148593042958477', 'is_elite: False']\n", + "Id: 62_43 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_97', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_43', 'origin': '61_97~CUW~61_87#MGNP'} Metrics: ['ELUC: -7.279710787467224', 'NSGA-II_crowding_distance: 0.8915835639057386', 'NSGA-II_rank: 8', 'change: 0.28688283059123787', 'is_elite: False']\n", + "Id: 62_78 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_60', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_78', 'origin': '61_60~CUW~61_87#MGNP'} Metrics: ['ELUC: -7.547281905487785', 'NSGA-II_crowding_distance: 1.285245396405132', 'NSGA-II_rank: 8', 'change: 0.2897061237073825', 'is_elite: False']\n", + "Id: 62_92 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_42', '61_14'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_92', 'origin': '61_42~CUW~61_14#MGNP'} Metrics: ['ELUC: -7.573701522655506', 'NSGA-II_crowding_distance: 0.22297362681252386', 'NSGA-II_rank: 1', 'change: 0.10107996757975622', 'is_elite: True']\n", + "Id: 62_85 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_89', '58_65'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_85', 'origin': '61_89~CUW~58_65#MGNP'} Metrics: ['ELUC: -7.695002019618256', 'NSGA-II_crowding_distance: 0.3029673915186019', 'NSGA-II_rank: 2', 'change: 0.11640858180540556', 'is_elite: False']\n", + "Id: 62_71 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_51', '60_57'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_71', 'origin': '61_51~CUW~60_57#MGNP'} Metrics: ['ELUC: -8.207464057117095', 'NSGA-II_crowding_distance: 1.0134803395402634', 'NSGA-II_rank: 3', 'change: 0.11779569924963924', 'is_elite: False']\n", + "Id: 62_36 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_87', '61_51'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_36', 'origin': '61_87~CUW~61_51#MGNP'} Metrics: ['ELUC: -8.50261749146633', 'NSGA-II_crowding_distance: 0.7751514084976098', 'NSGA-II_rank: 5', 'change: 0.24938179356660614', 'is_elite: False']\n", + "Id: 62_60 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_31', '60_57'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_60', 'origin': '61_31~CUW~60_57#MGNP'} Metrics: ['ELUC: -8.886516601304107', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.31405394578908025', 'is_elite: False']\n", + "Id: 62_73 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_92', '61_51'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_73', 'origin': '61_92~CUW~61_51#MGNP'} Metrics: ['ELUC: -9.280419063439238', 'NSGA-II_crowding_distance: 0.9814284383347727', 'NSGA-II_rank: 4', 'change: 0.2269243312004818', 'is_elite: False']\n", + "Id: 62_59 Identity: {'ancestor_count': 60, 'ancestor_ids': ['1_1', '61_99'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_59', 'origin': '1_1~CUW~61_99#MGNP'} Metrics: ['ELUC: -9.282065803972142', 'NSGA-II_crowding_distance: 0.20719345892724825', 'NSGA-II_rank: 2', 'change: 0.11698372025590686', 'is_elite: False']\n", + "Id: 62_39 Identity: {'ancestor_count': 56, 'ancestor_ids': ['2_49', '61_34'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_39', 'origin': '2_49~CUW~61_34#MGNP'} Metrics: ['ELUC: -9.579507912693455', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2734356239215102', 'is_elite: False']\n", + "Id: 60_33 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_19', '59_98'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_33', 'origin': '59_19~CUW~59_98#MGNP'} Metrics: ['ELUC: -9.70343618658159', 'NSGA-II_crowding_distance: 0.2838395459033621', 'NSGA-II_rank: 1', 'change: 0.11352365564595365', 'is_elite: True']\n", + "Id: 62_74 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_53', '61_14'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_74', 'origin': '61_53~CUW~61_14#MGNP'} Metrics: ['ELUC: -9.730630458049154', 'NSGA-II_crowding_distance: 0.2227229378149596', 'NSGA-II_rank: 2', 'change: 0.14261337524541698', 'is_elite: False']\n", + "Id: 62_57 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_57'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_57', 'origin': '2_49~CUW~60_57#MGNP'} Metrics: ['ELUC: -9.874780431116513', 'NSGA-II_crowding_distance: 1.2251425501386597', 'NSGA-II_rank: 6', 'change: 0.26327714631827254', 'is_elite: False']\n", + "Id: 62_69 Identity: {'ancestor_count': 56, 'ancestor_ids': ['61_34', '61_97'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_69', 'origin': '61_34~CUW~61_97#MGNP'} Metrics: ['ELUC: -10.46431953120932', 'NSGA-II_crowding_distance: 0.21979992179905267', 'NSGA-II_rank: 1', 'change: 0.13671668413434626', 'is_elite: True']\n", + "Id: 62_32 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_42', '61_51'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_32', 'origin': '61_42~CUW~61_51#MGNP'} Metrics: ['ELUC: -10.933222473713448', 'NSGA-II_crowding_distance: 0.21220640331945498', 'NSGA-II_rank: 2', 'change: 0.1525552622422995', 'is_elite: False']\n", + "Id: 62_61 Identity: {'ancestor_count': 60, 'ancestor_ids': ['2_49', '61_51'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_61', 'origin': '2_49~CUW~61_51#MGNP'} Metrics: ['ELUC: -11.239096966852241', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.280974350924924', 'is_elite: False']\n", + "Id: 62_76 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_53', '61_97'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_76', 'origin': '61_53~CUW~61_97#MGNP'} Metrics: ['ELUC: -11.775243150568487', 'NSGA-II_crowding_distance: 0.1620695935289972', 'NSGA-II_rank: 1', 'change: 0.1439478512885385', 'is_elite: False']\n", + "Id: 62_14 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_51', '61_99'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_14', 'origin': '61_51~CUW~61_99#MGNP'} Metrics: ['ELUC: -11.776725743789392', 'NSGA-II_crowding_distance: 0.28629419208255896', 'NSGA-II_rank: 2', 'change: 0.16998678384798235', 'is_elite: False']\n", + "Id: 62_56 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_92', '60_57'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_56', 'origin': '61_92~CUW~60_57#MGNP'} Metrics: ['ELUC: -12.02809029450867', 'NSGA-II_crowding_distance: 0.8687645103630305', 'NSGA-II_rank: 5', 'change: 0.2563217186236629', 'is_elite: False']\n", + "Id: 62_22 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_80', '61_51'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_22', 'origin': '61_80~CUW~61_51#MGNP'} Metrics: ['ELUC: -12.080578901484198', 'NSGA-II_crowding_distance: 0.23485937218148112', 'NSGA-II_rank: 1', 'change: 0.15764621942813206', 'is_elite: True']\n", + "Id: 62_99 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_51', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_99', 'origin': '61_51~CUW~61_87#MGNP'} Metrics: ['ELUC: -12.203497113258843', 'NSGA-II_crowding_distance: 0.4715653966968365', 'NSGA-II_rank: 4', 'change: 0.2542290589672156', 'is_elite: False']\n", + "Id: 62_90 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_20', '61_53'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_90', 'origin': '61_20~CUW~61_53#MGNP'} Metrics: ['ELUC: -12.362803327986018', 'NSGA-II_crowding_distance: 0.24838035144743753', 'NSGA-II_rank: 2', 'change: 0.2078303335484491', 'is_elite: False']\n", + "Id: 62_72 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_92', '61_31'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_72', 'origin': '61_92~CUW~61_31#MGNP'} Metrics: ['ELUC: -12.57425588376069', 'NSGA-II_crowding_distance: 0.4980367856496266', 'NSGA-II_rank: 5', 'change: 0.28010564083312256', 'is_elite: False']\n", + "Id: 62_45 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_31', '60_57'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_45', 'origin': '61_31~CUW~60_57#MGNP'} Metrics: ['ELUC: -12.717209704399622', 'NSGA-II_crowding_distance: 0.237829970400923', 'NSGA-II_rank: 4', 'change: 0.2635455922431935', 'is_elite: False']\n", + "Id: 62_38 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_42', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_38', 'origin': '61_42~CUW~61_87#MGNP'} Metrics: ['ELUC: -12.903043163845652', 'NSGA-II_crowding_distance: 0.3261526291406809', 'NSGA-II_rank: 5', 'change: 0.28017192967138704', 'is_elite: False']\n", + "Id: 62_13 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_53', '61_34'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_13', 'origin': '61_53~CUW~61_34#MGNP'} Metrics: ['ELUC: -13.074580119967976', 'NSGA-II_crowding_distance: 0.9710856018814479', 'NSGA-II_rank: 3', 'change: 0.21584129508074576', 'is_elite: False']\n", + "Id: 62_94 Identity: {'ancestor_count': 60, 'ancestor_ids': ['1_1', '61_53'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_94', 'origin': '1_1~CUW~61_53#MGNP'} Metrics: ['ELUC: -13.293917001422091', 'NSGA-II_crowding_distance: 0.308601435376059', 'NSGA-II_rank: 2', 'change: 0.2141245905114537', 'is_elite: False']\n", + "Id: 62_28 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_53', '61_31'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_28', 'origin': '61_53~CUW~61_31#MGNP'} Metrics: ['ELUC: -13.522890189139188', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2941189258341719', 'is_elite: False']\n", + "Id: 62_12 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_57', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_12', 'origin': '60_57~CUW~61_87#MGNP'} Metrics: ['ELUC: -13.573743005277489', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2777434114093878', 'is_elite: False']\n", + "Id: 62_27 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_87', '1_1'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_27', 'origin': '61_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.604370931407688', 'NSGA-II_crowding_distance: 0.38811470102895507', 'NSGA-II_rank: 3', 'change: 0.2734112879848565', 'is_elite: False']\n", + "Id: 62_46 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_57', '61_92'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_46', 'origin': '60_57~CUW~61_92#MGNP'} Metrics: ['ELUC: -13.636137798487452', 'NSGA-II_crowding_distance: 0.40130555765042186', 'NSGA-II_rank: 2', 'change: 0.2711013814972983', 'is_elite: False']\n", + "Id: 61_51 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_82'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_51', 'origin': '60_16~CUW~60_82#MGNP'} Metrics: ['ELUC: -13.65856940310432', 'NSGA-II_crowding_distance: 0.3304371874022248', 'NSGA-II_rank: 1', 'change: 0.18206402707296074', 'is_elite: True']\n", + "Id: 62_81 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_97', '61_53'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_81', 'origin': '61_97~CUW~61_53#MGNP'} Metrics: ['ELUC: -13.755680587009806', 'NSGA-II_crowding_distance: 0.2324112689317998', 'NSGA-II_rank: 1', 'change: 0.22781432033314214', 'is_elite: True']\n", + "Id: 62_88 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_31', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_88', 'origin': '61_31~CUW~61_87#MGNP'} Metrics: ['ELUC: -14.035177446607737', 'NSGA-II_crowding_distance: 0.3238001093821499', 'NSGA-II_rank: 3', 'change: 0.2920061955990598', 'is_elite: False']\n", + "Id: 61_53 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_53', '60_81'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_53', 'origin': '60_53~CUW~60_81#MGNP'} Metrics: ['ELUC: -14.671480366057644', 'NSGA-II_crowding_distance: 0.0898700922607795', 'NSGA-II_rank: 1', 'change: 0.23422095910340845', 'is_elite: False']\n", + "Id: 62_16 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_53', '61_53'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_16', 'origin': '61_53~CUW~61_53#MGNP'} Metrics: ['ELUC: -14.817124986056676', 'NSGA-II_crowding_distance: 0.1625890231525692', 'NSGA-II_rank: 1', 'change: 0.23661651449753246', 'is_elite: False']\n", + "Id: 62_95 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_97', '61_31'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_95', 'origin': '61_97~CUW~61_31#MGNP'} Metrics: ['ELUC: -15.431252312040412', 'NSGA-II_crowding_distance: 0.2802885447359967', 'NSGA-II_rank: 1', 'change: 0.26984033615316894', 'is_elite: True']\n", + "Id: 61_31 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '2_49'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_31', 'origin': '60_57~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.744869910992922', 'NSGA-II_crowding_distance: 0.3301898338058757', 'NSGA-II_rank: 2', 'change: 0.2854425115582287', 'is_elite: False']\n", + "Id: 62_33 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_31', '60_33'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_33', 'origin': '61_31~CUW~60_33#MGNP'} Metrics: ['ELUC: -16.90607653150904', 'NSGA-II_crowding_distance: 0.1981411485616079', 'NSGA-II_rank: 1', 'change: 0.28479821836672203', 'is_elite: False']\n", + "Id: 62_83 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_87', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_83', 'origin': '61_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.089407507035137', 'NSGA-II_crowding_distance: 0.07731349677611181', 'NSGA-II_rank: 1', 'change: 0.30082183453501554', 'is_elite: False']\n", + "Id: 62_66 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_97', '61_31'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_66', 'origin': '61_97~CUW~61_31#MGNP'} Metrics: ['ELUC: -17.15103588876343', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3048994644191956', 'is_elite: False']\n", + "Id: 62_37 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_87', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_37', 'origin': '61_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.293107269944986', 'NSGA-II_crowding_distance: 0.03625868323159378', 'NSGA-II_rank: 1', 'change: 0.30129881192326136', 'is_elite: False']\n", + "Id: 62_31 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_87', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_31', 'origin': '61_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59353415026058', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302920188584975', 'is_elite: False']\n", + "Id: 62_41 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_87', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_41', 'origin': '61_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59736498105856', 'NSGA-II_crowding_distance: 0.02307601379342427', 'NSGA-II_rank: 1', 'change: 0.3030204226934906', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 61_87 Identity: {'ancestor_count': 58, 'ancestor_ids': ['60_97', '60_97'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_87', 'origin': '60_97~CUW~60_97#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_29 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_31', '61_51'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_29', 'origin': '61_31~CUW~61_51#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_34 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_92', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_34', 'origin': '61_92~CUW~61_87#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_35 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_33'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_35', 'origin': '2_49~CUW~60_33#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_49 Identity: {'ancestor_count': 59, 'ancestor_ids': ['2_49', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_49', 'origin': '2_49~CUW~61_87#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_51 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_31', '61_20'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_51', 'origin': '61_31~CUW~61_20#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_68 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_87', '61_99'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_68', 'origin': '61_87~CUW~61_99#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_80 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_87', '61_87'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_80', 'origin': '61_87~CUW~61_87#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_84 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_53', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_84', 'origin': '61_53~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_89 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '61_31'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_89', 'origin': '2_49~CUW~61_31#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_91 Identity: {'ancestor_count': 59, 'ancestor_ids': ['61_87', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_91', 'origin': '61_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_96 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_96', 'origin': '60_57~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 62_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 62.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 63...:\n", + "PopulationResponse:\n", + " Generation: 63\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/63/20240220-031516\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 63 and asking ESP for generation 64...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 63 data persisted.\n", + "Evaluated candidates:\n", + "Id: 63_25 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_25', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 13.607327527982823', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.292061916421804', 'is_elite: False']\n", + "Id: 63_89 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_89', 'origin': '62_81~CUW~62_100#MGNP'} Metrics: ['ELUC: 11.368946943243007', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2861515016292886', 'is_elite: False']\n", + "Id: 63_87 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '62_95'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_87', 'origin': '62_92~CUW~62_95#MGNP'} Metrics: ['ELUC: 7.588905381839458', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.22026172311416525', 'is_elite: False']\n", + "Id: 63_75 Identity: {'ancestor_count': 54, 'ancestor_ids': ['62_100', '60_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_75', 'origin': '62_100~CUW~60_33#MGNP'} Metrics: ['ELUC: 7.424743268250445', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2515317267493323', 'is_elite: False']\n", + "Id: 63_57 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_57', 'origin': '60_57~CUW~62_100#MGNP'} Metrics: ['ELUC: 3.125838055780165', 'NSGA-II_crowding_distance: 1.5806833984257518', 'NSGA-II_rank: 8', 'change: 0.26022556874245184', 'is_elite: False']\n", + "Id: 63_11 Identity: {'ancestor_count': 61, 'ancestor_ids': ['1_1', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_11', 'origin': '1_1~CUW~62_22#MGNP'} Metrics: ['ELUC: 2.750695529083414', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07651661541600717', 'is_elite: False']\n", + "Id: 63_78 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '60_57'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_78', 'origin': '62_81~CUW~60_57#MGNP'} Metrics: ['ELUC: 1.2609455780730567', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.05610180728332803', 'is_elite: False']\n", + "Id: 63_23 Identity: {'ancestor_count': 56, 'ancestor_ids': ['62_33', '60_57'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_23', 'origin': '62_33~CUW~60_57#MGNP'} Metrics: ['ELUC: 1.1963144180690302', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.28736282038948296', 'is_elite: False']\n", + "Id: 63_32 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_76', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_32', 'origin': '62_76~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.0622038071295061', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09272352839045041', 'is_elite: False']\n", + "Id: 63_53 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_69', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_53', 'origin': '62_69~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.5135020280335066', 'NSGA-II_crowding_distance: 0.15932469810645217', 'NSGA-II_rank: 3', 'change: 0.0770844963309582', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 63_93 Identity: {'ancestor_count': 61, 'ancestor_ids': ['60_57', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_93', 'origin': '60_57~CUW~62_22#MGNP'} Metrics: ['ELUC: -0.29278684195868504', 'NSGA-II_crowding_distance: 0.28787566770040784', 'NSGA-II_rank: 3', 'change: 0.07771625381661967', 'is_elite: False']\n", + "Id: 63_22 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '60_57'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_22', 'origin': '60_57~CUW~60_57#MGNP'} Metrics: ['ELUC: -0.3263836649796108', 'NSGA-II_crowding_distance: 0.20259500297082267', 'NSGA-II_rank: 1', 'change: 0.04710403862932653', 'is_elite: True']\n", + "Id: 63_54 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_75', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_54', 'origin': '62_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6397407786745407', 'NSGA-II_crowding_distance: 0.18435591962613368', 'NSGA-II_rank: 1', 'change: 0.05449134674881952', 'is_elite: False']\n", + "Id: 63_31 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_15', '62_69'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_31', 'origin': '62_15~CUW~62_69#MGNP'} Metrics: ['ELUC: -1.0783340487905393', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11385665895848564', 'is_elite: False']\n", + "Id: 63_14 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_14', 'origin': '62_81~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2946971386592494', 'NSGA-II_crowding_distance: 0.40479282316840043', 'NSGA-II_rank: 2', 'change: 0.07154615544112766', 'is_elite: False']\n", + "Id: 63_71 Identity: {'ancestor_count': 60, 'ancestor_ids': ['62_33', '61_51'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_71', 'origin': '62_33~CUW~61_51#MGNP'} Metrics: ['ELUC: -2.097262417747223', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24481429694446488', 'is_elite: False']\n", + "Id: 63_55 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_69', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_55', 'origin': '62_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.3187174355798787', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28408468372944456', 'is_elite: False']\n", + "Id: 63_20 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_69', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_20', 'origin': '62_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.840776048229961', 'NSGA-II_crowding_distance: 0.24560405622250164', 'NSGA-II_rank: 1', 'change: 0.059441722959838926', 'is_elite: True']\n", + "Id: 63_86 Identity: {'ancestor_count': 56, 'ancestor_ids': ['60_33', '62_98'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_86', 'origin': '60_33~CUW~62_98#MGNP'} Metrics: ['ELUC: -3.551045798470648', 'NSGA-II_crowding_distance: 0.6838155554552597', 'NSGA-II_rank: 4', 'change: 0.11223856618262125', 'is_elite: False']\n", + "Id: 63_39 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '62_18'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_39', 'origin': '62_92~CUW~62_18#MGNP'} Metrics: ['ELUC: -3.757130331848418', 'NSGA-II_crowding_distance: 0.18453030515036795', 'NSGA-II_rank: 1', 'change: 0.07487106228861105', 'is_elite: False']\n", + "Id: 63_96 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_18', '62_69'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_96', 'origin': '62_18~CUW~62_69#MGNP'} Metrics: ['ELUC: -3.9129625649136743', 'NSGA-II_crowding_distance: 0.3834049794985913', 'NSGA-II_rank: 3', 'change: 0.09152845010856124', 'is_elite: False']\n", + "Id: 63_43 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_22', '62_69'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_43', 'origin': '62_22~CUW~62_69#MGNP'} Metrics: ['ELUC: -4.142960676011982', 'NSGA-II_crowding_distance: 0.3887354756894856', 'NSGA-II_rank: 3', 'change: 0.12036025414836542', 'is_elite: False']\n", + "Id: 63_88 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '60_57'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_88', 'origin': '62_92~CUW~60_57#MGNP'} Metrics: ['ELUC: -4.263103278436067', 'NSGA-II_crowding_distance: 0.33352435343666603', 'NSGA-II_rank: 2', 'change: 0.08168524348140119', 'is_elite: False']\n", + "Id: 63_59 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_75', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_59', 'origin': '62_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.874200250305794', 'NSGA-II_crowding_distance: 0.10914917538421781', 'NSGA-II_rank: 1', 'change: 0.0799936182979486', 'is_elite: False']\n", + "Id: 63_74 Identity: {'ancestor_count': 61, 'ancestor_ids': ['58_65', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_74', 'origin': '58_65~CUW~62_22#MGNP'} Metrics: ['ELUC: -4.885216593654819', 'NSGA-II_crowding_distance: 0.2621091931532214', 'NSGA-II_rank: 2', 'change: 0.1053895708417763', 'is_elite: False']\n", + "Id: 63_15 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '62_18'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_15', 'origin': '62_92~CUW~62_18#MGNP'} Metrics: ['ELUC: -5.269883436082447', 'NSGA-II_crowding_distance: 0.07203055423993637', 'NSGA-II_rank: 1', 'change: 0.0817668574047213', 'is_elite: False']\n", + "Id: 63_13 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '62_75'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_13', 'origin': '62_92~CUW~62_75#MGNP'} Metrics: ['ELUC: -5.640980434931692', 'NSGA-II_crowding_distance: 0.19575729102156153', 'NSGA-II_rank: 1', 'change: 0.08847343440697149', 'is_elite: True']\n", + "Id: 63_72 Identity: {'ancestor_count': 56, 'ancestor_ids': ['62_98', '62_95'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_72', 'origin': '62_98~CUW~62_95#MGNP'} Metrics: ['ELUC: -6.627008638929582', 'NSGA-II_crowding_distance: 1.1242787893760846', 'NSGA-II_rank: 6', 'change: 0.22813598941761173', 'is_elite: False']\n", + "Id: 63_85 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_85', 'origin': '60_57~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.854016166005561', 'NSGA-II_crowding_distance: 1.281208707954025', 'NSGA-II_rank: 8', 'change: 0.26589918050252287', 'is_elite: False']\n", + "Id: 63_42 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_22', '62_16'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_42', 'origin': '62_22~CUW~62_16#MGNP'} Metrics: ['ELUC: -6.977331750681167', 'NSGA-II_crowding_distance: 0.1975614848690894', 'NSGA-II_rank: 2', 'change: 0.1097096399364579', 'is_elite: False']\n", + "Id: 63_97 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_16', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_97', 'origin': '62_16~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.122573662333196', 'NSGA-II_crowding_distance: 1.1176204448883853', 'NSGA-II_rank: 5', 'change: 0.13083596201786546', 'is_elite: False']\n", + "Id: 63_35 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_22', '62_92'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_35', 'origin': '62_22~CUW~62_92#MGNP'} Metrics: ['ELUC: -7.2167705393393815', 'NSGA-II_crowding_distance: 0.5577842282990662', 'NSGA-II_rank: 4', 'change: 0.13064275100838404', 'is_elite: False']\n", + "Id: 63_79 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_69', '60_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_79', 'origin': '62_69~CUW~60_33#MGNP'} Metrics: ['ELUC: -7.420672071933445', 'NSGA-II_crowding_distance: 0.18229850434980738', 'NSGA-II_rank: 2', 'change: 0.12000878922064029', 'is_elite: False']\n", + "Id: 63_94 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_94', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.463410118959486', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2801363959958455', 'is_elite: False']\n", + "Id: 62_92 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_42', '61_14'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_92', 'origin': '61_42~CUW~61_14#MGNP'} Metrics: ['ELUC: -7.573701522655506', 'NSGA-II_crowding_distance: 0.2366493672145602', 'NSGA-II_rank: 1', 'change: 0.10107996757975622', 'is_elite: True']\n", + "Id: 63_58 Identity: {'ancestor_count': 56, 'ancestor_ids': ['1_1', '62_95'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_58', 'origin': '1_1~CUW~62_95#MGNP'} Metrics: ['ELUC: -7.640213849197594', 'NSGA-II_crowding_distance: 0.9221376335223016', 'NSGA-II_rank: 5', 'change: 0.2092035356791537', 'is_elite: False']\n", + "Id: 63_91 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_91', 'origin': '62_81~CUW~62_22#MGNP'} Metrics: ['ELUC: -7.726146953295097', 'NSGA-II_crowding_distance: 0.5337902550196747', 'NSGA-II_rank: 4', 'change: 0.174543765871289', 'is_elite: False']\n", + "Id: 63_46 Identity: {'ancestor_count': 54, 'ancestor_ids': ['62_100', '60_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_46', 'origin': '62_100~CUW~60_33#MGNP'} Metrics: ['ELUC: -8.191188384408864', 'NSGA-II_crowding_distance: 0.44736873238518693', 'NSGA-II_rank: 6', 'change: 0.24365505368038323', 'is_elite: False']\n", + "Id: 63_84 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_33', '62_16'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_84', 'origin': '62_33~CUW~62_16#MGNP'} Metrics: ['ELUC: -8.212830673228089', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.25413945195230037', 'is_elite: False']\n", + "Id: 63_67 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_16', '60_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_67', 'origin': '62_16~CUW~60_33#MGNP'} Metrics: ['ELUC: -8.24849498732997', 'NSGA-II_crowding_distance: 0.4786704739976946', 'NSGA-II_rank: 3', 'change: 0.1298230730318628', 'is_elite: False']\n", + "Id: 63_81 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '62_92'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_81', 'origin': '62_81~CUW~62_92#MGNP'} Metrics: ['ELUC: -8.406998746330343', 'NSGA-II_crowding_distance: 0.16283368123146993', 'NSGA-II_rank: 1', 'change: 0.11214414856189624', 'is_elite: False']\n", + "Id: 63_69 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_95', '62_75'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_69', 'origin': '62_95~CUW~62_75#MGNP'} Metrics: ['ELUC: -8.869403618183405', 'NSGA-II_crowding_distance: 0.4874339520076061', 'NSGA-II_rank: 4', 'change: 0.2187808395467593', 'is_elite: False']\n", + "Id: 63_28 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_33', '60_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_28', 'origin': '60_33~CUW~60_33#MGNP'} Metrics: ['ELUC: -8.983215864291019', 'NSGA-II_crowding_distance: 0.20210138246114567', 'NSGA-II_rank: 2', 'change: 0.12763177727241526', 'is_elite: False']\n", + "Id: 63_30 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_33', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_30', 'origin': '60_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 63_73 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '62_92'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_73', 'origin': '62_81~CUW~62_92#MGNP'} Metrics: ['ELUC: -9.431451420217309', 'NSGA-II_crowding_distance: 0.15966805813684004', 'NSGA-II_rank: 2', 'change: 0.142707056546076', 'is_elite: False']\n", + "Id: 63_47 Identity: {'ancestor_count': 56, 'ancestor_ids': ['60_33', '62_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_47', 'origin': '60_33~CUW~62_33#MGNP'} Metrics: ['ELUC: -9.61265491413644', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2712270183078047', 'is_elite: False']\n", + "Id: 60_33 Identity: {'ancestor_count': 53, 'ancestor_ids': ['59_19', '59_98'], 'birth_generation': 60, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '60_33', 'origin': '59_19~CUW~59_98#MGNP'} Metrics: ['ELUC: -9.70343618658159', 'NSGA-II_crowding_distance: 0.13748529761085046', 'NSGA-II_rank: 1', 'change: 0.11352365564595365', 'is_elite: False']\n", + "Id: 63_62 Identity: {'ancestor_count': 57, 'ancestor_ids': ['60_33', '62_69'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_62', 'origin': '60_33~CUW~62_69#MGNP'} Metrics: ['ELUC: -9.805560921007386', 'NSGA-II_crowding_distance: 0.12100586467189213', 'NSGA-II_rank: 1', 'change: 0.12943266632673092', 'is_elite: False']\n", + "Id: 63_27 Identity: {'ancestor_count': 61, 'ancestor_ids': ['60_57', '62_16'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_27', 'origin': '60_57~CUW~62_16#MGNP'} Metrics: ['ELUC: -10.165800480721835', 'NSGA-II_crowding_distance: 0.7119920648617228', 'NSGA-II_rank: 3', 'change: 0.15968301405638383', 'is_elite: False']\n", + "Id: 63_48 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_51', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_48', 'origin': '61_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.206733840924025', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2864731362123559', 'is_elite: False']\n", + "Id: 63_17 Identity: {'ancestor_count': 60, 'ancestor_ids': ['62_69', '61_51'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_17', 'origin': '62_69~CUW~61_51#MGNP'} Metrics: ['ELUC: -10.330617529177966', 'NSGA-II_crowding_distance: 0.24998838220239478', 'NSGA-II_rank: 2', 'change: 0.14876803674509842', 'is_elite: False']\n", + "Id: 63_65 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_33', '62_76'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_65', 'origin': '62_33~CUW~62_76#MGNP'} Metrics: ['ELUC: -10.376558295724573', 'NSGA-II_crowding_distance: 0.4401640702537555', 'NSGA-II_rank: 6', 'change: 0.24567155946968558', 'is_elite: False']\n", + "Id: 62_69 Identity: {'ancestor_count': 56, 'ancestor_ids': ['61_34', '61_97'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_69', 'origin': '61_34~CUW~61_97#MGNP'} Metrics: ['ELUC: -10.46431953120932', 'NSGA-II_crowding_distance: 0.1847548868037321', 'NSGA-II_rank: 1', 'change: 0.13671668413434626', 'is_elite: False']\n", + "Id: 63_70 Identity: {'ancestor_count': 56, 'ancestor_ids': ['62_95', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_70', 'origin': '62_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.762341326989977', 'NSGA-II_crowding_distance: 0.39887906523962324', 'NSGA-II_rank: 5', 'change: 0.2327568515163921', 'is_elite: False']\n", + "Id: 63_100 Identity: {'ancestor_count': 56, 'ancestor_ids': ['58_65', '62_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_100', 'origin': '58_65~CUW~62_33#MGNP'} Metrics: ['ELUC: -10.779722530322141', 'NSGA-II_crowding_distance: 0.2606533104644646', 'NSGA-II_rank: 5', 'change: 0.2327816118254613', 'is_elite: False']\n", + "Id: 63_45 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_45', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.839606523481295', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2695157645883106', 'is_elite: False']\n", + "Id: 63_16 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_16', '62_95'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_16', 'origin': '62_16~CUW~62_95#MGNP'} Metrics: ['ELUC: -10.88311864365485', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2648745121201614', 'is_elite: False']\n", + "Id: 63_41 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_95', '62_16'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_41', 'origin': '62_95~CUW~62_16#MGNP'} Metrics: ['ELUC: -10.968863313447262', 'NSGA-II_crowding_distance: 0.7384274135040226', 'NSGA-II_rank: 6', 'change: 0.2638726426858213', 'is_elite: False']\n", + "Id: 63_77 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '62_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_77', 'origin': '62_81~CUW~62_33#MGNP'} Metrics: ['ELUC: -11.265560255986305', 'NSGA-II_crowding_distance: 0.40277781967488546', 'NSGA-II_rank: 4', 'change: 0.23031857615223666', 'is_elite: False']\n", + "Id: 63_49 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_51', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_49', 'origin': '61_51~CUW~62_100#MGNP'} Metrics: ['ELUC: -11.656751778290872', 'NSGA-II_crowding_distance: 0.48350048987199135', 'NSGA-II_rank: 5', 'change: 0.26332735435104726', 'is_elite: False']\n", + "Id: 63_29 Identity: {'ancestor_count': 60, 'ancestor_ids': ['1_1', '61_51'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_29', 'origin': '1_1~CUW~61_51#MGNP'} Metrics: ['ELUC: -11.808151453531051', 'NSGA-II_crowding_distance: 0.1620695935289972', 'NSGA-II_rank: 1', 'change: 0.15057482869950703', 'is_elite: False']\n", + "Id: 62_22 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_80', '61_51'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_22', 'origin': '61_80~CUW~61_51#MGNP'} Metrics: ['ELUC: -12.080578901484198', 'NSGA-II_crowding_distance: 0.07095578442031836', 'NSGA-II_rank: 1', 'change: 0.15764621942813206', 'is_elite: False']\n", + "Id: 63_24 Identity: {'ancestor_count': 61, 'ancestor_ids': ['61_51', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_24', 'origin': '61_51~CUW~62_22#MGNP'} Metrics: ['ELUC: -12.454036370351679', 'NSGA-II_crowding_distance: 0.42427342399535384', 'NSGA-II_rank: 2', 'change: 0.16367246101378805', 'is_elite: False']\n", + "Id: 63_26 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_16', '62_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_26', 'origin': '62_16~CUW~62_33#MGNP'} Metrics: ['ELUC: -12.455498587003346', 'NSGA-II_crowding_distance: 0.2905528885481389', 'NSGA-II_rank: 4', 'change: 0.25681954961681247', 'is_elite: False']\n", + "Id: 63_90 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_51', '62_15'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_90', 'origin': '61_51~CUW~62_15#MGNP'} Metrics: ['ELUC: -12.504216007911067', 'NSGA-II_crowding_distance: 0.06793292372658843', 'NSGA-II_rank: 1', 'change: 0.15993402348383104', 'is_elite: False']\n", + "Id: 63_92 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_51', '62_69'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_92', 'origin': '61_51~CUW~62_69#MGNP'} Metrics: ['ELUC: -12.758865007891503', 'NSGA-II_crowding_distance: 0.13982189161764091', 'NSGA-II_rank: 1', 'change: 0.16640516568863642', 'is_elite: False']\n", + "Id: 63_44 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_33', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_44', 'origin': '60_33~CUW~62_100#MGNP'} Metrics: ['ELUC: -12.844633848491819', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2867173213532303', 'is_elite: False']\n", + "Id: 63_66 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '60_57'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_66', 'origin': '62_81~CUW~60_57#MGNP'} Metrics: ['ELUC: -13.173490411566243', 'NSGA-II_crowding_distance: 0.33887766247837386', 'NSGA-II_rank: 2', 'change: 0.21472749209904998', 'is_elite: False']\n", + "Id: 63_38 Identity: {'ancestor_count': 60, 'ancestor_ids': ['2_49', '61_51'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_38', 'origin': '2_49~CUW~61_51#MGNP'} Metrics: ['ELUC: -13.460118703081651', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27610555668140174', 'is_elite: False']\n", + "Id: 61_51 Identity: {'ancestor_count': 59, 'ancestor_ids': ['60_16', '60_82'], 'birth_generation': 61, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '61_51', 'origin': '60_16~CUW~60_82#MGNP'} Metrics: ['ELUC: -13.65856940310432', 'NSGA-II_crowding_distance: 0.14477686900959288', 'NSGA-II_rank: 1', 'change: 0.18206402707296074', 'is_elite: False']\n", + "Id: 63_56 Identity: {'ancestor_count': 61, 'ancestor_ids': ['61_51', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_56', 'origin': '61_51~CUW~62_22#MGNP'} Metrics: ['ELUC: -13.726827259252666', 'NSGA-II_crowding_distance: 0.15309118264340504', 'NSGA-II_rank: 1', 'change: 0.19317673925733211', 'is_elite: False']\n", + "Id: 63_83 Identity: {'ancestor_count': 56, 'ancestor_ids': ['62_95', '62_95'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_83', 'origin': '62_95~CUW~62_95#MGNP'} Metrics: ['ELUC: -13.75263483264982', 'NSGA-II_crowding_distance: 0.3796163698501801', 'NSGA-II_rank: 4', 'change: 0.25897367931083354', 'is_elite: False']\n", + "Id: 62_81 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_97', '61_53'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_81', 'origin': '61_97~CUW~61_53#MGNP'} Metrics: ['ELUC: -13.755680587009806', 'NSGA-II_crowding_distance: 0.6919766915478887', 'NSGA-II_rank: 3', 'change: 0.22781432033314214', 'is_elite: False']\n", + "Id: 63_99 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_33', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_99', 'origin': '60_33~CUW~62_100#MGNP'} Metrics: ['ELUC: -13.780990244009962', 'NSGA-II_crowding_distance: 0.27527010609919905', 'NSGA-II_rank: 3', 'change: 0.2748014473159716', 'is_elite: False']\n", + "Id: 63_98 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '62_81'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_98', 'origin': '62_81~CUW~62_81#MGNP'} Metrics: ['ELUC: -13.980367403421107', 'NSGA-II_crowding_distance: 0.29645239966171555', 'NSGA-II_rank: 2', 'change: 0.22624288536200127', 'is_elite: False']\n", + "Id: 63_36 Identity: {'ancestor_count': 61, 'ancestor_ids': ['61_51', '62_81'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_36', 'origin': '61_51~CUW~62_81#MGNP'} Metrics: ['ELUC: -14.475667047678117', 'NSGA-II_crowding_distance: 0.3161227881585331', 'NSGA-II_rank: 1', 'change: 0.2138766254090932', 'is_elite: True']\n", + "Id: 63_52 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_52', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -14.795650033167309', 'NSGA-II_crowding_distance: 0.17583033758313718', 'NSGA-II_rank: 3', 'change: 0.27816566979574814', 'is_elite: False']\n", + "Id: 63_61 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_16', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_61', 'origin': '62_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.859797405756519', 'NSGA-II_crowding_distance: 0.23094341963770512', 'NSGA-II_rank: 2', 'change: 0.2648013981240965', 'is_elite: False']\n", + "Id: 63_68 Identity: {'ancestor_count': 60, 'ancestor_ids': ['62_33', '61_51'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_68', 'origin': '62_33~CUW~61_51#MGNP'} Metrics: ['ELUC: -15.052816633425467', 'NSGA-II_crowding_distance: 0.05166128870701091', 'NSGA-II_rank: 2', 'change: 0.26845577880865296', 'is_elite: False']\n", + "Id: 62_95 Identity: {'ancestor_count': 55, 'ancestor_ids': ['61_97', '61_31'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_95', 'origin': '61_97~CUW~61_31#MGNP'} Metrics: ['ELUC: -15.431252312040412', 'NSGA-II_crowding_distance: 0.12597063963321836', 'NSGA-II_rank: 2', 'change: 0.26984033615316894', 'is_elite: False']\n", + "Id: 63_37 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_95', '62_92'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_37', 'origin': '62_95~CUW~62_92#MGNP'} Metrics: ['ELUC: -15.601256990238612', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2955201527991957', 'is_elite: False']\n", + "Id: 63_19 Identity: {'ancestor_count': 61, 'ancestor_ids': ['2_49', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_19', 'origin': '2_49~CUW~62_22#MGNP'} Metrics: ['ELUC: -15.641817568615762', 'NSGA-II_crowding_distance: 0.1431486649171129', 'NSGA-II_rank: 3', 'change: 0.29326932652506427', 'is_elite: False']\n", + "Id: 63_18 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_18', 'origin': '62_81~CUW~62_22#MGNP'} Metrics: ['ELUC: -15.774535594770928', 'NSGA-II_crowding_distance: 0.371115043560385', 'NSGA-II_rank: 1', 'change: 0.25275049275762856', 'is_elite: True']\n", + "Id: 63_95 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_95', '62_81'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_95', 'origin': '62_95~CUW~62_81#MGNP'} Metrics: ['ELUC: -15.873481054927547', 'NSGA-II_crowding_distance: 0.1638679467687016', 'NSGA-II_rank: 2', 'change: 0.288350698010658', 'is_elite: False']\n", + "Id: 63_33 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_75', '62_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_33', 'origin': '62_75~CUW~62_33#MGNP'} Metrics: ['ELUC: -15.939108025307391', 'NSGA-II_crowding_distance: 0.1107928192662361', 'NSGA-II_rank: 3', 'change: 0.29745266650186236', 'is_elite: False']\n", + "Id: 63_51 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_51', 'origin': '62_81~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.77527617063775', 'NSGA-II_crowding_distance: 0.11899912160419424', 'NSGA-II_rank: 2', 'change: 0.2920481972055855', 'is_elite: False']\n", + "Id: 63_82 Identity: {'ancestor_count': 56, 'ancestor_ids': ['62_33', '62_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_82', 'origin': '62_33~CUW~62_33#MGNP'} Metrics: ['ELUC: -16.828352259436347', 'NSGA-II_crowding_distance: 0.22855355538913252', 'NSGA-II_rank: 1', 'change: 0.2846832908105413', 'is_elite: True']\n", + "Id: 63_63 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_22', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_63', 'origin': '62_22~CUW~62_100#MGNP'} Metrics: ['ELUC: -17.00958466688089', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30267168228551034', 'is_elite: False']\n", + "Id: 63_34 Identity: {'ancestor_count': 61, 'ancestor_ids': ['2_49', '62_81'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_34', 'origin': '2_49~CUW~62_81#MGNP'} Metrics: ['ELUC: -17.143776428610217', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3005689306966215', 'is_elite: False']\n", + "Id: 63_12 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_16', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_12', 'origin': '62_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.29267004564011', 'NSGA-II_crowding_distance: 0.10458787148795784', 'NSGA-II_rank: 1', 'change: 0.2951825707549477', 'is_elite: False']\n", + "Id: 63_76 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_22', '62_95'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_76', 'origin': '62_22~CUW~62_95#MGNP'} Metrics: ['ELUC: -17.591408267004194', 'NSGA-II_crowding_distance: 0.043599198684690005', 'NSGA-II_rank: 1', 'change: 0.30294068525848505', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 62_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 63_21 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_21', 'origin': '2_49~CUW~62_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 63_40 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_40', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 63_50 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_100', '62_92'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_50', 'origin': '62_100~CUW~62_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 63_60 Identity: {'ancestor_count': 54, 'ancestor_ids': ['2_49', '60_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_60', 'origin': '2_49~CUW~60_33#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 63_64 Identity: {'ancestor_count': 3, 'ancestor_ids': ['62_100', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_64', 'origin': '62_100~CUW~62_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 63_80 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_80', 'origin': '2_49~CUW~62_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 63.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 64...:\n", + "PopulationResponse:\n", + " Generation: 64\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/64/20240220-032234\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 64 and asking ESP for generation 65...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 64 data persisted.\n", + "Evaluated candidates:\n", + "Id: 64_55 Identity: {'ancestor_count': 62, 'ancestor_ids': ['2_49', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_55', 'origin': '2_49~CUW~63_18#MGNP'} Metrics: ['ELUC: 18.92526962517788', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.30224975322248854', 'is_elite: False']\n", + "Id: 64_47 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_20', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_47', 'origin': '63_20~CUW~63_80#MGNP'} Metrics: ['ELUC: 11.767285385529755', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2692230928319224', 'is_elite: False']\n", + "Id: 64_79 Identity: {'ancestor_count': 57, 'ancestor_ids': ['1_1', '63_82'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_79', 'origin': '1_1~CUW~63_82#MGNP'} Metrics: ['ELUC: 7.149818157451941', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.20163861050777473', 'is_elite: False']\n", + "Id: 64_46 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_80', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_46', 'origin': '63_80~CUW~63_13#MGNP'} Metrics: ['ELUC: 1.5850824115759368', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.27102923428333237', 'is_elite: False']\n", + "Id: 64_86 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_39', '1_1'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_86', 'origin': '63_39~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.2172950236209459', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06723399910962274', 'is_elite: False']\n", + "Id: 64_39 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_20', '2_49'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_39', 'origin': '63_20~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.1405983700066649', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3346055586446206', 'is_elite: False']\n", + "Id: 64_62 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_54', '63_22'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_62', 'origin': '63_54~CUW~63_22#MGNP'} Metrics: ['ELUC: 0.990200257808984', 'NSGA-II_crowding_distance: 0.14463337921734828', 'NSGA-II_rank: 5', 'change: 0.07177946676383255', 'is_elite: False']\n", + "Id: 64_22 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_20', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_22', 'origin': '63_20~CUW~63_18#MGNP'} Metrics: ['ELUC: 0.5053512557078562', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.09791601650016017', 'is_elite: False']\n", + "Id: 64_83 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_20', '1_1'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_83', 'origin': '63_20~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.4473288229008623', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.050232450029733686', 'is_elite: False']\n", + "Id: 64_87 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_29', '63_39'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_87', 'origin': '63_29~CUW~63_39#MGNP'} Metrics: ['ELUC: 0.24865464094394427', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.07433184479032824', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 63_22 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '60_57'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_22', 'origin': '60_57~CUW~60_57#MGNP'} Metrics: ['ELUC: -0.3263836649796108', 'NSGA-II_crowding_distance: 0.210722823946786', 'NSGA-II_rank: 1', 'change: 0.04710403862932653', 'is_elite: True']\n", + "Id: 64_69 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_20', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_69', 'origin': '63_20~CUW~63_18#MGNP'} Metrics: ['ELUC: -0.4500139203820467', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.0944048344797874', 'is_elite: False']\n", + "Id: 64_41 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_22', '63_54'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_41', 'origin': '63_22~CUW~63_54#MGNP'} Metrics: ['ELUC: -0.6714842403233812', 'NSGA-II_crowding_distance: 0.14355661036930067', 'NSGA-II_rank: 5', 'change: 0.07249286792756514', 'is_elite: False']\n", + "Id: 64_67 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_13', '1_1'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_67', 'origin': '63_13~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7832529278165445', 'NSGA-II_crowding_distance: 0.18435591962613368', 'NSGA-II_rank: 1', 'change: 0.054481061997689935', 'is_elite: True']\n", + "Id: 64_96 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '63_54'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_96', 'origin': '62_92~CUW~63_54#MGNP'} Metrics: ['ELUC: -0.9991158275525609', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.0659398806851983', 'is_elite: False']\n", + "Id: 64_73 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '60_33'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_73', 'origin': '62_92~CUW~60_33#MGNP'} Metrics: ['ELUC: -1.031496176637769', 'NSGA-II_crowding_distance: 0.17972301221311654', 'NSGA-II_rank: 5', 'change: 0.07492819135740578', 'is_elite: False']\n", + "Id: 64_57 Identity: {'ancestor_count': 61, 'ancestor_ids': ['63_82', '63_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_57', 'origin': '63_82~CUW~63_92#MGNP'} Metrics: ['ELUC: -1.4334158176018155', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.17736351403236947', 'is_elite: False']\n", + "Id: 64_72 Identity: {'ancestor_count': 62, 'ancestor_ids': ['1_1', '63_54'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_72', 'origin': '1_1~CUW~63_54#MGNP'} Metrics: ['ELUC: -1.9615648027869987', 'NSGA-II_crowding_distance: 0.22685920807458435', 'NSGA-II_rank: 4', 'change: 0.06642906053608562', 'is_elite: False']\n", + "Id: 64_50 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_54', '62_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_50', 'origin': '63_54~CUW~62_92#MGNP'} Metrics: ['ELUC: -2.1367969073172057', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0655201830899306', 'is_elite: False']\n", + "Id: 64_35 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_29', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_35', 'origin': '63_29~CUW~63_13#MGNP'} Metrics: ['ELUC: -2.216114711398861', 'NSGA-II_crowding_distance: 1.3746414537924045', 'NSGA-II_rank: 6', 'change: 0.08551347238823882', 'is_elite: False']\n", + "Id: 64_77 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_22', '63_81'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_77', 'origin': '63_22~CUW~63_81#MGNP'} Metrics: ['ELUC: -2.5351983577402244', 'NSGA-II_crowding_distance: 0.29630521716937175', 'NSGA-II_rank: 2', 'change: 0.06547397938633365', 'is_elite: False']\n", + "Id: 64_28 Identity: {'ancestor_count': 58, 'ancestor_ids': ['62_69', '63_20'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_28', 'origin': '62_69~CUW~63_20#MGNP'} Metrics: ['ELUC: -2.8229212049873325', 'NSGA-II_crowding_distance: 0.15647689155805158', 'NSGA-II_rank: 5', 'change: 0.08178341023179013', 'is_elite: False']\n", + "Id: 63_20 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_69', '1_1'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_20', 'origin': '62_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.840776048229961', 'NSGA-II_crowding_distance: 0.1422163481798888', 'NSGA-II_rank: 1', 'change: 0.059441722959838926', 'is_elite: False']\n", + "Id: 64_42 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_81', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_42', 'origin': '63_81~CUW~63_13#MGNP'} Metrics: ['ELUC: -2.9403893416767084', 'NSGA-II_crowding_distance: 0.23962613178628256', 'NSGA-II_rank: 5', 'change: 0.08251357755824293', 'is_elite: False']\n", + "Id: 64_45 Identity: {'ancestor_count': 55, 'ancestor_ids': ['63_22', '1_1'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_45', 'origin': '63_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.94890408946579', 'NSGA-II_crowding_distance: 0.06319729316985952', 'NSGA-II_rank: 1', 'change: 0.060163483316822634', 'is_elite: False']\n", + "Id: 64_43 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_56', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_43', 'origin': '63_56~CUW~63_13#MGNP'} Metrics: ['ELUC: -3.0221908212826007', 'NSGA-II_crowding_distance: 0.49576769516681707', 'NSGA-II_rank: 5', 'change: 0.131781540514574', 'is_elite: False']\n", + "Id: 64_44 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_22', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_44', 'origin': '63_22~CUW~63_13#MGNP'} Metrics: ['ELUC: -3.1337310056407444', 'NSGA-II_crowding_distance: 0.1467629410135879', 'NSGA-II_rank: 3', 'change: 0.07496770469409944', 'is_elite: False']\n", + "Id: 64_64 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '63_22'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_64', 'origin': '62_92~CUW~63_22#MGNP'} Metrics: ['ELUC: -3.463223234710912', 'NSGA-II_crowding_distance: 0.3340857100570702', 'NSGA-II_rank: 4', 'change: 0.08094950736057069', 'is_elite: False']\n", + "Id: 64_30 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_20', '62_69'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_30', 'origin': '63_20~CUW~62_69#MGNP'} Metrics: ['ELUC: -3.536163126453668', 'NSGA-II_crowding_distance: 0.2028244478563795', 'NSGA-II_rank: 3', 'change: 0.07829807211459858', 'is_elite: False']\n", + "Id: 64_33 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '63_22'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_33', 'origin': '62_92~CUW~63_22#MGNP'} Metrics: ['ELUC: -3.612078568381876', 'NSGA-II_crowding_distance: 0.1596220031783317', 'NSGA-II_rank: 2', 'change: 0.06780954490912787', 'is_elite: False']\n", + "Id: 64_21 Identity: {'ancestor_count': 58, 'ancestor_ids': ['1_1', '63_20'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_21', 'origin': '1_1~CUW~63_20#MGNP'} Metrics: ['ELUC: -3.771454686000882', 'NSGA-II_crowding_distance: 0.17167658040628792', 'NSGA-II_rank: 1', 'change: 0.06250448356221107', 'is_elite: False']\n", + "Id: 64_59 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_59', 'origin': '62_92~CUW~63_18#MGNP'} Metrics: ['ELUC: -4.107547882776468', 'NSGA-II_crowding_distance: 0.170270642386518', 'NSGA-II_rank: 2', 'change: 0.08361040692296301', 'is_elite: False']\n", + "Id: 64_98 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_13', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_98', 'origin': '63_13~CUW~63_13#MGNP'} Metrics: ['ELUC: -4.640539937509917', 'NSGA-II_crowding_distance: 0.16919190471540999', 'NSGA-II_rank: 1', 'change: 0.08268036734071334', 'is_elite: False']\n", + "Id: 64_68 Identity: {'ancestor_count': 55, 'ancestor_ids': ['2_49', '63_22'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_68', 'origin': '2_49~CUW~63_22#MGNP'} Metrics: ['ELUC: -4.895910098899661', 'NSGA-II_crowding_distance: 1.5628219278055921', 'NSGA-II_rank: 6', 'change: 0.26740387444688063', 'is_elite: False']\n", + "Id: 64_95 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_20', '63_62'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_95', 'origin': '63_20~CUW~63_62#MGNP'} Metrics: ['ELUC: -5.174226877103012', 'NSGA-II_crowding_distance: 0.516866416452651', 'NSGA-II_rank: 4', 'change: 0.09518718889650567', 'is_elite: False']\n", + "Id: 64_81 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '1_1'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_81', 'origin': '62_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.218325537208281', 'NSGA-II_crowding_distance: 0.2974010332056175', 'NSGA-II_rank: 3', 'change: 0.09024610700399613', 'is_elite: False']\n", + "Id: 64_48 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '62_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_48', 'origin': '63_36~CUW~62_92#MGNP'} Metrics: ['ELUC: -5.223744902148384', 'NSGA-II_crowding_distance: 1.2189766343801265', 'NSGA-II_rank: 5', 'change: 0.15959145497689045', 'is_elite: False']\n", + "Id: 64_36 Identity: {'ancestor_count': 61, 'ancestor_ids': ['63_92', '1_1'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_36', 'origin': '63_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.326631935688078', 'NSGA-II_crowding_distance: 0.1878296609630019', 'NSGA-II_rank: 3', 'change: 0.12070273822201234', 'is_elite: False']\n", + "Id: 64_18 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_18', 'origin': '62_92~CUW~63_13#MGNP'} Metrics: ['ELUC: -5.509275630252826', 'NSGA-II_crowding_distance: 0.2990418718930879', 'NSGA-II_rank: 2', 'change: 0.08405337214196133', 'is_elite: False']\n", + "Id: 64_13 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_54', '62_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_13', 'origin': '63_54~CUW~62_92#MGNP'} Metrics: ['ELUC: -5.532109652470936', 'NSGA-II_crowding_distance: 0.07631552061104269', 'NSGA-II_rank: 1', 'change: 0.08310872002333945', 'is_elite: False']\n", + "Id: 63_13 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '62_75'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_13', 'origin': '62_92~CUW~62_75#MGNP'} Metrics: ['ELUC: -5.640980434931692', 'NSGA-II_crowding_distance: 0.03144363981973673', 'NSGA-II_rank: 1', 'change: 0.08847343440697149', 'is_elite: False']\n", + "Id: 64_12 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_13', '62_69'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_12', 'origin': '63_13~CUW~62_69#MGNP'} Metrics: ['ELUC: -5.687769137016493', 'NSGA-II_crowding_distance: 0.08763263773605512', 'NSGA-II_rank: 1', 'change: 0.0898492119823284', 'is_elite: False']\n", + "Id: 64_66 Identity: {'ancestor_count': 61, 'ancestor_ids': ['63_92', '62_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_66', 'origin': '63_92~CUW~62_92#MGNP'} Metrics: ['ELUC: -5.876118258131427', 'NSGA-II_crowding_distance: 0.246750129879159', 'NSGA-II_rank: 3', 'change: 0.12449996413184383', 'is_elite: False']\n", + "Id: 64_93 Identity: {'ancestor_count': 61, 'ancestor_ids': ['63_80', '62_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_93', 'origin': '63_80~CUW~62_92#MGNP'} Metrics: ['ELUC: -6.040756036169356', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2813001834537354', 'is_elite: False']\n", + "Id: 64_61 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_18', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_61', 'origin': '63_18~CUW~63_13#MGNP'} Metrics: ['ELUC: -6.939988243516378', 'NSGA-II_crowding_distance: 1.2124614296245748', 'NSGA-II_rank: 4', 'change: 0.14932468444685174', 'is_elite: False']\n", + "Id: 64_97 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '62_69'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_97', 'origin': '62_92~CUW~62_69#MGNP'} Metrics: ['ELUC: -7.0148107802498565', 'NSGA-II_crowding_distance: 0.14490227414039636', 'NSGA-II_rank: 1', 'change: 0.09130673622873567', 'is_elite: False']\n", + "Id: 64_70 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_81', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_70', 'origin': '63_81~CUW~63_18#MGNP'} Metrics: ['ELUC: -7.2970939838108775', 'NSGA-II_crowding_distance: 0.2406086970952992', 'NSGA-II_rank: 2', 'change: 0.1141483350965233', 'is_elite: False']\n", + "Id: 64_84 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_13', '63_56'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_84', 'origin': '63_13~CUW~63_56#MGNP'} Metrics: ['ELUC: -7.570703692474281', 'NSGA-II_crowding_distance: 0.12737343718477284', 'NSGA-II_rank: 2', 'change: 0.11574558200357589', 'is_elite: False']\n", + "Id: 62_92 Identity: {'ancestor_count': 60, 'ancestor_ids': ['61_42', '61_14'], 'birth_generation': 62, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '62_92', 'origin': '61_42~CUW~61_14#MGNP'} Metrics: ['ELUC: -7.573701522655506', 'NSGA-II_crowding_distance: 0.09824068680896635', 'NSGA-II_rank: 1', 'change: 0.10107996757975622', 'is_elite: False']\n", + "Id: 64_75 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_39', '62_69'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_75', 'origin': '63_39~CUW~62_69#MGNP'} Metrics: ['ELUC: -8.14676094999574', 'NSGA-II_crowding_distance: 0.08169821605978492', 'NSGA-II_rank: 1', 'change: 0.101410024605982', 'is_elite: False']\n", + "Id: 64_16 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_81', '62_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_16', 'origin': '63_81~CUW~62_92#MGNP'} Metrics: ['ELUC: -8.54673660285374', 'NSGA-II_crowding_distance: 0.07045069141677678', 'NSGA-II_rank: 1', 'change: 0.10894418938692656', 'is_elite: False']\n", + "Id: 64_56 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '63_36'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_56', 'origin': '62_92~CUW~63_36#MGNP'} Metrics: ['ELUC: -8.645697291256658', 'NSGA-II_crowding_distance: 0.49647645382794037', 'NSGA-II_rank: 3', 'change: 0.1269205652215254', 'is_elite: False']\n", + "Id: 64_65 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_20', '62_69'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_65', 'origin': '63_20~CUW~62_69#MGNP'} Metrics: ['ELUC: -8.754219942080114', 'NSGA-II_crowding_distance: 0.3193946873570147', 'NSGA-II_rank: 2', 'change: 0.12576517583526117', 'is_elite: False']\n", + "Id: 64_54 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '63_81'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_54', 'origin': '62_92~CUW~63_81#MGNP'} Metrics: ['ELUC: -8.78248427988815', 'NSGA-II_crowding_distance: 0.31631179028712386', 'NSGA-II_rank: 1', 'change: 0.11164252006914299', 'is_elite: True']\n", + "Id: 64_32 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_56', '2_49'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_32', 'origin': '63_56~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.574533734310824', 'NSGA-II_crowding_distance: 0.5713687739850634', 'NSGA-II_rank: 6', 'change: 0.27556481966898466', 'is_elite: False']\n", + "Id: 64_49 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '63_22'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_49', 'origin': '63_36~CUW~63_22#MGNP'} Metrics: ['ELUC: -10.065255915918002', 'NSGA-II_crowding_distance: 0.5816222007909322', 'NSGA-II_rank: 3', 'change: 0.1763304131030769', 'is_elite: False']\n", + "Id: 64_23 Identity: {'ancestor_count': 57, 'ancestor_ids': ['63_82', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_23', 'origin': '63_82~CUW~63_80#MGNP'} Metrics: ['ELUC: -10.389682805760163', 'NSGA-II_crowding_distance: 0.15953366832389698', 'NSGA-II_rank: 6', 'change: 0.2821918336565032', 'is_elite: False']\n", + "Id: 64_15 Identity: {'ancestor_count': 61, 'ancestor_ids': ['63_92', '62_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_15', 'origin': '63_92~CUW~62_92#MGNP'} Metrics: ['ELUC: -10.523477734022492', 'NSGA-II_crowding_distance: 0.5450542797106174', 'NSGA-II_rank: 2', 'change: 0.15476365282087445', 'is_elite: False']\n", + "Id: 64_82 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_82', 'origin': '62_92~CUW~63_80#MGNP'} Metrics: ['ELUC: -10.693083453928507', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2877976657291826', 'is_elite: False']\n", + "Id: 64_94 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_69', '63_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_94', 'origin': '62_69~CUW~63_92#MGNP'} Metrics: ['ELUC: -11.650498896140382', 'NSGA-II_crowding_distance: 0.5006326466780632', 'NSGA-II_rank: 1', 'change: 0.1506527758051681', 'is_elite: True']\n", + "Id: 64_90 Identity: {'ancestor_count': 61, 'ancestor_ids': ['63_29', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_90', 'origin': '63_29~CUW~63_80#MGNP'} Metrics: ['ELUC: -12.033208533090805', 'NSGA-II_crowding_distance: 1.0835988731885413', 'NSGA-II_rank: 5', 'change: 0.27343590941715906', 'is_elite: False']\n", + "Id: 64_25 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_18', '63_39'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_25', 'origin': '63_18~CUW~63_39#MGNP'} Metrics: ['ELUC: -12.093152594191682', 'NSGA-II_crowding_distance: 0.444767917577362', 'NSGA-II_rank: 3', 'change: 0.2107058338444051', 'is_elite: False']\n", + "Id: 64_20 Identity: {'ancestor_count': 57, 'ancestor_ids': ['63_82', '62_69'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_20', 'origin': '63_82~CUW~62_69#MGNP'} Metrics: ['ELUC: -12.372905554596048', 'NSGA-II_crowding_distance: 0.4260364530675067', 'NSGA-II_rank: 3', 'change: 0.24559263285420882', 'is_elite: False']\n", + "Id: 64_100 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_80', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_100', 'origin': '63_80~CUW~63_13#MGNP'} Metrics: ['ELUC: -12.922833214007696', 'NSGA-II_crowding_distance: 1.0437782065852144', 'NSGA-II_rank: 4', 'change: 0.26209202358290273', 'is_elite: False']\n", + "Id: 64_74 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '63_29'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_74', 'origin': '63_36~CUW~63_29#MGNP'} Metrics: ['ELUC: -13.319747210467197', 'NSGA-II_crowding_distance: 0.23817483760588404', 'NSGA-II_rank: 1', 'change: 0.18402139475490095', 'is_elite: True']\n", + "Id: 64_88 Identity: {'ancestor_count': 62, 'ancestor_ids': ['61_51', '63_56'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_88', 'origin': '61_51~CUW~63_56#MGNP'} Metrics: ['ELUC: -13.685960935950456', 'NSGA-II_crowding_distance: 0.05224798340183312', 'NSGA-II_rank: 1', 'change: 0.18717642139160498', 'is_elite: False']\n", + "Id: 64_91 Identity: {'ancestor_count': 62, 'ancestor_ids': ['61_51', '63_36'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_91', 'origin': '61_51~CUW~63_36#MGNP'} Metrics: ['ELUC: -13.828444603555111', 'NSGA-II_crowding_distance: 0.4184680618410213', 'NSGA-II_rank: 2', 'change: 0.19185320446207624', 'is_elite: False']\n", + "Id: 64_58 Identity: {'ancestor_count': 61, 'ancestor_ids': ['63_80', '63_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_58', 'origin': '63_80~CUW~63_92#MGNP'} Metrics: ['ELUC: -13.895970859484304', 'NSGA-II_crowding_distance: 0.21704084240312618', 'NSGA-II_rank: 5', 'change: 0.2761866205208647', 'is_elite: False']\n", + "Id: 64_63 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '63_36'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_63', 'origin': '63_36~CUW~63_36#MGNP'} Metrics: ['ELUC: -13.896143619318007', 'NSGA-II_crowding_distance: 0.20161339598442612', 'NSGA-II_rank: 2', 'change: 0.21288146175010014', 'is_elite: False']\n", + "Id: 64_31 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_18', '63_29'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_31', 'origin': '63_18~CUW~63_29#MGNP'} Metrics: ['ELUC: -13.914131339650634', 'NSGA-II_crowding_distance: 0.09658624209733724', 'NSGA-II_rank: 1', 'change: 0.18952414678061139', 'is_elite: False']\n", + "Id: 64_24 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_20', '63_36'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_24', 'origin': '63_20~CUW~63_36#MGNP'} Metrics: ['ELUC: -14.284809840998385', 'NSGA-II_crowding_distance: 0.1135537642688125', 'NSGA-II_rank: 1', 'change: 0.20583295308382826', 'is_elite: False']\n", + "Id: 64_17 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_17', 'origin': '62_92~CUW~63_18#MGNP'} Metrics: ['ELUC: -14.395355182570293', 'NSGA-II_crowding_distance: 0.26818754632001934', 'NSGA-II_rank: 2', 'change: 0.23477718928815947', 'is_elite: False']\n", + "Id: 64_34 Identity: {'ancestor_count': 62, 'ancestor_ids': ['2_49', '63_56'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_34', 'origin': '2_49~CUW~63_56#MGNP'} Metrics: ['ELUC: -14.422263800702662', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2876019641403424', 'is_elite: False']\n", + "Id: 63_36 Identity: {'ancestor_count': 61, 'ancestor_ids': ['61_51', '62_81'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_36', 'origin': '61_51~CUW~62_81#MGNP'} Metrics: ['ELUC: -14.475667047678117', 'NSGA-II_crowding_distance: 0.22174939325679155', 'NSGA-II_rank: 1', 'change: 0.2138766254090932', 'is_elite: True']\n", + "Id: 64_78 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_69', '63_82'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_78', 'origin': '62_69~CUW~63_82#MGNP'} Metrics: ['ELUC: -15.41506566667656', 'NSGA-II_crowding_distance: 0.387247512519176', 'NSGA-II_rank: 4', 'change: 0.2641537527141316', 'is_elite: False']\n", + "Id: 64_40 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_54', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_40', 'origin': '63_54~CUW~63_18#MGNP'} Metrics: ['ELUC: -15.65352726135874', 'NSGA-II_crowding_distance: 0.20415756247166494', 'NSGA-II_rank: 1', 'change: 0.2487704737891359', 'is_elite: True']\n", + "Id: 64_71 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '63_54'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_71', 'origin': '63_36~CUW~63_54#MGNP'} Metrics: ['ELUC: -15.7239270057372', 'NSGA-II_crowding_distance: 0.4714273463498809', 'NSGA-II_rank: 3', 'change: 0.25461402857797816', 'is_elite: False']\n", + "Id: 64_53 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_18', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_53', 'origin': '63_18~CUW~63_18#MGNP'} Metrics: ['ELUC: -15.77296594771724', 'NSGA-II_crowding_distance: 0.3334759221317424', 'NSGA-II_rank: 2', 'change: 0.2541430338229574', 'is_elite: False']\n", + "Id: 63_18 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_81', '62_22'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_18', 'origin': '62_81~CUW~62_22#MGNP'} Metrics: ['ELUC: -15.774535594770928', 'NSGA-II_crowding_distance: 0.05715553320121455', 'NSGA-II_rank: 1', 'change: 0.25275049275762856', 'is_elite: False']\n", + "Id: 64_85 Identity: {'ancestor_count': 57, 'ancestor_ids': ['63_80', '63_82'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_85', 'origin': '63_80~CUW~63_82#MGNP'} Metrics: ['ELUC: -15.998514413677482', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.3057915246840335', 'is_elite: False']\n", + "Id: 64_60 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_18', '60_33'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_60', 'origin': '63_18~CUW~60_33#MGNP'} Metrics: ['ELUC: -16.074187574484913', 'NSGA-II_crowding_distance: 0.10129512956846769', 'NSGA-II_rank: 1', 'change: 0.2586856760017411', 'is_elite: False']\n", + "Id: 64_29 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_29', 'origin': '62_92~CUW~63_80#MGNP'} Metrics: ['ELUC: -16.098720836398513', 'NSGA-II_crowding_distance: 0.24689151716035768', 'NSGA-II_rank: 3', 'change: 0.2987883911335755', 'is_elite: False']\n", + "Id: 64_99 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_82', '63_54'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_99', 'origin': '63_82~CUW~63_54#MGNP'} Metrics: ['ELUC: -16.245732125076405', 'NSGA-II_crowding_distance: 0.08398870272119367', 'NSGA-II_rank: 1', 'change: 0.27497835166846224', 'is_elite: False']\n", + "Id: 64_76 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_80', '63_13'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_76', 'origin': '63_80~CUW~63_13#MGNP'} Metrics: ['ELUC: -16.270008846882448', 'NSGA-II_crowding_distance: 0.06628255158494382', 'NSGA-II_rank: 1', 'change: 0.2804228858144213', 'is_elite: False']\n", + "Id: 64_52 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '2_49'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_52', 'origin': '62_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.62892810694465', 'NSGA-II_crowding_distance: 0.09066895916205722', 'NSGA-II_rank: 3', 'change: 0.29900106671791804', 'is_elite: False']\n", + "Id: 63_82 Identity: {'ancestor_count': 56, 'ancestor_ids': ['62_33', '62_33'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_82', 'origin': '62_33~CUW~62_33#MGNP'} Metrics: ['ELUC: -16.828352259436347', 'NSGA-II_crowding_distance: 0.2867651478307558', 'NSGA-II_rank: 2', 'change: 0.2846832908105413', 'is_elite: False']\n", + "Id: 64_37 Identity: {'ancestor_count': 57, 'ancestor_ids': ['63_82', '1_1'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_37', 'origin': '63_82~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.904848648773406', 'NSGA-II_crowding_distance: 0.1451838423177661', 'NSGA-II_rank: 1', 'change: 0.2835701773875209', 'is_elite: False']\n", + "Id: 64_27 Identity: {'ancestor_count': 57, 'ancestor_ids': ['63_82', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_27', 'origin': '63_82~CUW~63_80#MGNP'} Metrics: ['ELUC: -17.183058185537426', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30320991041615786', 'is_elite: False']\n", + "Id: 64_19 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_18', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_19', 'origin': '63_18~CUW~63_80#MGNP'} Metrics: ['ELUC: -17.458335713443322', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3027971472507313', 'is_elite: False']\n", + "Id: 64_26 Identity: {'ancestor_count': 61, 'ancestor_ids': ['63_82', '62_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_26', 'origin': '63_82~CUW~62_92#MGNP'} Metrics: ['ELUC: -17.52952742715067', 'NSGA-II_crowding_distance: 0.10150707766250114', 'NSGA-II_rank: 1', 'change: 0.3023680903987839', 'is_elite: False']\n", + "Id: 64_51 Identity: {'ancestor_count': 57, 'ancestor_ids': ['62_69', '2_49'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_51', 'origin': '62_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.571634071954676', 'NSGA-II_crowding_distance: 0.006000175991260319', 'NSGA-II_rank: 1', 'change: 0.30254207309990927', 'is_elite: False']\n", + "Id: 64_14 Identity: {'ancestor_count': 4, 'ancestor_ids': ['2_49', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_14', 'origin': '2_49~CUW~63_80#MGNP'} Metrics: ['ELUC: -17.596773932974873', 'NSGA-II_crowding_distance: 0.003065537900504219', 'NSGA-II_rank: 1', 'change: 0.30301721526984343', 'is_elite: False']\n", + "Id: 64_11 Identity: {'ancestor_count': 4, 'ancestor_ids': ['63_80', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_11', 'origin': '63_80~CUW~63_80#MGNP'} Metrics: ['ELUC: -17.5973572441212', 'NSGA-II_crowding_distance: 4.574086254004047e-05', 'NSGA-II_rank: 1', 'change: 0.3030202311332646', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 63_80 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '62_100'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_80', 'origin': '2_49~CUW~62_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 64_38 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_38', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 64_80 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_80', '63_36'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_80', 'origin': '63_80~CUW~63_36#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 64_89 Identity: {'ancestor_count': 4, 'ancestor_ids': ['63_80', '63_80'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_89', 'origin': '63_80~CUW~63_80#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 64_92 Identity: {'ancestor_count': 57, 'ancestor_ids': ['63_82', '2_49'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_92', 'origin': '63_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 64.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 65...:\n", + "PopulationResponse:\n", + " Generation: 65\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/65/20240220-032949\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 65 and asking ESP for generation 66...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 65 data persisted.\n", + "Evaluated candidates:\n", + "Id: 65_74 Identity: {'ancestor_count': 62, 'ancestor_ids': ['2_49', '64_97'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_74', 'origin': '2_49~CUW~64_97#MGNP'} Metrics: ['ELUC: 18.629700404551322', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28334003999249957', 'is_elite: False']\n", + "Id: 65_62 Identity: {'ancestor_count': 63, 'ancestor_ids': ['2_49', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_62', 'origin': '2_49~CUW~64_54#MGNP'} Metrics: ['ELUC: 12.131525699588224', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2462422783158227', 'is_elite: False']\n", + "Id: 65_29 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_29', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 11.324080654558909', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23834999633231785', 'is_elite: False']\n", + "Id: 65_18 Identity: {'ancestor_count': 62, 'ancestor_ids': ['2_49', '64_97'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_18', 'origin': '2_49~CUW~64_97#MGNP'} Metrics: ['ELUC: 4.289029049318796', 'NSGA-II_crowding_distance: 1.7843361486721103', 'NSGA-II_rank: 9', 'change: 0.26966649727414954', 'is_elite: False']\n", + "Id: 65_17 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_24', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_17', 'origin': '64_24~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.020885380409325', 'NSGA-II_crowding_distance: 0.2890454588616979', 'NSGA-II_rank: 9', 'change: 0.2711351234965884', 'is_elite: False']\n", + "Id: 65_40 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_67', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_40', 'origin': '64_67~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.3135444543932984', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2720165519425624', 'is_elite: False']\n", + "Id: 65_46 Identity: {'ancestor_count': 59, 'ancestor_ids': ['64_21', '1_1'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_46', 'origin': '64_21~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.1664402622830647', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07071267772440655', 'is_elite: False']\n", + "Id: 65_55 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '1_1'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_55', 'origin': '64_40~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.5316011578314022', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08780597208373801', 'is_elite: False']\n", + "Id: 65_100 Identity: {'ancestor_count': 58, 'ancestor_ids': ['64_37', '63_22'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_100', 'origin': '64_37~CUW~63_22#MGNP'} Metrics: ['ELUC: 0.3682221779440427', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2322783203455657', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 63_22 Identity: {'ancestor_count': 54, 'ancestor_ids': ['60_57', '60_57'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_22', 'origin': '60_57~CUW~60_57#MGNP'} Metrics: ['ELUC: -0.3263836649796108', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04710403862932653', 'is_elite: False']\n", + "Id: 65_87 Identity: {'ancestor_count': 55, 'ancestor_ids': ['63_22', '1_1'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_87', 'origin': '63_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.3333090149071922', 'NSGA-II_crowding_distance: 0.19381451384380136', 'NSGA-II_rank: 1', 'change: 0.0343879787181119', 'is_elite: False']\n", + "Id: 65_92 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_22', '63_20'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_92', 'origin': '63_22~CUW~63_20#MGNP'} Metrics: ['ELUC: -0.3457671516241081', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06137497495997249', 'is_elite: False']\n", + "Id: 65_20 Identity: {'ancestor_count': 62, 'ancestor_ids': ['1_1', '64_94'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_20', 'origin': '1_1~CUW~64_94#MGNP'} Metrics: ['ELUC: -0.35901764880856435', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08749636372254357', 'is_elite: False']\n", + "Id: 65_70 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_54', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_70', 'origin': '64_54~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 65_82 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_20', '1_1'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_82', 'origin': '63_20~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6408979371134926', 'NSGA-II_crowding_distance: 0.1756824784348743', 'NSGA-II_rank: 3', 'change: 0.06204427727082499', 'is_elite: False']\n", + "Id: 65_81 Identity: {'ancestor_count': 62, 'ancestor_ids': ['1_1', '64_97'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_81', 'origin': '1_1~CUW~64_97#MGNP'} Metrics: ['ELUC: -0.6922286811883429', 'NSGA-II_crowding_distance: 0.1534894205266393', 'NSGA-II_rank: 1', 'change: 0.05098070859128114', 'is_elite: False']\n", + "Id: 64_67 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_13', '1_1'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_67', 'origin': '63_13~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7832529278165445', 'NSGA-II_crowding_distance: 0.15730694189959443', 'NSGA-II_rank: 2', 'change: 0.054481061997689935', 'is_elite: False']\n", + "Id: 65_24 Identity: {'ancestor_count': 55, 'ancestor_ids': ['63_22', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_24', 'origin': '63_22~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.9157202201301292', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.30519382668046685', 'is_elite: False']\n", + "Id: 65_47 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '64_37'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_47', 'origin': '64_98~CUW~64_37#MGNP'} Metrics: ['ELUC: -1.300554718855377', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2192023371099343', 'is_elite: False']\n", + "Id: 65_13 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_21', '64_40'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_13', 'origin': '64_21~CUW~64_40#MGNP'} Metrics: ['ELUC: -1.5900151503737001', 'NSGA-II_crowding_distance: 0.9219738421413378', 'NSGA-II_rank: 6', 'change: 0.10355244591823808', 'is_elite: False']\n", + "Id: 65_80 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_74', '63_22'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_80', 'origin': '64_74~CUW~63_22#MGNP'} Metrics: ['ELUC: -1.828392961799778', 'NSGA-II_crowding_distance: 0.5390557780626', 'NSGA-II_rank: 5', 'change: 0.09417942499074783', 'is_elite: False']\n", + "Id: 65_32 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_32', 'origin': '64_98~CUW~64_67#MGNP'} Metrics: ['ELUC: -1.8455167929725966', 'NSGA-II_crowding_distance: 0.2899650987274401', 'NSGA-II_rank: 2', 'change: 0.06395292605893872', 'is_elite: False']\n", + "Id: 65_12 Identity: {'ancestor_count': 58, 'ancestor_ids': ['63_20', '1_1'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_12', 'origin': '63_20~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8533793022748437', 'NSGA-II_crowding_distance: 0.4522577113745426', 'NSGA-II_rank: 4', 'change: 0.07648487117173476', 'is_elite: False']\n", + "Id: 65_48 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '63_22'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_48', 'origin': '64_98~CUW~63_22#MGNP'} Metrics: ['ELUC: -2.014626818808028', 'NSGA-II_crowding_distance: 0.13315961107403257', 'NSGA-II_rank: 1', 'change: 0.051653319934981734', 'is_elite: False']\n", + "Id: 65_75 Identity: {'ancestor_count': 63, 'ancestor_ids': ['63_20', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_75', 'origin': '63_20~CUW~64_54#MGNP'} Metrics: ['ELUC: -2.1842552356422407', 'NSGA-II_crowding_distance: 0.2139705970711983', 'NSGA-II_rank: 3', 'change: 0.07452399688265147', 'is_elite: False']\n", + "Id: 65_79 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_79', 'origin': '64_98~CUW~64_67#MGNP'} Metrics: ['ELUC: -2.185104812492197', 'NSGA-II_crowding_distance: 0.2094662879631577', 'NSGA-II_rank: 1', 'change: 0.0653780009856818', 'is_elite: True']\n", + "Id: 65_39 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '63_22'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_39', 'origin': '64_98~CUW~63_22#MGNP'} Metrics: ['ELUC: -2.941510253603077', 'NSGA-II_crowding_distance: 0.09715769192254589', 'NSGA-II_rank: 3', 'change: 0.07715251484802427', 'is_elite: False']\n", + "Id: 65_37 Identity: {'ancestor_count': 63, 'ancestor_ids': ['63_22', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_37', 'origin': '63_22~CUW~64_54#MGNP'} Metrics: ['ELUC: -3.09204677401324', 'NSGA-II_crowding_distance: 0.09238266574040818', 'NSGA-II_rank: 3', 'change: 0.08340305108286479', 'is_elite: False']\n", + "Id: 65_71 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_24', '64_92'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_71', 'origin': '64_24~CUW~64_92#MGNP'} Metrics: ['ELUC: -3.234382101927737', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.27681202276070666', 'is_elite: False']\n", + "Id: 65_45 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_74', '63_22'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_45', 'origin': '64_74~CUW~63_22#MGNP'} Metrics: ['ELUC: -3.5041504944589903', 'NSGA-II_crowding_distance: 0.45746545383651316', 'NSGA-II_rank: 4', 'change: 0.0886620120993664', 'is_elite: False']\n", + "Id: 65_63 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_74', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_63', 'origin': '64_74~CUW~64_67#MGNP'} Metrics: ['ELUC: -3.8530741184118944', 'NSGA-II_crowding_distance: 0.12369315006489487', 'NSGA-II_rank: 3', 'change: 0.08488134893695118', 'is_elite: False']\n", + "Id: 65_51 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '63_36'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_51', 'origin': '64_98~CUW~63_36#MGNP'} Metrics: ['ELUC: -3.9817275570695383', 'NSGA-II_crowding_distance: 0.8013787374220784', 'NSGA-II_rank: 5', 'change: 0.12687230539674485', 'is_elite: False']\n", + "Id: 65_44 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_37', '63_36'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_44', 'origin': '64_37~CUW~63_36#MGNP'} Metrics: ['ELUC: -4.14304821496747', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.31334399005670616', 'is_elite: False']\n", + "Id: 65_84 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_84', 'origin': '64_40~CUW~64_54#MGNP'} Metrics: ['ELUC: -4.480454417125699', 'NSGA-II_crowding_distance: 0.2929818902944841', 'NSGA-II_rank: 3', 'change: 0.09127448281344716', 'is_elite: False']\n", + "Id: 65_67 Identity: {'ancestor_count': 62, 'ancestor_ids': ['1_1', '63_36'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_67', 'origin': '1_1~CUW~63_36#MGNP'} Metrics: ['ELUC: -4.494926772264565', 'NSGA-II_crowding_distance: 1.3763223368972044', 'NSGA-II_rank: 6', 'change: 0.16298710741268468', 'is_elite: False']\n", + "Id: 65_77 Identity: {'ancestor_count': 63, 'ancestor_ids': ['63_20', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_77', 'origin': '63_20~CUW~64_54#MGNP'} Metrics: ['ELUC: -4.56291525918018', 'NSGA-II_crowding_distance: 0.22562213266381267', 'NSGA-II_rank: 2', 'change: 0.07076138472429408', 'is_elite: False']\n", + "Id: 65_43 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_67', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_43', 'origin': '64_67~CUW~64_54#MGNP'} Metrics: ['ELUC: -4.647058217249514', 'NSGA-II_crowding_distance: 0.30264075845896987', 'NSGA-II_rank: 2', 'change: 0.07872414921450449', 'is_elite: False']\n", + "Id: 65_61 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_97', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_61', 'origin': '64_97~CUW~64_67#MGNP'} Metrics: ['ELUC: -4.797884582837093', 'NSGA-II_crowding_distance: 0.22243220035635808', 'NSGA-II_rank: 1', 'change: 0.06692065020947584', 'is_elite: True']\n", + "Id: 65_72 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_54', '64_21'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_72', 'origin': '64_54~CUW~64_21#MGNP'} Metrics: ['ELUC: -5.575329385497145', 'NSGA-II_crowding_distance: 0.19516623706873631', 'NSGA-II_rank: 1', 'change: 0.07421365676884618', 'is_elite: False']\n", + "Id: 65_15 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_74', '64_98'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_15', 'origin': '64_74~CUW~64_98#MGNP'} Metrics: ['ELUC: -5.706425675616314', 'NSGA-II_crowding_distance: 0.8014698193406571', 'NSGA-II_rank: 4', 'change: 0.11998505775793157', 'is_elite: False']\n", + "Id: 65_64 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '64_97'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_64', 'origin': '63_36~CUW~64_97#MGNP'} Metrics: ['ELUC: -6.214638417218467', 'NSGA-II_crowding_distance: 0.36769193677857914', 'NSGA-II_rank: 3', 'change: 0.11720197959285042', 'is_elite: False']\n", + "Id: 65_73 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_94', '1_1'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_73', 'origin': '64_94~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.486908796504281', 'NSGA-II_crowding_distance: 0.2052832963598556', 'NSGA-II_rank: 1', 'change: 0.09649064453990763', 'is_elite: True']\n", + "Id: 65_76 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_21', '64_24'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_76', 'origin': '64_21~CUW~64_24#MGNP'} Metrics: ['ELUC: -6.878991522817848', 'NSGA-II_crowding_distance: 0.8486209279403522', 'NSGA-II_rank: 5', 'change: 0.15862981038865367', 'is_elite: False']\n", + "Id: 65_94 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_92', '63_22'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_94', 'origin': '62_92~CUW~63_22#MGNP'} Metrics: ['ELUC: -7.543527251220125', 'NSGA-II_crowding_distance: 0.37370584249320593', 'NSGA-II_rank: 2', 'change: 0.10230207914153737', 'is_elite: False']\n", + "Id: 65_88 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_54', '64_98'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_88', 'origin': '64_54~CUW~64_98#MGNP'} Metrics: ['ELUC: -7.562705722026094', 'NSGA-II_crowding_distance: 0.18134229300112725', 'NSGA-II_rank: 1', 'change: 0.10173922865924302', 'is_elite: False']\n", + "Id: 65_41 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '64_37'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_41', 'origin': '64_40~CUW~64_37#MGNP'} Metrics: ['ELUC: -8.247308387130047', 'NSGA-II_crowding_distance: 1.0780261578586623', 'NSGA-II_rank: 6', 'change: 0.2638709520772513', 'is_elite: False']\n", + "Id: 65_59 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_24', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_59', 'origin': '64_24~CUW~64_54#MGNP'} Metrics: ['ELUC: -8.251309659367548', 'NSGA-II_crowding_distance: 0.22787075866368567', 'NSGA-II_rank: 3', 'change: 0.11993017397698501', 'is_elite: False']\n", + "Id: 65_58 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '64_94'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_58', 'origin': '62_92~CUW~64_94#MGNP'} Metrics: ['ELUC: -8.467174078790931', 'NSGA-II_crowding_distance: 0.1796229236408021', 'NSGA-II_rank: 2', 'change: 0.11556478411322953', 'is_elite: False']\n", + "Id: 65_23 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_94', '1_1'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_23', 'origin': '64_94~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.570719435110744', 'NSGA-II_crowding_distance: 0.3498537006804523', 'NSGA-II_rank: 3', 'change: 0.13467821912738864', 'is_elite: False']\n", + "Id: 64_54 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '63_81'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_54', 'origin': '62_92~CUW~63_81#MGNP'} Metrics: ['ELUC: -8.78248427988815', 'NSGA-II_crowding_distance: 0.14944842349912688', 'NSGA-II_rank: 1', 'change: 0.11164252006914299', 'is_elite: False']\n", + "Id: 65_35 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '64_97'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_35', 'origin': '64_98~CUW~64_97#MGNP'} Metrics: ['ELUC: -8.907856476067677', 'NSGA-II_crowding_distance: 0.16246790178123077', 'NSGA-II_rank: 2', 'change: 0.12712834501491724', 'is_elite: False']\n", + "Id: 65_36 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_67', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_36', 'origin': '64_67~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.971402326866672', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3037302131881038', 'is_elite: False']\n", + "Id: 65_89 Identity: {'ancestor_count': 63, 'ancestor_ids': ['63_20', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_89', 'origin': '63_20~CUW~64_54#MGNP'} Metrics: ['ELUC: -8.977859865202893', 'NSGA-II_crowding_distance: 0.19758449703751685', 'NSGA-II_rank: 1', 'change: 0.12231570576482353', 'is_elite: False']\n", + "Id: 65_96 Identity: {'ancestor_count': 63, 'ancestor_ids': ['1_1', '64_60'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_96', 'origin': '1_1~CUW~64_60#MGNP'} Metrics: ['ELUC: -9.644722472748255', 'NSGA-II_crowding_distance: 0.1560694692099424', 'NSGA-II_rank: 2', 'change: 0.13887214401009257', 'is_elite: False']\n", + "Id: 65_33 Identity: {'ancestor_count': 62, 'ancestor_ids': ['1_1', '64_94'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_33', 'origin': '1_1~CUW~64_94#MGNP'} Metrics: ['ELUC: -10.075556351015415', 'NSGA-II_crowding_distance: 0.16630201108191384', 'NSGA-II_rank: 2', 'change: 0.14896669587375763', 'is_elite: False']\n", + "Id: 65_91 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_94', '64_21'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_91', 'origin': '64_94~CUW~64_21#MGNP'} Metrics: ['ELUC: -10.8386360952982', 'NSGA-II_crowding_distance: 0.21919001423818354', 'NSGA-II_rank: 1', 'change: 0.1357038007433227', 'is_elite: True']\n", + "Id: 65_52 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_94', '64_74'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_52', 'origin': '64_94~CUW~64_74#MGNP'} Metrics: ['ELUC: -11.026391876919009', 'NSGA-II_crowding_distance: 1.0284431258821267', 'NSGA-II_rank: 5', 'change: 0.1651859520397275', 'is_elite: False']\n", + "Id: 65_60 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_54', '64_74'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_60', 'origin': '64_54~CUW~64_74#MGNP'} Metrics: ['ELUC: -11.097390823511585', 'NSGA-II_crowding_distance: 1.1108609622786338', 'NSGA-II_rank: 4', 'change: 0.1535290397196447', 'is_elite: False']\n", + "Id: 65_69 Identity: {'ancestor_count': 59, 'ancestor_ids': ['64_21', '64_92'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_69', 'origin': '64_21~CUW~64_92#MGNP'} Metrics: ['ELUC: -11.218636884923317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27914295365554154', 'is_elite: False']\n", + "Id: 65_30 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_74', '64_94'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_30', 'origin': '64_74~CUW~64_94#MGNP'} Metrics: ['ELUC: -11.449735566418699', 'NSGA-II_crowding_distance: 0.35361963685958275', 'NSGA-II_rank: 3', 'change: 0.15294160737019427', 'is_elite: False']\n", + "Id: 65_50 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_24', '64_98'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_50', 'origin': '64_24~CUW~64_98#MGNP'} Metrics: ['ELUC: -11.531935085844935', 'NSGA-II_crowding_distance: 0.365189350192023', 'NSGA-II_rank: 3', 'change: 0.17205235359601195', 'is_elite: False']\n", + "Id: 64_94 Identity: {'ancestor_count': 61, 'ancestor_ids': ['62_69', '63_92'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_94', 'origin': '62_69~CUW~63_92#MGNP'} Metrics: ['ELUC: -11.650498896140382', 'NSGA-II_crowding_distance: 0.46655457741437734', 'NSGA-II_rank: 2', 'change: 0.1506527758051681', 'is_elite: False']\n", + "Id: 65_11 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_94', '64_98'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_11', 'origin': '64_94~CUW~64_98#MGNP'} Metrics: ['ELUC: -11.817458635163227', 'NSGA-II_crowding_distance: 0.18705135919993765', 'NSGA-II_rank: 1', 'change: 0.13952825502730673', 'is_elite: False']\n", + "Id: 65_19 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '64_60'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_19', 'origin': '64_40~CUW~64_60#MGNP'} Metrics: ['ELUC: -11.913791162537992', 'NSGA-II_crowding_distance: 0.38537552210587833', 'NSGA-II_rank: 3', 'change: 0.2298071895003397', 'is_elite: False']\n", + "Id: 65_66 Identity: {'ancestor_count': 59, 'ancestor_ids': ['64_92', '64_21'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_66', 'origin': '64_92~CUW~64_21#MGNP'} Metrics: ['ELUC: -11.928105932213052', 'NSGA-II_crowding_distance: 0.7462724692848001', 'NSGA-II_rank: 4', 'change: 0.267810619918026', 'is_elite: False']\n", + "Id: 65_85 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_94', '64_26'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_85', 'origin': '64_94~CUW~64_26#MGNP'} Metrics: ['ELUC: -12.028654950815888', 'NSGA-II_crowding_distance: 0.3863314690132229', 'NSGA-II_rank: 3', 'change: 0.25306328850296816', 'is_elite: False']\n", + "Id: 65_97 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_60', '64_21'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_97', 'origin': '64_60~CUW~64_21#MGNP'} Metrics: ['ELUC: -12.446347854838491', 'NSGA-II_crowding_distance: 0.23455987641250875', 'NSGA-II_rank: 1', 'change: 0.1642323937672648', 'is_elite: True']\n", + "Id: 65_56 Identity: {'ancestor_count': 62, 'ancestor_ids': ['62_92', '63_36'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_56', 'origin': '62_92~CUW~63_36#MGNP'} Metrics: ['ELUC: -13.159424364420238', 'NSGA-II_crowding_distance: 0.6230219254757251', 'NSGA-II_rank: 2', 'change: 0.22038887143293406', 'is_elite: False']\n", + "Id: 64_74 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '63_29'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_74', 'origin': '63_36~CUW~63_29#MGNP'} Metrics: ['ELUC: -13.319747210467197', 'NSGA-II_crowding_distance: 0.17948039647934863', 'NSGA-II_rank: 1', 'change: 0.18402139475490095', 'is_elite: False']\n", + "Id: 65_54 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_92', '64_94'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_54', 'origin': '64_92~CUW~64_94#MGNP'} Metrics: ['ELUC: -13.320444728767823', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2791753920310453', 'is_elite: False']\n", + "Id: 65_14 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_54', '63_36'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_14', 'origin': '64_54~CUW~63_36#MGNP'} Metrics: ['ELUC: -13.375732160949388', 'NSGA-II_crowding_distance: 0.1051477257146782', 'NSGA-II_rank: 1', 'change: 0.20201340616243826', 'is_elite: False']\n", + "Id: 65_78 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_74', '63_36'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_78', 'origin': '64_74~CUW~63_36#MGNP'} Metrics: ['ELUC: -13.85546014373972', 'NSGA-II_crowding_distance: 0.10231814163190565', 'NSGA-II_rank: 1', 'change: 0.20630391925801106', 'is_elite: False']\n", + "Id: 63_36 Identity: {'ancestor_count': 61, 'ancestor_ids': ['61_51', '62_81'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_36', 'origin': '61_51~CUW~62_81#MGNP'} Metrics: ['ELUC: -14.475667047678117', 'NSGA-II_crowding_distance: 0.24459034340748023', 'NSGA-II_rank: 1', 'change: 0.2138766254090932', 'is_elite: True']\n", + "Id: 65_93 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_21', '64_26'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_93', 'origin': '64_21~CUW~64_26#MGNP'} Metrics: ['ELUC: -14.89111071463949', 'NSGA-II_crowding_distance: 0.28474790276680245', 'NSGA-II_rank: 3', 'change: 0.2744422134023476', 'is_elite: False']\n", + "Id: 65_65 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '64_92'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_65', 'origin': '64_40~CUW~64_92#MGNP'} Metrics: ['ELUC: -14.895088605474927', 'NSGA-II_crowding_distance: 0.06331317767959838', 'NSGA-II_rank: 3', 'change: 0.27604837619063777', 'is_elite: False']\n", + "Id: 65_31 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '64_92'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_31', 'origin': '63_36~CUW~64_92#MGNP'} Metrics: ['ELUC: -15.239211321975684', 'NSGA-II_crowding_distance: 0.10118452256950908', 'NSGA-II_rank: 3', 'change: 0.28382000220147513', 'is_elite: False']\n", + "Id: 65_99 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '64_37'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_99', 'origin': '64_40~CUW~64_37#MGNP'} Metrics: ['ELUC: -15.274712468390426', 'NSGA-II_crowding_distance: 0.3225317002795725', 'NSGA-II_rank: 2', 'change: 0.2534792099043674', 'is_elite: False']\n", + "Id: 64_40 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_54', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_40', 'origin': '63_54~CUW~63_18#MGNP'} Metrics: ['ELUC: -15.65352726135874', 'NSGA-II_crowding_distance: 0.24846440144881538', 'NSGA-II_rank: 1', 'change: 0.2487704737891359', 'is_elite: True']\n", + "Id: 65_57 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_57', 'origin': '63_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.685197245789633', 'NSGA-II_crowding_distance: 0.07108704523380921', 'NSGA-II_rank: 3', 'change: 0.2875866086864538', 'is_elite: False']\n", + "Id: 65_25 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_94', '64_92'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_25', 'origin': '64_94~CUW~64_92#MGNP'} Metrics: ['ELUC: -15.884005823673805', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2906028018371194', 'is_elite: False']\n", + "Id: 65_68 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_60', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_68', 'origin': '64_60~CUW~64_54#MGNP'} Metrics: ['ELUC: -15.944123778868402', 'NSGA-II_crowding_distance: 0.2185112939568501', 'NSGA-II_rank: 2', 'change: 0.2599140995798944', 'is_elite: False']\n", + "Id: 65_49 Identity: {'ancestor_count': 63, 'ancestor_ids': ['63_36', '64_98'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_49', 'origin': '63_36~CUW~64_98#MGNP'} Metrics: ['ELUC: -16.138646401286742', 'NSGA-II_crowding_distance: 0.17949875938872356', 'NSGA-II_rank: 1', 'change: 0.2597915935088998', 'is_elite: False']\n", + "Id: 65_86 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_74', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_86', 'origin': '64_74~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.199824232036594', 'NSGA-II_crowding_distance: 0.21524616311860298', 'NSGA-II_rank: 2', 'change: 0.29476369217292', 'is_elite: False']\n", + "Id: 65_27 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '64_37'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_27', 'origin': '64_40~CUW~64_37#MGNP'} Metrics: ['ELUC: -16.769941245345215', 'NSGA-II_crowding_distance: 0.12714625398945864', 'NSGA-II_rank: 1', 'change: 0.28338301399715765', 'is_elite: False']\n", + "Id: 65_21 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_26', '64_37'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_21', 'origin': '64_26~CUW~64_37#MGNP'} Metrics: ['ELUC: -16.89205517711527', 'NSGA-II_crowding_distance: 0.05868456476779425', 'NSGA-II_rank: 1', 'change: 0.2849436230631711', 'is_elite: False']\n", + "Id: 65_28 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_37', '63_36'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_28', 'origin': '64_37~CUW~63_36#MGNP'} Metrics: ['ELUC: -16.997551096655762', 'NSGA-II_crowding_distance: 0.0730619506476673', 'NSGA-II_rank: 2', 'change: 0.29843713409955225', 'is_elite: False']\n", + "Id: 65_95 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_92', '64_54'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_95', 'origin': '64_92~CUW~64_54#MGNP'} Metrics: ['ELUC: -17.082572735491308', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.2999160033667653', 'is_elite: False']\n", + "Id: 65_16 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_24', '64_26'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_16', 'origin': '64_24~CUW~64_26#MGNP'} Metrics: ['ELUC: -17.241106979946952', 'NSGA-II_crowding_distance: 0.08615877785442566', 'NSGA-II_rank: 1', 'change: 0.29289735258721583', 'is_elite: False']\n", + "Id: 65_34 Identity: {'ancestor_count': 59, 'ancestor_ids': ['2_49', '64_21'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_34', 'origin': '2_49~CUW~64_21#MGNP'} Metrics: ['ELUC: -17.41642321439181', 'NSGA-II_crowding_distance: 0.04655895739468486', 'NSGA-II_rank: 1', 'change: 0.3017527950865791', 'is_elite: False']\n", + "Id: 65_53 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_54', '64_92'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_53', 'origin': '64_54~CUW~64_92#MGNP'} Metrics: ['ELUC: -17.505816426420665', 'NSGA-II_crowding_distance: 0.011457577512102683', 'NSGA-II_rank: 1', 'change: 0.3022973069966246', 'is_elite: False']\n", + "Id: 65_26 Identity: {'ancestor_count': 63, 'ancestor_ids': ['2_49', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_26', 'origin': '2_49~CUW~64_67#MGNP'} Metrics: ['ELUC: -17.560174573630004', 'NSGA-II_crowding_distance: 0.007631713542771987', 'NSGA-II_rank: 1', 'change: 0.3027319760110714', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 64_92 Identity: {'ancestor_count': 57, 'ancestor_ids': ['63_82', '2_49'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_92', 'origin': '63_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 65_22 Identity: {'ancestor_count': 58, 'ancestor_ids': ['64_92', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_22', 'origin': '64_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 65_38 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_92', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_38', 'origin': '64_92~CUW~64_67#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 65_42 Identity: {'ancestor_count': 58, 'ancestor_ids': ['2_49', '64_92'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_42', 'origin': '2_49~CUW~64_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 65_83 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '2_49'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_83', 'origin': '64_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 65_90 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_92', '64_24'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_90', 'origin': '64_92~CUW~64_24#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 65_98 Identity: {'ancestor_count': 58, 'ancestor_ids': ['2_49', '64_37'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_98', 'origin': '2_49~CUW~64_37#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 65.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 66...:\n", + "PopulationResponse:\n", + " Generation: 66\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/66/20240220-033704\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 66 and asking ESP for generation 67...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 66 data persisted.\n", + "Evaluated candidates:\n", + "Id: 66_20 Identity: {'ancestor_count': 59, 'ancestor_ids': ['1_1', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_20', 'origin': '1_1~CUW~65_98#MGNP'} Metrics: ['ELUC: 18.553619113838657', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.29115414445174365', 'is_elite: False']\n", + "Id: 66_92 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_98', '65_91'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_92', 'origin': '65_98~CUW~65_91#MGNP'} Metrics: ['ELUC: 7.403197980005228', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27418314393560855', 'is_elite: False']\n", + "Id: 66_55 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_72', '64_40'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_55', 'origin': '65_72~CUW~64_40#MGNP'} Metrics: ['ELUC: 6.493936082250643', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.1271151742476525', 'is_elite: False']\n", + "Id: 66_77 Identity: {'ancestor_count': 63, 'ancestor_ids': ['2_49', '65_91'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_77', 'origin': '2_49~CUW~65_91#MGNP'} Metrics: ['ELUC: 6.412557591144087', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2711852567156066', 'is_elite: False']\n", + "Id: 66_32 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_11', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_32', 'origin': '65_11~CUW~65_98#MGNP'} Metrics: ['ELUC: 4.30940146187175', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25005941251200625', 'is_elite: False']\n", + "Id: 66_65 Identity: {'ancestor_count': 64, 'ancestor_ids': ['2_49', '65_89'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_65', 'origin': '2_49~CUW~65_89#MGNP'} Metrics: ['ELUC: 2.3398730138497026', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2534373055696948', 'is_elite: False']\n", + "Id: 66_67 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_67', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.178513776312852', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23234274778528394', 'is_elite: False']\n", + "Id: 66_28 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_28', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.547210858288747', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04678570401414897', 'is_elite: False']\n", + "Id: 66_36 Identity: {'ancestor_count': 64, 'ancestor_ids': ['1_1', '65_79'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_36', 'origin': '1_1~CUW~65_79#MGNP'} Metrics: ['ELUC: 0.6637019759772639', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.072584600001046', 'is_elite: False']\n", + "Id: 66_30 Identity: {'ancestor_count': 64, 'ancestor_ids': ['1_1', '65_79'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_30', 'origin': '1_1~CUW~65_79#MGNP'} Metrics: ['ELUC: 0.5244340464426184', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.038743037938703116', 'is_elite: False']\n", + "Id: 66_16 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_16', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.41357376874446844', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2549553030346891', 'is_elite: False']\n", + "Id: 66_41 Identity: {'ancestor_count': 64, 'ancestor_ids': ['64_40', '65_72'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_41', 'origin': '64_40~CUW~65_72#MGNP'} Metrics: ['ELUC: 0.2109010434718447', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15672177819175948', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 66_87 Identity: {'ancestor_count': 56, 'ancestor_ids': ['65_87', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_87', 'origin': '65_87~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.07313180248894549', 'NSGA-II_crowding_distance: 0.10555052604867617', 'NSGA-II_rank: 2', 'change: 0.045587082789309584', 'is_elite: False']\n", + "Id: 66_73 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_87', '65_79'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_73', 'origin': '65_87~CUW~65_79#MGNP'} Metrics: ['ELUC: -0.14639875555372717', 'NSGA-II_crowding_distance: 0.2394825811797362', 'NSGA-II_rank: 2', 'change: 0.05685484607501746', 'is_elite: False']\n", + "Id: 66_17 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_11', '65_87'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_17', 'origin': '65_11~CUW~65_87#MGNP'} Metrics: ['ELUC: -0.3289030893003956', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.10265215669008153', 'is_elite: False']\n", + "Id: 66_18 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_79', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_18', 'origin': '65_79~CUW~65_98#MGNP'} Metrics: ['ELUC: -0.5767696806732957', 'NSGA-II_crowding_distance: 0.5412959412972023', 'NSGA-II_rank: 8', 'change: 0.23781067798307634', 'is_elite: False']\n", + "Id: 66_24 Identity: {'ancestor_count': 64, 'ancestor_ids': ['2_49', '65_61'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_24', 'origin': '2_49~CUW~65_61#MGNP'} Metrics: ['ELUC: -0.7952478608007693', 'NSGA-II_crowding_distance: 1.2271039354765174', 'NSGA-II_rank: 8', 'change: 0.24038654762088466', 'is_elite: False']\n", + "Id: 66_27 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_73', '64_40'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_27', 'origin': '65_73~CUW~64_40#MGNP'} Metrics: ['ELUC: -0.9936290581044109', 'NSGA-II_crowding_distance: 0.8823860733680166', 'NSGA-II_rank: 6', 'change: 0.13246309595366912', 'is_elite: False']\n", + "Id: 66_93 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_61', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_93', 'origin': '65_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.0165640682800527', 'NSGA-II_crowding_distance: 0.2847125231377542', 'NSGA-II_rank: 3', 'change: 0.07237518478719432', 'is_elite: False']\n", + "Id: 66_74 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_72', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_74', 'origin': '65_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2237585094391712', 'NSGA-II_crowding_distance: 0.32697412491783395', 'NSGA-II_rank: 1', 'change: 0.0392809679484303', 'is_elite: True']\n", + "Id: 66_25 Identity: {'ancestor_count': 64, 'ancestor_ids': ['64_40', '65_97'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_25', 'origin': '64_40~CUW~65_97#MGNP'} Metrics: ['ELUC: -1.6666021873450576', 'NSGA-II_crowding_distance: 0.3724792875050401', 'NSGA-II_rank: 3', 'change: 0.07672146033549598', 'is_elite: False']\n", + "Id: 66_95 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_97', '64_40'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_95', 'origin': '65_97~CUW~64_40#MGNP'} Metrics: ['ELUC: -2.0593514444842125', 'NSGA-II_crowding_distance: 1.2953933731419252', 'NSGA-II_rank: 6', 'change: 0.16391581400082048', 'is_elite: False']\n", + "Id: 65_79 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_79', 'origin': '64_98~CUW~64_67#MGNP'} Metrics: ['ELUC: -2.185104812492197', 'NSGA-II_crowding_distance: 0.2959125259837802', 'NSGA-II_rank: 1', 'change: 0.0653780009856818', 'is_elite: True']\n", + "Id: 66_66 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '65_73'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_66', 'origin': '64_40~CUW~65_73#MGNP'} Metrics: ['ELUC: -2.2439958728533362', 'NSGA-II_crowding_distance: 0.4547857026753222', 'NSGA-II_rank: 5', 'change: 0.10411153939688363', 'is_elite: False']\n", + "Id: 66_43 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_87', '65_72'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_43', 'origin': '65_87~CUW~65_72#MGNP'} Metrics: ['ELUC: -2.8755428465502173', 'NSGA-II_crowding_distance: 0.259708984930725', 'NSGA-II_rank: 2', 'change: 0.06800794363158014', 'is_elite: False']\n", + "Id: 66_44 Identity: {'ancestor_count': 63, 'ancestor_ids': ['1_1', '65_73'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_44', 'origin': '1_1~CUW~65_73#MGNP'} Metrics: ['ELUC: -3.1482530061895', 'NSGA-II_crowding_distance: 0.18495031082892494', 'NSGA-II_rank: 2', 'change: 0.08171252612790586', 'is_elite: False']\n", + "Id: 66_80 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_98', '65_97'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_80', 'origin': '65_98~CUW~65_97#MGNP'} Metrics: ['ELUC: -4.532328920525494', 'NSGA-II_crowding_distance: 1.8129855334984044', 'NSGA-II_rank: 7', 'change: 0.2375209657717865', 'is_elite: False']\n", + "Id: 66_98 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_73', '65_61'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_98', 'origin': '65_73~CUW~65_61#MGNP'} Metrics: ['ELUC: -4.685494586275414', 'NSGA-II_crowding_distance: 0.5175867962638708', 'NSGA-II_rank: 4', 'change: 0.1012970747086459', 'is_elite: False']\n", + "Id: 65_61 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_97', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_61', 'origin': '64_97~CUW~64_67#MGNP'} Metrics: ['ELUC: -4.797884582837093', 'NSGA-II_crowding_distance: 0.19043062164605434', 'NSGA-II_rank: 1', 'change: 0.06692065020947584', 'is_elite: False']\n", + "Id: 66_70 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_81', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_70', 'origin': '65_81~CUW~63_36#MGNP'} Metrics: ['ELUC: -4.908778957221543', 'NSGA-II_crowding_distance: 0.30686997669584093', 'NSGA-II_rank: 5', 'change: 0.10937162741489048', 'is_elite: False']\n", + "Id: 66_47 Identity: {'ancestor_count': 64, 'ancestor_ids': ['1_1', '65_61'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_47', 'origin': '1_1~CUW~65_61#MGNP'} Metrics: ['ELUC: -4.915955924903025', 'NSGA-II_crowding_distance: 0.15769575580578074', 'NSGA-II_rank: 2', 'change: 0.08712982034029204', 'is_elite: False']\n", + "Id: 66_23 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_79', '65_88'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_23', 'origin': '65_79~CUW~65_88#MGNP'} Metrics: ['ELUC: -4.970036869708547', 'NSGA-II_crowding_distance: 0.08982370585686289', 'NSGA-II_rank: 1', 'change: 0.07493709938156415', 'is_elite: False']\n", + "Id: 66_71 Identity: {'ancestor_count': 64, 'ancestor_ids': ['64_40', '65_97'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_71', 'origin': '64_40~CUW~65_97#MGNP'} Metrics: ['ELUC: -5.269971303731699', 'NSGA-II_crowding_distance: 0.10371278382053735', 'NSGA-II_rank: 5', 'change: 0.10972964321756018', 'is_elite: False']\n", + "Id: 66_35 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_81', '64_74'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_35', 'origin': '65_81~CUW~64_74#MGNP'} Metrics: ['ELUC: -5.30977316646344', 'NSGA-II_crowding_distance: 0.07413794322816322', 'NSGA-II_rank: 2', 'change: 0.09186525398961842', 'is_elite: False']\n", + "Id: 66_69 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_72', '65_72'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_69', 'origin': '65_72~CUW~65_72#MGNP'} Metrics: ['ELUC: -5.7867589770513375', 'NSGA-II_crowding_distance: 0.13954025982890822', 'NSGA-II_rank: 1', 'change: 0.07694053905043877', 'is_elite: False']\n", + "Id: 66_48 Identity: {'ancestor_count': 59, 'ancestor_ids': ['65_98', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_48', 'origin': '65_98~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.79900907289776', 'NSGA-II_crowding_distance: 0.44327526206567897', 'NSGA-II_rank: 7', 'change: 0.24330406509615785', 'is_elite: False']\n", + "Id: 66_83 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_91', '65_89'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_83', 'origin': '65_91~CUW~65_89#MGNP'} Metrics: ['ELUC: -5.818461217725968', 'NSGA-II_crowding_distance: 0.19605222032171246', 'NSGA-II_rank: 5', 'change: 0.11317478058057237', 'is_elite: False']\n", + "Id: 66_81 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_89', '65_61'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_81', 'origin': '65_89~CUW~65_61#MGNP'} Metrics: ['ELUC: -5.8332133740006205', 'NSGA-II_crowding_distance: 0.171880231678802', 'NSGA-II_rank: 4', 'change: 0.10860696930216192', 'is_elite: False']\n", + "Id: 66_62 Identity: {'ancestor_count': 64, 'ancestor_ids': ['1_1', '65_97'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_62', 'origin': '1_1~CUW~65_97#MGNP'} Metrics: ['ELUC: -5.874391716079955', 'NSGA-II_crowding_distance: 0.08245979075104387', 'NSGA-II_rank: 2', 'change: 0.09274540539919708', 'is_elite: False']\n", + "Id: 66_39 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_89', '65_73'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_39', 'origin': '65_89~CUW~65_73#MGNP'} Metrics: ['ELUC: -5.946736673486817', 'NSGA-II_crowding_distance: 0.7527855358730522', 'NSGA-II_rank: 5', 'change: 0.13449309439520168', 'is_elite: False']\n", + "Id: 66_90 Identity: {'ancestor_count': 64, 'ancestor_ids': ['2_49', '65_97'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_90', 'origin': '2_49~CUW~65_97#MGNP'} Metrics: ['ELUC: -6.02273060842366', 'NSGA-II_crowding_distance: 1.4587040587027977', 'NSGA-II_rank: 8', 'change: 0.2627894807998629', 'is_elite: False']\n", + "Id: 66_60 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_89', '65_79'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_60', 'origin': '65_89~CUW~65_79#MGNP'} Metrics: ['ELUC: -6.08636435633545', 'NSGA-II_crowding_distance: 0.3714229681206347', 'NSGA-II_rank: 3', 'change: 0.09995641415808061', 'is_elite: False']\n", + "Id: 66_14 Identity: {'ancestor_count': 59, 'ancestor_ids': ['65_98', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_14', 'origin': '65_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.169950917313329', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2758012929199951', 'is_elite: False']\n", + "Id: 66_34 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '65_73'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_34', 'origin': '64_40~CUW~65_73#MGNP'} Metrics: ['ELUC: -6.190088192674424', 'NSGA-II_crowding_distance: 0.4803560209769281', 'NSGA-II_rank: 4', 'change: 0.12169096408584869', 'is_elite: False']\n", + "Id: 66_49 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_89', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_49', 'origin': '65_89~CUW~65_98#MGNP'} Metrics: ['ELUC: -6.190564161581225', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.25576895264305277', 'is_elite: False']\n", + "Id: 66_96 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_61', '65_73'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_96', 'origin': '65_61~CUW~65_73#MGNP'} Metrics: ['ELUC: -6.3634399247498985', 'NSGA-II_crowding_distance: 0.3921072977752881', 'NSGA-II_rank: 3', 'change: 0.10902448385129548', 'is_elite: False']\n", + "Id: 65_73 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_94', '1_1'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_73', 'origin': '64_94~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.486908796504281', 'NSGA-II_crowding_distance: 0.2463344920364455', 'NSGA-II_rank: 2', 'change: 0.09649064453990763', 'is_elite: False']\n", + "Id: 66_97 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_11', '65_61'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_97', 'origin': '65_11~CUW~65_61#MGNP'} Metrics: ['ELUC: -6.649431272586398', 'NSGA-II_crowding_distance: 0.32638296860316723', 'NSGA-II_rank: 1', 'change: 0.08807296262011674', 'is_elite: True']\n", + "Id: 66_12 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_61', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_12', 'origin': '65_61~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.50258539338771', 'NSGA-II_crowding_distance: 1.1176139266319836', 'NSGA-II_rank: 6', 'change: 0.23659968241021836', 'is_elite: False']\n", + "Id: 66_79 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '65_87'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_79', 'origin': '63_36~CUW~65_87#MGNP'} Metrics: ['ELUC: -8.16710964270556', 'NSGA-II_crowding_distance: 0.3195908788616607', 'NSGA-II_rank: 2', 'change: 0.12441047839744848', 'is_elite: False']\n", + "Id: 66_21 Identity: {'ancestor_count': 62, 'ancestor_ids': ['65_98', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_21', 'origin': '65_98~CUW~63_36#MGNP'} Metrics: ['ELUC: -8.232774871057826', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.24913922439518146', 'is_elite: False']\n", + "Id: 66_51 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_11', '64_40'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_51', 'origin': '65_11~CUW~64_40#MGNP'} Metrics: ['ELUC: -8.8240172240726', 'NSGA-II_crowding_distance: 1.3142272346003192', 'NSGA-II_rank: 5', 'change: 0.2014011892021677', 'is_elite: False']\n", + "Id: 66_64 Identity: {'ancestor_count': 64, 'ancestor_ids': ['63_36', '65_89'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_64', 'origin': '63_36~CUW~65_89#MGNP'} Metrics: ['ELUC: -8.847525890766667', 'NSGA-II_crowding_distance: 0.7183118978070334', 'NSGA-II_rank: 4', 'change: 0.18097740587199868', 'is_elite: False']\n", + "Id: 66_88 Identity: {'ancestor_count': 64, 'ancestor_ids': ['63_36', '65_11'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_88', 'origin': '63_36~CUW~65_11#MGNP'} Metrics: ['ELUC: -9.173937596127788', 'NSGA-II_crowding_distance: 0.4380762273558517', 'NSGA-II_rank: 3', 'change: 0.1591012499532854', 'is_elite: False']\n", + "Id: 66_84 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_72', '65_11'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_84', 'origin': '65_72~CUW~65_11#MGNP'} Metrics: ['ELUC: -9.232613027376372', 'NSGA-II_crowding_distance: 0.3254394503005467', 'NSGA-II_rank: 1', 'change: 0.11584873809704303', 'is_elite: True']\n", + "Id: 66_56 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_97', '65_72'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_56', 'origin': '65_97~CUW~65_72#MGNP'} Metrics: ['ELUC: -9.286437988959138', 'NSGA-II_crowding_distance: 0.1944091378461592', 'NSGA-II_rank: 2', 'change: 0.14012481621003642', 'is_elite: False']\n", + "Id: 66_37 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_98', '65_89'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_37', 'origin': '65_98~CUW~65_89#MGNP'} Metrics: ['ELUC: -9.418986396183923', 'NSGA-II_crowding_distance: 0.35681306033811744', 'NSGA-II_rank: 4', 'change: 0.24642401661096822', 'is_elite: False']\n", + "Id: 66_53 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_53', 'origin': '63_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.788562753097688', 'NSGA-II_crowding_distance: 0.10872538465995994', 'NSGA-II_rank: 4', 'change: 0.25149753854615586', 'is_elite: False']\n", + "Id: 66_38 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_11', '65_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_38', 'origin': '65_11~CUW~65_49#MGNP'} Metrics: ['ELUC: -9.919457613028955', 'NSGA-II_crowding_distance: 0.1578863526473503', 'NSGA-II_rank: 1', 'change: 0.12968348725326723', 'is_elite: False']\n", + "Id: 66_76 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_91', '65_97'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_76', 'origin': '65_91~CUW~65_97#MGNP'} Metrics: ['ELUC: -10.215143847437322', 'NSGA-II_crowding_distance: 0.23524880136703913', 'NSGA-II_rank: 2', 'change: 0.14592101818239234', 'is_elite: False']\n", + "Id: 66_46 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_79', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_46', 'origin': '65_79~CUW~63_36#MGNP'} Metrics: ['ELUC: -10.446815222732933', 'NSGA-II_crowding_distance: 0.5770592656086617', 'NSGA-II_rank: 3', 'change: 0.16661878218203305', 'is_elite: False']\n", + "Id: 66_31 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_89', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_31', 'origin': '65_89~CUW~65_98#MGNP'} Metrics: ['ELUC: -10.547189886932685', 'NSGA-II_crowding_distance: 0.27852280162462684', 'NSGA-II_rank: 4', 'change: 0.2570457904411105', 'is_elite: False']\n", + "Id: 65_91 Identity: {'ancestor_count': 62, 'ancestor_ids': ['64_94', '64_21'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_91', 'origin': '64_94~CUW~64_21#MGNP'} Metrics: ['ELUC: -10.8386360952982', 'NSGA-II_crowding_distance: 0.13226484558313034', 'NSGA-II_rank: 1', 'change: 0.1357038007433227', 'is_elite: False']\n", + "Id: 66_19 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_61', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_19', 'origin': '65_61~CUW~63_36#MGNP'} Metrics: ['ELUC: -11.065419289956612', 'NSGA-II_crowding_distance: 0.18304576702058983', 'NSGA-II_rank: 1', 'change: 0.14970104676423462', 'is_elite: False']\n", + "Id: 66_91 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_91', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.276047486809505', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2871359457856584', 'is_elite: False']\n", + "Id: 66_59 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_72', '65_97'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_59', 'origin': '65_72~CUW~65_97#MGNP'} Metrics: ['ELUC: -11.952575945889988', 'NSGA-II_crowding_distance: 0.4182124543442952', 'NSGA-II_rank: 2', 'change: 0.16341416727693323', 'is_elite: False']\n", + "Id: 66_78 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_97', '65_11'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_78', 'origin': '65_97~CUW~65_11#MGNP'} Metrics: ['ELUC: -12.424195383586678', 'NSGA-II_crowding_distance: 0.1272418430667846', 'NSGA-II_rank: 1', 'change: 0.16341314859190398', 'is_elite: False']\n", + "Id: 65_97 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_60', '64_21'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_97', 'origin': '64_60~CUW~64_21#MGNP'} Metrics: ['ELUC: -12.446347854838491', 'NSGA-II_crowding_distance: 0.0823688552131282', 'NSGA-II_rank: 1', 'change: 0.1642323937672648', 'is_elite: False']\n", + "Id: 66_68 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_11', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_68', 'origin': '65_11~CUW~63_36#MGNP'} Metrics: ['ELUC: -12.86248467633504', 'NSGA-II_crowding_distance: 0.1639545847370893', 'NSGA-II_rank: 1', 'change: 0.1805522749812958', 'is_elite: False']\n", + "Id: 66_29 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_98', '65_89'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_29', 'origin': '65_98~CUW~65_89#MGNP'} Metrics: ['ELUC: -13.028428679439926', 'NSGA-II_crowding_distance: 0.5790148077180787', 'NSGA-II_rank: 4', 'change: 0.27419093006868833', 'is_elite: False']\n", + "Id: 66_82 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_74', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_82', 'origin': '64_74~CUW~63_36#MGNP'} Metrics: ['ELUC: -13.416067317312507', 'NSGA-II_crowding_distance: 0.12706926683445294', 'NSGA-II_rank: 1', 'change: 0.19669634990752075', 'is_elite: False']\n", + "Id: 66_86 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_49', '65_72'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_86', 'origin': '65_49~CUW~65_72#MGNP'} Metrics: ['ELUC: -13.786694940213756', 'NSGA-II_crowding_distance: 0.37134269263042213', 'NSGA-II_rank: 2', 'change: 0.20436005007193134', 'is_elite: False']\n", + "Id: 66_13 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_49', '65_91'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_13', 'origin': '65_49~CUW~65_91#MGNP'} Metrics: ['ELUC: -13.909210339668052', 'NSGA-II_crowding_distance: 0.0495490889451452', 'NSGA-II_rank: 1', 'change: 0.20070365531243803', 'is_elite: False']\n", + "Id: 66_75 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_91', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_75', 'origin': '65_91~CUW~63_36#MGNP'} Metrics: ['ELUC: -13.990286333243182', 'NSGA-II_crowding_distance: 0.06167751347094992', 'NSGA-II_rank: 1', 'change: 0.20173602016005002', 'is_elite: False']\n", + "Id: 66_52 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_79', '64_40'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_52', 'origin': '65_79~CUW~64_40#MGNP'} Metrics: ['ELUC: -14.001595190019259', 'NSGA-II_crowding_distance: 0.9057882813857596', 'NSGA-II_rank: 3', 'change: 0.24234613006202352', 'is_elite: False']\n", + "Id: 66_33 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_33', 'origin': '64_40~CUW~63_36#MGNP'} Metrics: ['ELUC: -14.003467963230651', 'NSGA-II_crowding_distance: 0.2581656186885194', 'NSGA-II_rank: 2', 'change: 0.231643604986724', 'is_elite: False']\n", + "Id: 66_50 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_50', 'origin': '63_36~CUW~63_36#MGNP'} Metrics: ['ELUC: -14.234710871936137', 'NSGA-II_crowding_distance: 0.0682948644290198', 'NSGA-II_rank: 1', 'change: 0.21358300646871145', 'is_elite: False']\n", + "Id: 66_45 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_98', '65_97'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_45', 'origin': '65_98~CUW~65_97#MGNP'} Metrics: ['ELUC: -14.290211490966081', 'NSGA-II_crowding_distance: 0.1489002526557929', 'NSGA-II_rank: 2', 'change: 0.2652456130833211', 'is_elite: False']\n", + "Id: 66_63 Identity: {'ancestor_count': 59, 'ancestor_ids': ['1_1', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_63', 'origin': '1_1~CUW~65_98#MGNP'} Metrics: ['ELUC: -14.38597920557904', 'NSGA-II_crowding_distance: 0.11722093452068888', 'NSGA-II_rank: 2', 'change: 0.26541690308462057', 'is_elite: False']\n", + "Id: 63_36 Identity: {'ancestor_count': 61, 'ancestor_ids': ['61_51', '62_81'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_36', 'origin': '61_51~CUW~62_81#MGNP'} Metrics: ['ELUC: -14.475667047678117', 'NSGA-II_crowding_distance: 0.19862481622358386', 'NSGA-II_rank: 1', 'change: 0.2138766254090932', 'is_elite: True']\n", + "Id: 66_58 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_98', '64_40'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_58', 'origin': '65_98~CUW~64_40#MGNP'} Metrics: ['ELUC: -15.181777960155925', 'NSGA-II_crowding_distance: 0.1287831785135218', 'NSGA-II_rank: 2', 'change: 0.28322253394572483', 'is_elite: False']\n", + "Id: 66_22 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_91', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_22', 'origin': '65_91~CUW~65_98#MGNP'} Metrics: ['ELUC: -15.35549592658288', 'NSGA-II_crowding_distance: 0.061339985337113434', 'NSGA-II_rank: 2', 'change: 0.2853127046165649', 'is_elite: False']\n", + "Id: 66_89 Identity: {'ancestor_count': 59, 'ancestor_ids': ['65_98', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_89', 'origin': '65_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.548217519152066', 'NSGA-II_crowding_distance: 0.16002735733189366', 'NSGA-II_rank: 2', 'change: 0.2940895088462997', 'is_elite: False']\n", + "Id: 64_40 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_54', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_40', 'origin': '63_54~CUW~63_18#MGNP'} Metrics: ['ELUC: -15.65352726135874', 'NSGA-II_crowding_distance: 0.3446140245590732', 'NSGA-II_rank: 1', 'change: 0.2487704737891359', 'is_elite: True']\n", + "Id: 66_61 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_61', 'origin': '63_36~CUW~65_98#MGNP'} Metrics: ['ELUC: -16.47929590075316', 'NSGA-II_crowding_distance: 0.2610771805363247', 'NSGA-II_rank: 1', 'change: 0.2826995713071776', 'is_elite: True']\n", + "Id: 66_72 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_72', 'origin': '63_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.15179421930696', 'NSGA-II_crowding_distance: 0.14225779892897727', 'NSGA-II_rank: 2', 'change: 0.30140803316717574', 'is_elite: False']\n", + "Id: 66_100 Identity: {'ancestor_count': 64, 'ancestor_ids': ['2_49', '65_61'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_100', 'origin': '2_49~CUW~65_61#MGNP'} Metrics: ['ELUC: -17.226389602914672', 'NSGA-II_crowding_distance: 0.12622659865868058', 'NSGA-II_rank: 1', 'change: 0.2999781275506614', 'is_elite: False']\n", + "Id: 66_54 Identity: {'ancestor_count': 56, 'ancestor_ids': ['65_87', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_54', 'origin': '65_87~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.27786686830094', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.30428207654132916', 'is_elite: False']\n", + "Id: 66_40 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_98', '65_73'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_40', 'origin': '65_98~CUW~65_73#MGNP'} Metrics: ['ELUC: -17.538480081365037', 'NSGA-II_crowding_distance: 0.030691781103443855', 'NSGA-II_rank: 2', 'change: 0.30265986478953183', 'is_elite: False']\n", + "Id: 66_94 Identity: {'ancestor_count': 62, 'ancestor_ids': ['2_49', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_94', 'origin': '2_49~CUW~63_36#MGNP'} Metrics: ['ELUC: -17.56196673340353', 'NSGA-II_crowding_distance: 0.03129681455764995', 'NSGA-II_rank: 1', 'change: 0.3019895176335975', 'is_elite: False']\n", + "Id: 66_42 Identity: {'ancestor_count': 63, 'ancestor_ids': ['2_49', '64_40'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_42', 'origin': '2_49~CUW~64_40#MGNP'} Metrics: ['ELUC: -17.595482373030205', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3030294180638124', 'is_elite: False']\n", + "Id: 66_15 Identity: {'ancestor_count': 63, 'ancestor_ids': ['2_49', '65_91'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_15', 'origin': '2_49~CUW~65_91#MGNP'} Metrics: ['ELUC: -17.597012211358447', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302629576648415', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 65_98 Identity: {'ancestor_count': 58, 'ancestor_ids': ['2_49', '64_37'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_98', 'origin': '2_49~CUW~64_37#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 66_11 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_97', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_11', 'origin': '65_97~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 66_26 Identity: {'ancestor_count': 64, 'ancestor_ids': ['2_49', '65_72'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_26', 'origin': '2_49~CUW~65_72#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 66_57 Identity: {'ancestor_count': 64, 'ancestor_ids': ['2_49', '65_61'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_57', 'origin': '2_49~CUW~65_61#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 66_85 Identity: {'ancestor_count': 62, 'ancestor_ids': ['2_49', '63_36'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_85', 'origin': '2_49~CUW~63_36#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 66_99 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_99', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 66.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 67...:\n", + "PopulationResponse:\n", + " Generation: 67\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/67/20240220-034419\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 67 and asking ESP for generation 68...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 67 data persisted.\n", + "Evaluated candidates:\n", + "Id: 67_57 Identity: {'ancestor_count': 65, 'ancestor_ids': ['2_49', '66_38'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_57', 'origin': '2_49~CUW~66_38#MGNP'} Metrics: ['ELUC: 23.816218548717682', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30376480863650146', 'is_elite: False']\n", + "Id: 67_19 Identity: {'ancestor_count': 63, 'ancestor_ids': ['2_49', '64_40'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_19', 'origin': '2_49~CUW~64_40#MGNP'} Metrics: ['ELUC: 9.590661294890795', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2695301078619214', 'is_elite: False']\n", + "Id: 67_17 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_99', '66_69'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_17', 'origin': '66_99~CUW~66_69#MGNP'} Metrics: ['ELUC: 6.397876424240281', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26266127691385094', 'is_elite: False']\n", + "Id: 67_44 Identity: {'ancestor_count': 65, 'ancestor_ids': ['64_40', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_44', 'origin': '64_40~CUW~66_84#MGNP'} Metrics: ['ELUC: 2.4729211219771345', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.11727131860281238', 'is_elite: False']\n", + "Id: 67_83 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '66_99'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_83', 'origin': '64_40~CUW~66_99#MGNP'} Metrics: ['ELUC: 1.8454009342629945', 'NSGA-II_crowding_distance: 1.3808250021070503', 'NSGA-II_rank: 7', 'change: 0.2515928890653773', 'is_elite: False']\n", + "Id: 67_99 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '1_1'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_99', 'origin': '66_97~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.5211202049098325', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06637197717119758', 'is_elite: False']\n", + "Id: 67_32 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_84', '1_1'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_32', 'origin': '66_84~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.1588181158356285', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08282631967561363', 'is_elite: False']\n", + "Id: 67_41 Identity: {'ancestor_count': 65, 'ancestor_ids': ['2_49', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_41', 'origin': '2_49~CUW~66_74#MGNP'} Metrics: ['ELUC: 0.9909313957534791', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.3165346763906422', 'is_elite: False']\n", + "Id: 67_27 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_69', '66_38'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_27', 'origin': '66_69~CUW~66_38#MGNP'} Metrics: ['ELUC: 0.9199616109698328', 'NSGA-II_crowding_distance: 0.5457740173391163', 'NSGA-II_rank: 6', 'change: 0.09420488300150238', 'is_elite: False']\n", + "Id: 67_45 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_61', '1_1'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_45', 'origin': '65_61~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.8755657108877763', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08185314397742088', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 67_61 Identity: {'ancestor_count': 63, 'ancestor_ids': ['1_1', '65_91'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_61', 'origin': '1_1~CUW~65_91#MGNP'} Metrics: ['ELUC: -0.09260401976606457', 'NSGA-II_crowding_distance: 0.33856906548527965', 'NSGA-II_rank: 4', 'change: 0.07914184850322352', 'is_elite: False']\n", + "Id: 67_12 Identity: {'ancestor_count': 63, 'ancestor_ids': ['1_1', '64_40'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_12', 'origin': '1_1~CUW~64_40#MGNP'} Metrics: ['ELUC: -0.9977250630655143', 'NSGA-II_crowding_distance: 1.2584144013939669', 'NSGA-II_rank: 6', 'change: 0.15909843655607117', 'is_elite: False']\n", + "Id: 67_63 Identity: {'ancestor_count': 65, 'ancestor_ids': ['1_1', '66_78'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_63', 'origin': '1_1~CUW~66_78#MGNP'} Metrics: ['ELUC: -1.0080027354206567', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.061130475074927894', 'is_elite: False']\n", + "Id: 67_43 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_84', '66_99'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_43', 'origin': '66_84~CUW~66_99#MGNP'} Metrics: ['ELUC: -1.0518999696972056', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.34544297268528346', 'is_elite: False']\n", + "Id: 66_74 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_72', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_74', 'origin': '65_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2237585094391712', 'NSGA-II_crowding_distance: 0.2765703363905077', 'NSGA-II_rank: 1', 'change: 0.0392809679484303', 'is_elite: True']\n", + "Id: 67_86 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_86', 'origin': '66_97~CUW~66_74#MGNP'} Metrics: ['ELUC: -1.4837078192010733', 'NSGA-II_crowding_distance: 0.08851703352056003', 'NSGA-II_rank: 2', 'change: 0.06127759186624699', 'is_elite: False']\n", + "Id: 67_55 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_79', '65_79'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_55', 'origin': '65_79~CUW~65_79#MGNP'} Metrics: ['ELUC: -1.525221376246451', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06623962511847319', 'is_elite: False']\n", + "Id: 67_42 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_79', '64_40'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_42', 'origin': '65_79~CUW~64_40#MGNP'} Metrics: ['ELUC: -1.8108104494763222', 'NSGA-II_crowding_distance: 0.6503822293780233', 'NSGA-II_rank: 4', 'change: 0.09508915943299903', 'is_elite: False']\n", + "Id: 67_18 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_18', 'origin': '65_79~CUW~66_74#MGNP'} Metrics: ['ELUC: -1.9715789697939752', 'NSGA-II_crowding_distance: 0.1859180655533707', 'NSGA-II_rank: 1', 'change: 0.05396223312155555', 'is_elite: False']\n", + "Id: 67_84 Identity: {'ancestor_count': 64, 'ancestor_ids': ['1_1', '65_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_84', 'origin': '1_1~CUW~65_61#MGNP'} Metrics: ['ELUC: -2.1784362764031022', 'NSGA-II_crowding_distance: 0.18023694963114745', 'NSGA-II_rank: 3', 'change: 0.07119625662096032', 'is_elite: False']\n", + "Id: 65_79 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_98', '64_67'], 'birth_generation': 65, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '65_79', 'origin': '64_98~CUW~64_67#MGNP'} Metrics: ['ELUC: -2.185104812492197', 'NSGA-II_crowding_distance: 0.08384757119422853', 'NSGA-II_rank: 2', 'change: 0.0653780009856818', 'is_elite: False']\n", + "Id: 67_80 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_80', 'origin': '66_97~CUW~66_84#MGNP'} Metrics: ['ELUC: -2.200537931158231', 'NSGA-II_crowding_distance: 0.17511717347715233', 'NSGA-II_rank: 2', 'change: 0.07110704448809406', 'is_elite: False']\n", + "Id: 67_65 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '65_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_65', 'origin': '66_74~CUW~65_61#MGNP'} Metrics: ['ELUC: -3.020481855950209', 'NSGA-II_crowding_distance: 0.28239709795229206', 'NSGA-II_rank: 3', 'change: 0.0830512848790787', 'is_elite: False']\n", + "Id: 67_35 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_35', 'origin': '65_79~CUW~66_74#MGNP'} Metrics: ['ELUC: -3.2420300459574194', 'NSGA-II_crowding_distance: 0.27573787051052434', 'NSGA-II_rank: 1', 'change: 0.06050408546776139', 'is_elite: True']\n", + "Id: 67_81 Identity: {'ancestor_count': 62, 'ancestor_ids': ['1_1', '63_36'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_81', 'origin': '1_1~CUW~63_36#MGNP'} Metrics: ['ELUC: -3.352133351440882', 'NSGA-II_crowding_distance: 1.2923030264490327', 'NSGA-II_rank: 5', 'change: 0.12148454618540269', 'is_elite: False']\n", + "Id: 67_98 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_98', 'origin': '64_40~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.829949294590886', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.28905830031109264', 'is_elite: False']\n", + "Id: 67_49 Identity: {'ancestor_count': 65, 'ancestor_ids': ['1_1', '66_100'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_49', 'origin': '1_1~CUW~66_100#MGNP'} Metrics: ['ELUC: -4.065248600885316', 'NSGA-II_crowding_distance: 1.1985414358683628', 'NSGA-II_rank: 7', 'change: 0.2682113536697477', 'is_elite: False']\n", + "Id: 67_40 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '66_19'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_40', 'origin': '66_74~CUW~66_19#MGNP'} Metrics: ['ELUC: -4.168032094244106', 'NSGA-II_crowding_distance: 0.21793245509588158', 'NSGA-II_rank: 2', 'change: 0.07882312205418257', 'is_elite: False']\n", + "Id: 67_33 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_33', 'origin': '66_97~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.935324735417923', 'NSGA-II_crowding_distance: 0.8400544013948622', 'NSGA-II_rank: 6', 'change: 0.25428239549628845', 'is_elite: False']\n", + "Id: 67_15 Identity: {'ancestor_count': 65, 'ancestor_ids': ['1_1', '66_97'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_15', 'origin': '1_1~CUW~66_97#MGNP'} Metrics: ['ELUC: -4.9795755695101365', 'NSGA-II_crowding_distance: 0.255538982846582', 'NSGA-II_rank: 3', 'change: 0.0900851256344445', 'is_elite: False']\n", + "Id: 67_37 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_19', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_37', 'origin': '66_19~CUW~66_84#MGNP'} Metrics: ['ELUC: -5.103813939545255', 'NSGA-II_crowding_distance: 0.16191979795241634', 'NSGA-II_rank: 2', 'change: 0.08148874177496705', 'is_elite: False']\n", + "Id: 67_88 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_88', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.171342796667845', 'NSGA-II_crowding_distance: 0.1826585771022222', 'NSGA-II_rank: 6', 'change: 0.261221074530168', 'is_elite: False']\n", + "Id: 67_75 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_19'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_75', 'origin': '65_79~CUW~66_19#MGNP'} Metrics: ['ELUC: -5.418067400507282', 'NSGA-II_crowding_distance: 0.2861927077872659', 'NSGA-II_rank: 1', 'change: 0.07774829792440713', 'is_elite: True']\n", + "Id: 67_78 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_79', '66_99'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_78', 'origin': '65_79~CUW~66_99#MGNP'} Metrics: ['ELUC: -5.874365611147386', 'NSGA-II_crowding_distance: 0.6141715812660214', 'NSGA-II_rank: 6', 'change: 0.2759235616980909', 'is_elite: False']\n", + "Id: 67_76 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '65_79'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_76', 'origin': '66_97~CUW~65_79#MGNP'} Metrics: ['ELUC: -5.948955811918179', 'NSGA-II_crowding_distance: 0.1696596834394981', 'NSGA-II_rank: 3', 'change: 0.09374221776130101', 'is_elite: False']\n", + "Id: 67_97 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_61', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_97', 'origin': '65_61~CUW~66_74#MGNP'} Metrics: ['ELUC: -6.014501184593244', 'NSGA-II_crowding_distance: 0.1674786353077557', 'NSGA-II_rank: 2', 'change: 0.0910656898573633', 'is_elite: False']\n", + "Id: 67_31 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_91', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_31', 'origin': '65_91~CUW~66_74#MGNP'} Metrics: ['ELUC: -6.211597435184135', 'NSGA-II_crowding_distance: 0.09340159405268939', 'NSGA-II_rank: 3', 'change: 0.10876326803991616', 'is_elite: False']\n", + "Id: 67_16 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_78', '65_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_16', 'origin': '66_78~CUW~65_61#MGNP'} Metrics: ['ELUC: -6.286209048365426', 'NSGA-II_crowding_distance: 0.2501354959390173', 'NSGA-II_rank: 3', 'change: 0.10956897188095177', 'is_elite: False']\n", + "Id: 67_92 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '66_97'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_92', 'origin': '66_74~CUW~66_97#MGNP'} Metrics: ['ELUC: -6.430447326418738', 'NSGA-II_crowding_distance: 0.1239203737446116', 'NSGA-II_rank: 2', 'change: 0.10265588001049747', 'is_elite: False']\n", + "Id: 66_97 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_11', '65_61'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_97', 'origin': '65_11~CUW~65_61#MGNP'} Metrics: ['ELUC: -6.649431272586398', 'NSGA-II_crowding_distance: 0.13586510544628697', 'NSGA-II_rank: 1', 'change: 0.08807296262011674', 'is_elite: False']\n", + "Id: 67_90 Identity: {'ancestor_count': 65, 'ancestor_ids': ['1_1', '66_38'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_90', 'origin': '1_1~CUW~66_38#MGNP'} Metrics: ['ELUC: -6.652037992991116', 'NSGA-II_crowding_distance: 0.2234590602508558', 'NSGA-II_rank: 2', 'change: 0.11174454686095064', 'is_elite: False']\n", + "Id: 67_95 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '65_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_95', 'origin': '66_97~CUW~65_61#MGNP'} Metrics: ['ELUC: -7.0786689452865215', 'NSGA-II_crowding_distance: 0.25278698444760245', 'NSGA-II_rank: 1', 'change: 0.09010649759159399', 'is_elite: True']\n", + "Id: 67_36 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_36', 'origin': '65_79~CUW~66_84#MGNP'} Metrics: ['ELUC: -7.539650726641594', 'NSGA-II_crowding_distance: 0.4870479611396072', 'NSGA-II_rank: 4', 'change: 0.11934473397554395', 'is_elite: False']\n", + "Id: 67_73 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_73', 'origin': '65_79~CUW~66_84#MGNP'} Metrics: ['ELUC: -7.63733229798367', 'NSGA-II_crowding_distance: 0.08088241482419178', 'NSGA-II_rank: 4', 'change: 0.12162569364474846', 'is_elite: False']\n", + "Id: 67_64 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_61', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_64', 'origin': '66_61~CUW~66_74#MGNP'} Metrics: ['ELUC: -8.34988394480165', 'NSGA-II_crowding_distance: 1.161543672656852', 'NSGA-II_rank: 5', 'change: 0.21222964288120358', 'is_elite: False']\n", + "Id: 67_66 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_66', 'origin': '66_74~CUW~66_84#MGNP'} Metrics: ['ELUC: -8.525323447151388', 'NSGA-II_crowding_distance: 0.08267733716454705', 'NSGA-II_rank: 4', 'change: 0.12349304517817997', 'is_elite: False']\n", + "Id: 67_79 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_84', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_79', 'origin': '66_84~CUW~66_84#MGNP'} Metrics: ['ELUC: -8.645062890903256', 'NSGA-II_crowding_distance: 0.3308160256968906', 'NSGA-II_rank: 4', 'change: 0.12586343143432813', 'is_elite: False']\n", + "Id: 67_85 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '65_79'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_85', 'origin': '66_97~CUW~65_79#MGNP'} Metrics: ['ELUC: -9.202630357812577', 'NSGA-II_crowding_distance: 0.591840829777208', 'NSGA-II_rank: 3', 'change: 0.11720430486352104', 'is_elite: False']\n", + "Id: 66_84 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_72', '65_11'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_84', 'origin': '65_72~CUW~65_11#MGNP'} Metrics: ['ELUC: -9.232613027376372', 'NSGA-II_crowding_distance: 0.23904683858401624', 'NSGA-II_rank: 2', 'change: 0.11584873809704303', 'is_elite: False']\n", + "Id: 67_46 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_46', 'origin': '63_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.236002766677421', 'NSGA-II_crowding_distance: 0.7076969735509672', 'NSGA-II_rank: 5', 'change: 0.27571121581705366', 'is_elite: False']\n", + "Id: 67_14 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_19', '66_38'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_14', 'origin': '66_19~CUW~66_38#MGNP'} Metrics: ['ELUC: -9.613468483625022', 'NSGA-II_crowding_distance: 0.14517814050528277', 'NSGA-II_rank: 2', 'change: 0.1263856191374223', 'is_elite: False']\n", + "Id: 67_100 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_78', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_100', 'origin': '66_78~CUW~66_84#MGNP'} Metrics: ['ELUC: -9.618489777027925', 'NSGA-II_crowding_distance: 0.32961663845432776', 'NSGA-II_rank: 1', 'change: 0.11311312747406431', 'is_elite: True']\n", + "Id: 67_23 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_23', 'origin': '66_97~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.673903145341455', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29641516034942206', 'is_elite: False']\n", + "Id: 67_47 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_19'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_47', 'origin': '65_79~CUW~66_19#MGNP'} Metrics: ['ELUC: -9.922678983680015', 'NSGA-II_crowding_distance: 0.10638642096657164', 'NSGA-II_rank: 2', 'change: 0.1409036784069902', 'is_elite: False']\n", + "Id: 67_77 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_19', '66_19'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_77', 'origin': '66_19~CUW~66_19#MGNP'} Metrics: ['ELUC: -10.226947264975042', 'NSGA-II_crowding_distance: 0.18983598489226933', 'NSGA-II_rank: 2', 'change: 0.14317399527085728', 'is_elite: False']\n", + "Id: 67_28 Identity: {'ancestor_count': 63, 'ancestor_ids': ['65_91', '63_36'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_28', 'origin': '65_91~CUW~63_36#MGNP'} Metrics: ['ELUC: -10.413453256461235', 'NSGA-II_crowding_distance: 0.6329271421574589', 'NSGA-II_rank: 4', 'change: 0.17110419490804846', 'is_elite: False']\n", + "Id: 67_13 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_13', 'origin': '66_97~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.608076923214831', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2932310274609375', 'is_elite: False']\n", + "Id: 67_56 Identity: {'ancestor_count': 63, 'ancestor_ids': ['66_61', '65_91'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_56', 'origin': '66_61~CUW~65_91#MGNP'} Metrics: ['ELUC: -10.679016514764418', 'NSGA-II_crowding_distance: 0.3801834667401144', 'NSGA-II_rank: 4', 'change: 0.239522406873726', 'is_elite: False']\n", + "Id: 67_67 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_38', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_67', 'origin': '66_38~CUW~66_84#MGNP'} Metrics: ['ELUC: -10.75955357180204', 'NSGA-II_crowding_distance: 0.23497603397146252', 'NSGA-II_rank: 1', 'change: 0.12599101035060642', 'is_elite: False']\n", + "Id: 67_53 Identity: {'ancestor_count': 64, 'ancestor_ids': ['2_49', '65_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_53', 'origin': '2_49~CUW~65_61#MGNP'} Metrics: ['ELUC: -10.81330727430642', 'NSGA-II_crowding_distance: 0.2072483978746289', 'NSGA-II_rank: 4', 'change: 0.25112711034459684', 'is_elite: False']\n", + "Id: 67_22 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '63_36'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_22', 'origin': '66_74~CUW~63_36#MGNP'} Metrics: ['ELUC: -11.088766235250676', 'NSGA-II_crowding_distance: 0.3934489157846526', 'NSGA-II_rank: 3', 'change: 0.16651926119478477', 'is_elite: False']\n", + "Id: 67_21 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_68', '1_1'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_21', 'origin': '66_68~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.397380651666651', 'NSGA-II_crowding_distance: 0.10084271559483249', 'NSGA-II_rank: 3', 'change: 0.17128851906041878', 'is_elite: False']\n", + "Id: 67_60 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_23', '66_19'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_60', 'origin': '66_23~CUW~66_19#MGNP'} Metrics: ['ELUC: -11.422714386977695', 'NSGA-II_crowding_distance: 0.20603425836023148', 'NSGA-II_rank: 2', 'change: 0.16495037894287706', 'is_elite: False']\n", + "Id: 67_25 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_78', '65_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_25', 'origin': '66_78~CUW~65_61#MGNP'} Metrics: ['ELUC: -11.436046712896506', 'NSGA-II_crowding_distance: 0.20851529937135074', 'NSGA-II_rank: 1', 'change: 0.1523802381085673', 'is_elite: False']\n", + "Id: 67_39 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '66_99'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_39', 'origin': '63_36~CUW~66_99#MGNP'} Metrics: ['ELUC: -11.891921498201889', 'NSGA-II_crowding_distance: 0.30335136715586575', 'NSGA-II_rank: 4', 'change: 0.2689202239602599', 'is_elite: False']\n", + "Id: 67_59 Identity: {'ancestor_count': 65, 'ancestor_ids': ['63_36', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_59', 'origin': '63_36~CUW~66_74#MGNP'} Metrics: ['ELUC: -11.944978412656999', 'NSGA-II_crowding_distance: 0.3540927701823027', 'NSGA-II_rank: 3', 'change: 0.17560653560358763', 'is_elite: False']\n", + "Id: 67_72 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_38', '66_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_72', 'origin': '66_38~CUW~66_61#MGNP'} Metrics: ['ELUC: -12.02806036039096', 'NSGA-II_crowding_distance: 0.4075706522224187', 'NSGA-II_rank: 3', 'change: 0.2418220599792928', 'is_elite: False']\n", + "Id: 67_96 Identity: {'ancestor_count': 65, 'ancestor_ids': ['63_36', '66_68'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_96', 'origin': '63_36~CUW~66_68#MGNP'} Metrics: ['ELUC: -12.034838719030887', 'NSGA-II_crowding_distance: 0.26959795502565526', 'NSGA-II_rank: 2', 'change: 0.16664991009007563', 'is_elite: False']\n", + "Id: 67_52 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_19', '66_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_52', 'origin': '66_19~CUW~66_61#MGNP'} Metrics: ['ELUC: -12.156376130276456', 'NSGA-II_crowding_distance: 0.1500922976972572', 'NSGA-II_rank: 3', 'change: 0.2651578272772518', 'is_elite: False']\n", + "Id: 67_54 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_84', '66_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_54', 'origin': '66_84~CUW~66_61#MGNP'} Metrics: ['ELUC: -12.271727770191426', 'NSGA-II_crowding_distance: 0.2516179323999395', 'NSGA-II_rank: 3', 'change: 0.27210443798382966', 'is_elite: False']\n", + "Id: 67_26 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_78', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_26', 'origin': '66_78~CUW~66_84#MGNP'} Metrics: ['ELUC: -12.503942449928555', 'NSGA-II_crowding_distance: 0.2850643019599135', 'NSGA-II_rank: 1', 'change: 0.1586045119624284', 'is_elite: True']\n", + "Id: 67_51 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_84', '63_36'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_51', 'origin': '66_84~CUW~63_36#MGNP'} Metrics: ['ELUC: -12.804336805879794', 'NSGA-II_crowding_distance: 0.5329271814297644', 'NSGA-II_rank: 2', 'change: 0.21001730225489745', 'is_elite: False']\n", + "Id: 67_89 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_61', '66_99'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_89', 'origin': '65_61~CUW~66_99#MGNP'} Metrics: ['ELUC: -12.821898993427835', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2925497310428427', 'is_elite: False']\n", + "Id: 67_29 Identity: {'ancestor_count': 63, 'ancestor_ids': ['2_49', '66_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_29', 'origin': '2_49~CUW~66_61#MGNP'} Metrics: ['ELUC: -12.982855963988273', 'NSGA-II_crowding_distance: 0.2515300961784783', 'NSGA-II_rank: 4', 'change: 0.2885208453833679', 'is_elite: False']\n", + "Id: 67_68 Identity: {'ancestor_count': 64, 'ancestor_ids': ['66_82', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_68', 'origin': '66_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.696503006616096', 'NSGA-II_crowding_distance: 0.3922413708973287', 'NSGA-II_rank: 2', 'change: 0.27133003060410155', 'is_elite: False']\n", + "Id: 67_69 Identity: {'ancestor_count': 65, 'ancestor_ids': ['63_36', '66_78'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_69', 'origin': '63_36~CUW~66_78#MGNP'} Metrics: ['ELUC: -13.9681855204079', 'NSGA-II_crowding_distance: 0.29738443328151487', 'NSGA-II_rank: 1', 'change: 0.1944658970894259', 'is_elite: True']\n", + "Id: 67_71 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_84', '66_99'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_71', 'origin': '66_84~CUW~66_99#MGNP'} Metrics: ['ELUC: -14.252633214852224', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.29189400634229523', 'is_elite: False']\n", + "Id: 67_94 Identity: {'ancestor_count': 65, 'ancestor_ids': ['2_49', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_94', 'origin': '2_49~CUW~66_74#MGNP'} Metrics: ['ELUC: -14.286688022350258', 'NSGA-II_crowding_distance: 0.3319011753566978', 'NSGA-II_rank: 3', 'change: 0.2879306118567859', 'is_elite: False']\n", + "Id: 67_24 Identity: {'ancestor_count': 64, 'ancestor_ids': ['66_61', '65_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_24', 'origin': '66_61~CUW~65_61#MGNP'} Metrics: ['ELUC: -14.4471390541927', 'NSGA-II_crowding_distance: 0.17655357924971277', 'NSGA-II_rank: 2', 'change: 0.2809420208129742', 'is_elite: False']\n", + "Id: 63_36 Identity: {'ancestor_count': 61, 'ancestor_ids': ['61_51', '62_81'], 'birth_generation': 63, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '63_36', 'origin': '61_51~CUW~62_81#MGNP'} Metrics: ['ELUC: -14.475667047678117', 'NSGA-II_crowding_distance: 0.22208098467151607', 'NSGA-II_rank: 1', 'change: 0.2138766254090932', 'is_elite: False']\n", + "Id: 67_58 Identity: {'ancestor_count': 63, 'ancestor_ids': ['64_40', '64_40'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_58', 'origin': '64_40~CUW~64_40#MGNP'} Metrics: ['ELUC: -15.249319870603447', 'NSGA-II_crowding_distance: 0.16903475967250603', 'NSGA-II_rank: 1', 'change: 0.23898866897414692', 'is_elite: False']\n", + "Id: 67_70 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_84', '66_99'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_70', 'origin': '66_84~CUW~66_99#MGNP'} Metrics: ['ELUC: -15.558529794333928', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29439191377383034', 'is_elite: False']\n", + "Id: 67_11 Identity: {'ancestor_count': 65, 'ancestor_ids': ['64_40', '66_97'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_11', 'origin': '64_40~CUW~66_97#MGNP'} Metrics: ['ELUC: -15.635773210001986', 'NSGA-II_crowding_distance: 0.05577269346273425', 'NSGA-II_rank: 1', 'change: 0.2446254715676828', 'is_elite: False']\n", + "Id: 64_40 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_54', '63_18'], 'birth_generation': 64, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '64_40', 'origin': '63_54~CUW~63_18#MGNP'} Metrics: ['ELUC: -15.65352726135874', 'NSGA-II_crowding_distance: 0.11252757641797412', 'NSGA-II_rank: 1', 'change: 0.2487704737891359', 'is_elite: False']\n", + "Id: 67_62 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_100', '66_69'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_62', 'origin': '66_100~CUW~66_69#MGNP'} Metrics: ['ELUC: -15.819826838749416', 'NSGA-II_crowding_distance: 0.10561709831593535', 'NSGA-II_rank: 2', 'change: 0.2830754215372884', 'is_elite: False']\n", + "Id: 67_87 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_61', '66_19'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_87', 'origin': '66_61~CUW~66_19#MGNP'} Metrics: ['ELUC: -15.89128159338018', 'NSGA-II_crowding_distance: 0.06678531946071528', 'NSGA-II_rank: 2', 'change: 0.28543204441784137', 'is_elite: False']\n", + "Id: 67_91 Identity: {'ancestor_count': 62, 'ancestor_ids': ['66_99', '63_36'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_91', 'origin': '66_99~CUW~63_36#MGNP'} Metrics: ['ELUC: -16.26304805315435', 'NSGA-II_crowding_distance: 0.09734045433910779', 'NSGA-II_rank: 2', 'change: 0.29276730020152675', 'is_elite: False']\n", + "Id: 67_93 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '64_40'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_93', 'origin': '66_97~CUW~64_40#MGNP'} Metrics: ['ELUC: -16.30501250428286', 'NSGA-II_crowding_distance: 0.16067770310756035', 'NSGA-II_rank: 1', 'change: 0.26684399556121285', 'is_elite: False']\n", + "Id: 67_50 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_50', 'origin': '63_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.368402483091536', 'NSGA-II_crowding_distance: 0.12279202325424793', 'NSGA-II_rank: 2', 'change: 0.30202058749661564', 'is_elite: False']\n", + "Id: 66_61 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '65_98'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_61', 'origin': '63_36~CUW~65_98#MGNP'} Metrics: ['ELUC: -16.47929590075316', 'NSGA-II_crowding_distance: 0.09217035664953162', 'NSGA-II_rank: 1', 'change: 0.2826995713071776', 'is_elite: False']\n", + "Id: 67_74 Identity: {'ancestor_count': 63, 'ancestor_ids': ['66_61', '63_36'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_74', 'origin': '66_61~CUW~63_36#MGNP'} Metrics: ['ELUC: -16.790184140720907', 'NSGA-II_crowding_distance: 0.13168392071727364', 'NSGA-II_rank: 1', 'change: 0.28611206372657577', 'is_elite: False']\n", + "Id: 67_82 Identity: {'ancestor_count': 65, 'ancestor_ids': ['2_49', '66_100'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_82', 'origin': '2_49~CUW~66_100#MGNP'} Metrics: ['ELUC: -17.59689025975395', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030200959254767', 'is_elite: False']\n", + "Id: 67_48 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_48', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597231922975535', 'NSGA-II_crowding_distance: 0.10257762380547572', 'NSGA-II_rank: 1', 'change: 0.30301939978140247', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 66_99 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_99', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 67_20 Identity: {'ancestor_count': 3, 'ancestor_ids': ['66_99', '66_99'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_20', 'origin': '66_99~CUW~66_99#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 67_30 Identity: {'ancestor_count': 63, 'ancestor_ids': ['66_99', '66_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_30', 'origin': '66_99~CUW~66_61#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 67_34 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_34', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 67_38 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_38', 'origin': '66_74~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 67.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 68...:\n", + "PopulationResponse:\n", + " Generation: 68\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/68/20240220-035134\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 68 and asking ESP for generation 69...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 68 data persisted.\n", + "Evaluated candidates:\n", + "Id: 68_71 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_35'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_71', 'origin': '2_49~CUW~67_35#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 68_39 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '67_38'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_39', 'origin': '67_95~CUW~67_38#MGNP'} Metrics: ['ELUC: 17.109098352344827', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24762712946196008', 'is_elite: False']\n", + "Id: 68_59 Identity: {'ancestor_count': 66, 'ancestor_ids': ['63_36', '67_38'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_59', 'origin': '63_36~CUW~67_38#MGNP'} Metrics: ['ELUC: 5.464471118896669', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.27168824556560633', 'is_elite: False']\n", + "Id: 68_31 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_18', '67_67'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_31', 'origin': '67_18~CUW~67_67#MGNP'} Metrics: ['ELUC: 1.9062928603476508', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.10554346889938554', 'is_elite: False']\n", + "Id: 68_82 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_95'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_82', 'origin': '2_49~CUW~67_95#MGNP'} Metrics: ['ELUC: 1.180962628606504', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.26841012475042897', 'is_elite: False']\n", + "Id: 68_18 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '2_49'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_18', 'origin': '67_100~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.0030118237797845', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.33522712954638273', 'is_elite: False']\n", + "Id: 68_61 Identity: {'ancestor_count': 66, 'ancestor_ids': ['1_1', '67_35'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_61', 'origin': '1_1~CUW~67_35#MGNP'} Metrics: ['ELUC: 0.21236662448852453', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03367095199859553', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 68_27 Identity: {'ancestor_count': 66, 'ancestor_ids': ['1_1', '67_18'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_27', 'origin': '1_1~CUW~67_18#MGNP'} Metrics: ['ELUC: -0.39430393106662237', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.05819407823434101', 'is_elite: False']\n", + "Id: 68_89 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_89', 'origin': '66_74~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5847852299011347', 'NSGA-II_crowding_distance: 0.18483423305215987', 'NSGA-II_rank: 1', 'change: 0.03566503224537867', 'is_elite: True']\n", + "Id: 68_57 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_35', '67_18'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_57', 'origin': '67_35~CUW~67_18#MGNP'} Metrics: ['ELUC: -0.6786342534087538', 'NSGA-II_crowding_distance: 0.176762005921486', 'NSGA-II_rank: 2', 'change: 0.05351734777676713', 'is_elite: False']\n", + "Id: 68_97 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_35', '67_69'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_97', 'origin': '67_35~CUW~67_69#MGNP'} Metrics: ['ELUC: -0.6995599663482018', 'NSGA-II_crowding_distance: 0.916086954087539', 'NSGA-II_rank: 5', 'change: 0.10576312979321112', 'is_elite: False']\n", + "Id: 68_63 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_18', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_63', 'origin': '67_18~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8611448875319689', 'NSGA-II_crowding_distance: 0.3568020542230266', 'NSGA-II_rank: 3', 'change: 0.06413527093334824', 'is_elite: False']\n", + "Id: 66_74 Identity: {'ancestor_count': 64, 'ancestor_ids': ['65_72', '1_1'], 'birth_generation': 66, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '66_74', 'origin': '65_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2237585094391712', 'NSGA-II_crowding_distance: 0.07725944915264213', 'NSGA-II_rank: 1', 'change: 0.0392809679484303', 'is_elite: False']\n", + "Id: 68_84 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_84', 'origin': '67_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.382579291493319', 'NSGA-II_crowding_distance: 0.14769930744785437', 'NSGA-II_rank: 2', 'change: 0.05518151762123191', 'is_elite: False']\n", + "Id: 68_67 Identity: {'ancestor_count': 66, 'ancestor_ids': ['66_74', '67_35'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_67', 'origin': '66_74~CUW~67_35#MGNP'} Metrics: ['ELUC: -1.396063369989346', 'NSGA-II_crowding_distance: 0.10337163684691789', 'NSGA-II_rank: 1', 'change: 0.04494989005011594', 'is_elite: False']\n", + "Id: 68_28 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_38'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_28', 'origin': '67_100~CUW~67_38#MGNP'} Metrics: ['ELUC: -1.5968834215980185', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.24822507020106166', 'is_elite: False']\n", + "Id: 68_60 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_35', '66_74'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_60', 'origin': '67_35~CUW~66_74#MGNP'} Metrics: ['ELUC: -1.9393974938915925', 'NSGA-II_crowding_distance: 0.15711903576623687', 'NSGA-II_rank: 1', 'change: 0.057980146578709896', 'is_elite: False']\n", + "Id: 68_22 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_22', 'origin': '67_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.342079181993835', 'NSGA-II_crowding_distance: 0.26938867719763804', 'NSGA-II_rank: 2', 'change: 0.06629517734733854', 'is_elite: False']\n", + "Id: 68_65 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_65', 'origin': '67_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.576959461657107', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08706699667815647', 'is_elite: False']\n", + "Id: 68_35 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_93', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_35', 'origin': '67_93~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.8453749314947236', 'NSGA-II_crowding_distance: 0.21637290528384723', 'NSGA-II_rank: 4', 'change: 0.10412128314919324', 'is_elite: False']\n", + "Id: 68_58 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '67_69'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_58', 'origin': '67_95~CUW~67_69#MGNP'} Metrics: ['ELUC: -3.192344901049352', 'NSGA-II_crowding_distance: 0.3488013286602998', 'NSGA-II_rank: 4', 'change: 0.11706261132739626', 'is_elite: False']\n", + "Id: 67_35 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_74'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_35', 'origin': '65_79~CUW~66_74#MGNP'} Metrics: ['ELUC: -3.2420300459574194', 'NSGA-II_crowding_distance: 0.1279611996247913', 'NSGA-II_rank: 1', 'change: 0.06050408546776139', 'is_elite: False']\n", + "Id: 68_64 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '66_74'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_64', 'origin': '67_75~CUW~66_74#MGNP'} Metrics: ['ELUC: -3.4873658411438835', 'NSGA-II_crowding_distance: 0.1815559082955015', 'NSGA-II_rank: 1', 'change: 0.06989141696422255', 'is_elite: True']\n", + "Id: 68_19 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_35', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_19', 'origin': '67_35~CUW~67_100#MGNP'} Metrics: ['ELUC: -3.4951676408140737', 'NSGA-II_crowding_distance: 0.36658745955750305', 'NSGA-II_rank: 3', 'change: 0.07830628132906332', 'is_elite: False']\n", + "Id: 68_49 Identity: {'ancestor_count': 62, 'ancestor_ids': ['2_49', '63_36'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_49', 'origin': '2_49~CUW~63_36#MGNP'} Metrics: ['ELUC: -4.220726231848116', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3195298858130947', 'is_elite: False']\n", + "Id: 68_20 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '66_74'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_20', 'origin': '67_95~CUW~66_74#MGNP'} Metrics: ['ELUC: -4.405556400450532', 'NSGA-II_crowding_distance: 0.2306415463060302', 'NSGA-II_rank: 3', 'change: 0.0801269924119215', 'is_elite: False']\n", + "Id: 68_12 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_12', 'origin': '67_75~CUW~67_100#MGNP'} Metrics: ['ELUC: -4.431812421454705', 'NSGA-II_crowding_distance: 0.21280623520374853', 'NSGA-II_rank: 2', 'change: 0.07824698437307527', 'is_elite: False']\n", + "Id: 68_62 Identity: {'ancestor_count': 64, 'ancestor_ids': ['1_1', '67_58'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_62', 'origin': '1_1~CUW~67_58#MGNP'} Metrics: ['ELUC: -4.552892952036571', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.17969925115734', 'is_elite: False']\n", + "Id: 68_53 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_35', '67_35'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_53', 'origin': '67_35~CUW~67_35#MGNP'} Metrics: ['ELUC: -4.5722046516138715', 'NSGA-II_crowding_distance: 0.10223439732790435', 'NSGA-II_rank: 2', 'change: 0.08732259794569533', 'is_elite: False']\n", + "Id: 68_72 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_67', '67_95'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_72', 'origin': '67_67~CUW~67_95#MGNP'} Metrics: ['ELUC: -5.089283099123732', 'NSGA-II_crowding_distance: 0.16025609017595813', 'NSGA-II_rank: 3', 'change: 0.09665443421555958', 'is_elite: False']\n", + "Id: 68_46 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_26', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_46', 'origin': '67_26~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.100827120113823', 'NSGA-II_crowding_distance: 0.6243378808160378', 'NSGA-II_rank: 4', 'change: 0.12752314893712902', 'is_elite: False']\n", + "Id: 68_98 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_26', '67_93'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_98', 'origin': '67_26~CUW~67_93#MGNP'} Metrics: ['ELUC: -5.176423365426737', 'NSGA-II_crowding_distance: 0.5440777231741518', 'NSGA-II_rank: 3', 'change: 0.09726457611154975', 'is_elite: False']\n", + "Id: 68_85 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '67_69'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_85', 'origin': '67_95~CUW~67_69#MGNP'} Metrics: ['ELUC: -5.3563200424853985', 'NSGA-II_crowding_distance: 0.12029081995730828', 'NSGA-II_rank: 2', 'change: 0.09065616679823942', 'is_elite: False']\n", + "Id: 67_75 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_19'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_75', 'origin': '65_79~CUW~66_19#MGNP'} Metrics: ['ELUC: -5.418067400507282', 'NSGA-II_crowding_distance: 0.26845933336027694', 'NSGA-II_rank: 1', 'change: 0.07774829792440713', 'is_elite: True']\n", + "Id: 68_88 Identity: {'ancestor_count': 66, 'ancestor_ids': ['63_36', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_88', 'origin': '63_36~CUW~67_100#MGNP'} Metrics: ['ELUC: -5.834057056338646', 'NSGA-II_crowding_distance: 0.12513524249280952', 'NSGA-II_rank: 2', 'change: 0.099188884543932', 'is_elite: False']\n", + "Id: 68_33 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '67_74'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_33', 'origin': '66_74~CUW~67_74#MGNP'} Metrics: ['ELUC: -6.077824589800611', 'NSGA-II_crowding_distance: 1.7827016095095702', 'NSGA-II_rank: 9', 'change: 0.2366083839219488', 'is_elite: False']\n", + "Id: 68_34 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_25', '67_95'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_34', 'origin': '67_25~CUW~67_95#MGNP'} Metrics: ['ELUC: -6.6350286774682035', 'NSGA-II_crowding_distance: 0.06760028801069497', 'NSGA-II_rank: 2', 'change: 0.10353389805978096', 'is_elite: False']\n", + "Id: 68_80 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_26', '66_74'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_80', 'origin': '67_26~CUW~66_74#MGNP'} Metrics: ['ELUC: -6.662851744793713', 'NSGA-II_crowding_distance: 0.09194983718536097', 'NSGA-II_rank: 2', 'change: 0.103977398312533', 'is_elite: False']\n", + "Id: 68_44 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '2_49'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_44', 'origin': '67_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.986970613801276', 'NSGA-II_crowding_distance: 0.8039407809410286', 'NSGA-II_rank: 9', 'change: 0.25907539012000874', 'is_elite: False']\n", + "Id: 68_32 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '67_75'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_32', 'origin': '67_95~CUW~67_75#MGNP'} Metrics: ['ELUC: -7.052130768828379', 'NSGA-II_crowding_distance: 0.13586510544628697', 'NSGA-II_rank: 1', 'change: 0.0894985398855924', 'is_elite: False']\n", + "Id: 67_95 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_97', '65_61'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_95', 'origin': '66_97~CUW~65_61#MGNP'} Metrics: ['ELUC: -7.0786689452865215', 'NSGA-II_crowding_distance: 0.16032679132718486', 'NSGA-II_rank: 1', 'change: 0.09010649759159399', 'is_elite: False']\n", + "Id: 68_24 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_38', '67_75'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_24', 'origin': '67_38~CUW~67_75#MGNP'} Metrics: ['ELUC: -7.23627742680587', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2703517226564327', 'is_elite: False']\n", + "Id: 68_14 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_75'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_14', 'origin': '67_100~CUW~67_75#MGNP'} Metrics: ['ELUC: -7.669746530081472', 'NSGA-II_crowding_distance: 0.14100327687073153', 'NSGA-II_rank: 2', 'change: 0.11150214698675187', 'is_elite: False']\n", + "Id: 68_45 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_25', '67_67'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_45', 'origin': '67_25~CUW~67_67#MGNP'} Metrics: ['ELUC: -7.69409922797657', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.15275345942710772', 'is_elite: False']\n", + "Id: 68_54 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_25', '67_75'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_54', 'origin': '67_25~CUW~67_75#MGNP'} Metrics: ['ELUC: -7.800744657415662', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.14239214525789248', 'is_elite: False']\n", + "Id: 68_16 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_26', '67_75'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_16', 'origin': '67_26~CUW~67_75#MGNP'} Metrics: ['ELUC: -8.047247508194971', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.14010195000239822', 'is_elite: False']\n", + "Id: 68_41 Identity: {'ancestor_count': 66, 'ancestor_ids': ['66_74', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_41', 'origin': '66_74~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.418013654258557', 'NSGA-II_crowding_distance: 0.10007352066840358', 'NSGA-II_rank: 2', 'change: 0.11355023286459053', 'is_elite: False']\n", + "Id: 68_26 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '63_36'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_26', 'origin': '67_100~CUW~63_36#MGNP'} Metrics: ['ELUC: -8.442195718427866', 'NSGA-II_crowding_distance: 1.068874222652522', 'NSGA-II_rank: 5', 'change: 0.13541022403314548', 'is_elite: False']\n", + "Id: 68_79 Identity: {'ancestor_count': 66, 'ancestor_ids': ['63_36', '67_35'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_79', 'origin': '63_36~CUW~67_35#MGNP'} Metrics: ['ELUC: -8.491600003746495', 'NSGA-II_crowding_distance: 0.8417036059465928', 'NSGA-II_rank: 4', 'change: 0.13402481311903516', 'is_elite: False']\n", + "Id: 68_68 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_68', 'origin': '67_100~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.761487407874672', 'NSGA-II_crowding_distance: 0.22155867849307992', 'NSGA-II_rank: 1', 'change: 0.10832817250116257', 'is_elite: True']\n", + "Id: 68_29 Identity: {'ancestor_count': 66, 'ancestor_ids': ['66_74', '67_67'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_29', 'origin': '66_74~CUW~67_67#MGNP'} Metrics: ['ELUC: -8.79098405395113', 'NSGA-II_crowding_distance: 0.07827624219145593', 'NSGA-II_rank: 2', 'change: 0.12025131313806486', 'is_elite: False']\n", + "Id: 68_15 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_38', '66_74'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_15', 'origin': '67_38~CUW~66_74#MGNP'} Metrics: ['ELUC: -9.169182154939945', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.29310900716715377', 'is_elite: False']\n", + "Id: 68_11 Identity: {'ancestor_count': 66, 'ancestor_ids': ['1_1', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_11', 'origin': '1_1~CUW~67_26#MGNP'} Metrics: ['ELUC: -9.198584741803815', 'NSGA-II_crowding_distance: 0.07967381827658972', 'NSGA-II_rank: 2', 'change: 0.1219089497899752', 'is_elite: False']\n", + "Id: 68_23 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_25', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_23', 'origin': '67_25~CUW~67_26#MGNP'} Metrics: ['ELUC: -9.421700924537856', 'NSGA-II_crowding_distance: 0.8742079953994707', 'NSGA-II_rank: 3', 'change: 0.13248373847492184', 'is_elite: False']\n", + "Id: 67_100 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_78', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_100', 'origin': '66_78~CUW~66_84#MGNP'} Metrics: ['ELUC: -9.618489777027925', 'NSGA-II_crowding_distance: 0.1029650377130091', 'NSGA-II_rank: 1', 'change: 0.11311312747406431', 'is_elite: False']\n", + "Id: 68_100 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_35'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_100', 'origin': '67_100~CUW~67_35#MGNP'} Metrics: ['ELUC: -9.788617580309591', 'NSGA-II_crowding_distance: 0.1558082209762773', 'NSGA-II_rank: 2', 'change: 0.1255680545567776', 'is_elite: False']\n", + "Id: 68_48 Identity: {'ancestor_count': 66, 'ancestor_ids': ['66_97', '67_38'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_48', 'origin': '66_97~CUW~67_38#MGNP'} Metrics: ['ELUC: -9.82174178507764', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.28713356323108213', 'is_elite: False']\n", + "Id: 68_47 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_75'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_47', 'origin': '67_100~CUW~67_75#MGNP'} Metrics: ['ELUC: -9.90251104865417', 'NSGA-II_crowding_distance: 0.09806008565461655', 'NSGA-II_rank: 1', 'change: 0.11968712230345976', 'is_elite: False']\n", + "Id: 68_56 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_26', '67_18'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_56', 'origin': '67_26~CUW~67_18#MGNP'} Metrics: ['ELUC: -10.095917133265317', 'NSGA-II_crowding_distance: 0.13758054895913968', 'NSGA-II_rank: 1', 'change: 0.13426998233978274', 'is_elite: False']\n", + "Id: 68_92 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_38'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_92', 'origin': '2_49~CUW~67_38#MGNP'} Metrics: ['ELUC: -10.20835065847884', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29133412390738816', 'is_elite: False']\n", + "Id: 68_90 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_58', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_90', 'origin': '67_58~CUW~67_100#MGNP'} Metrics: ['ELUC: -10.332156153813752', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.19694665675553913', 'is_elite: False']\n", + "Id: 68_52 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_69'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_52', 'origin': '2_49~CUW~67_69#MGNP'} Metrics: ['ELUC: -10.789508122649591', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2796263754027185', 'is_elite: False']\n", + "Id: 68_77 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_77', 'origin': '67_69~CUW~67_26#MGNP'} Metrics: ['ELUC: -10.845183030135702', 'NSGA-II_crowding_distance: 0.46086778953509433', 'NSGA-II_rank: 5', 'change: 0.16637943595104893', 'is_elite: False']\n", + "Id: 68_86 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '63_36'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_86', 'origin': '66_74~CUW~63_36#MGNP'} Metrics: ['ELUC: -10.96181515839262', 'NSGA-II_crowding_distance: 0.49694629424611647', 'NSGA-II_rank: 5', 'change: 0.18632683301973768', 'is_elite: False']\n", + "Id: 68_69 Identity: {'ancestor_count': 66, 'ancestor_ids': ['1_1', '67_67'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_69', 'origin': '1_1~CUW~67_67#MGNP'} Metrics: ['ELUC: -10.994357544485553', 'NSGA-II_crowding_distance: 0.14091157417305245', 'NSGA-II_rank: 2', 'change: 0.13474413396438978', 'is_elite: False']\n", + "Id: 68_70 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_38', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_70', 'origin': '67_38~CUW~67_26#MGNP'} Metrics: ['ELUC: -11.193777944819306', 'NSGA-II_crowding_distance: 0.6230452563773666', 'NSGA-II_rank: 5', 'change: 0.2529213037365421', 'is_elite: False']\n", + "Id: 68_55 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_35', '67_25'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_55', 'origin': '67_35~CUW~67_25#MGNP'} Metrics: ['ELUC: -11.1939648627478', 'NSGA-II_crowding_distance: 0.04491125285194434', 'NSGA-II_rank: 2', 'change: 0.14061250566959507', 'is_elite: False']\n", + "Id: 68_66 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_95'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_66', 'origin': '67_100~CUW~67_95#MGNP'} Metrics: ['ELUC: -11.232192651856572', 'NSGA-II_crowding_distance: 0.10858776540018662', 'NSGA-II_rank: 2', 'change: 0.1428395045803999', 'is_elite: False']\n", + "Id: 68_74 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_93'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_74', 'origin': '67_100~CUW~67_93#MGNP'} Metrics: ['ELUC: -11.434342624513919', 'NSGA-II_crowding_distance: 0.09780833928128309', 'NSGA-II_rank: 1', 'change: 0.134742438140474', 'is_elite: False']\n", + "Id: 68_83 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '67_69'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_83', 'origin': '67_95~CUW~67_69#MGNP'} Metrics: ['ELUC: -11.440260316909718', 'NSGA-II_crowding_distance: 0.03126965511480321', 'NSGA-II_rank: 1', 'change: 0.14063989295135026', 'is_elite: False']\n", + "Id: 68_99 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_99', 'origin': '67_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.488441735245626', 'NSGA-II_crowding_distance: 1.1125636395309617', 'NSGA-II_rank: 4', 'change: 0.16533331163839846', 'is_elite: False']\n", + "Id: 68_51 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_51', 'origin': '67_75~CUW~67_26#MGNP'} Metrics: ['ELUC: -11.494930563334144', 'NSGA-II_crowding_distance: 0.09320280537218308', 'NSGA-II_rank: 1', 'change: 0.14304441036982074', 'is_elite: False']\n", + "Id: 68_42 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '2_49'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_42', 'origin': '63_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.830480694203114', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2890622566010873', 'is_elite: False']\n", + "Id: 68_25 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_26', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_25', 'origin': '67_26~CUW~67_26#MGNP'} Metrics: ['ELUC: -12.097695686381762', 'NSGA-II_crowding_distance: 0.8684786762967914', 'NSGA-II_rank: 3', 'change: 0.15535439315708746', 'is_elite: False']\n", + "Id: 68_73 Identity: {'ancestor_count': 66, 'ancestor_ids': ['1_1', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_73', 'origin': '1_1~CUW~67_26#MGNP'} Metrics: ['ELUC: -12.216923602745064', 'NSGA-II_crowding_distance: 0.23204580334149827', 'NSGA-II_rank: 2', 'change: 0.15314876554981777', 'is_elite: False']\n", + "Id: 68_43 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_38', '63_36'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_43', 'origin': '67_38~CUW~63_36#MGNP'} Metrics: ['ELUC: -12.23976214613581', 'NSGA-II_crowding_distance: 0.694733792790339', 'NSGA-II_rank: 4', 'change: 0.27672641536765025', 'is_elite: False']\n", + "Id: 68_17 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_17', 'origin': '67_100~CUW~67_26#MGNP'} Metrics: ['ELUC: -12.411105522730274', 'NSGA-II_crowding_distance: 0.10953681417471464', 'NSGA-II_rank: 1', 'change: 0.15197399066538952', 'is_elite: False']\n", + "Id: 68_95 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_95', 'origin': '2_49~CUW~67_26#MGNP'} Metrics: ['ELUC: -12.440396959919399', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2818660535983028', 'is_elite: False']\n", + "Id: 67_26 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_78', '66_84'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_26', 'origin': '66_78~CUW~66_84#MGNP'} Metrics: ['ELUC: -12.503942449928555', 'NSGA-II_crowding_distance: 0.09925302517836179', 'NSGA-II_rank: 1', 'change: 0.1586045119624284', 'is_elite: False']\n", + "Id: 68_76 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_26', '67_69'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_76', 'origin': '67_26~CUW~67_69#MGNP'} Metrics: ['ELUC: -12.988206144542646', 'NSGA-II_crowding_distance: 0.24290620065349117', 'NSGA-II_rank: 2', 'change: 0.176384151056794', 'is_elite: False']\n", + "Id: 68_38 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_38', 'origin': '67_69~CUW~67_26#MGNP'} Metrics: ['ELUC: -13.095768130219115', 'NSGA-II_crowding_distance: 0.20346707659877739', 'NSGA-II_rank: 1', 'change: 0.1699699460226114', 'is_elite: True']\n", + "Id: 68_81 Identity: {'ancestor_count': 66, 'ancestor_ids': ['1_1', '67_93'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_81', 'origin': '1_1~CUW~67_93#MGNP'} Metrics: ['ELUC: -13.410347502512893', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.22781984990910017', 'is_elite: False']\n", + "Id: 68_78 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_26', '64_40'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_78', 'origin': '67_26~CUW~64_40#MGNP'} Metrics: ['ELUC: -13.436172499056724', 'NSGA-II_crowding_distance: 0.46118927997511594', 'NSGA-II_rank: 2', 'change: 0.19798744823232586', 'is_elite: False']\n", + "Id: 68_93 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_69'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_93', 'origin': '2_49~CUW~67_69#MGNP'} Metrics: ['ELUC: -13.952856413152288', 'NSGA-II_crowding_distance: 0.5160771677146859', 'NSGA-II_rank: 2', 'change: 0.28272948125473824', 'is_elite: False']\n", + "Id: 67_69 Identity: {'ancestor_count': 65, 'ancestor_ids': ['63_36', '66_78'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_69', 'origin': '63_36~CUW~66_78#MGNP'} Metrics: ['ELUC: -13.9681855204079', 'NSGA-II_crowding_distance: 0.4196995725683669', 'NSGA-II_rank: 1', 'change: 0.1944658970894259', 'is_elite: True']\n", + "Id: 68_21 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_93', '67_18'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_21', 'origin': '67_93~CUW~67_18#MGNP'} Metrics: ['ELUC: -15.687529779148477', 'NSGA-II_crowding_distance: 0.3502438383477882', 'NSGA-II_rank: 1', 'change: 0.2512159513288761', 'is_elite: True']\n", + "Id: 68_40 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '67_93'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_40', 'origin': '67_69~CUW~67_93#MGNP'} Metrics: ['ELUC: -16.142186134887623', 'NSGA-II_crowding_distance: 0.13520427334430968', 'NSGA-II_rank: 1', 'change: 0.26207739266399654', 'is_elite: False']\n", + "Id: 68_50 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '2_49'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_50', 'origin': '67_75~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.281975071683352', 'NSGA-II_crowding_distance: 0.20990297712994294', 'NSGA-II_rank: 2', 'change: 0.28923910180405454', 'is_elite: False']\n", + "Id: 68_75 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '67_74'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_75', 'origin': '66_74~CUW~67_74#MGNP'} Metrics: ['ELUC: -16.28483835264712', 'NSGA-II_crowding_distance: 0.13096749363727392', 'NSGA-II_rank: 1', 'change: 0.28142138281921963', 'is_elite: False']\n", + "Id: 68_91 Identity: {'ancestor_count': 62, 'ancestor_ids': ['2_49', '63_36'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_91', 'origin': '2_49~CUW~63_36#MGNP'} Metrics: ['ELUC: -16.51283750294361', 'NSGA-II_crowding_distance: 0.09535106943760596', 'NSGA-II_rank: 1', 'change: 0.29486510613387684', 'is_elite: False']\n", + "Id: 68_87 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_38'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_87', 'origin': '67_100~CUW~67_38#MGNP'} Metrics: ['ELUC: -16.55665957339834', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.29712136010896095', 'is_elite: False']\n", + "Id: 68_37 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_37', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.088374558541126', 'NSGA-II_crowding_distance: 0.08901634124316286', 'NSGA-II_rank: 1', 'change: 0.29623575994297546', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 67_38 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '2_49'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_38', 'origin': '66_74~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 68_13 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '2_49'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_13', 'origin': '63_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 68_30 Identity: {'ancestor_count': 62, 'ancestor_ids': ['63_36', '2_49'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_30', 'origin': '63_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 68_36 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_38', '2_49'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_36', 'origin': '67_38~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 68_94 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_69'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_94', 'origin': '2_49~CUW~67_69#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 68_96 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_67'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_96', 'origin': '2_49~CUW~67_67#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 68.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 69...:\n", + "PopulationResponse:\n", + " Generation: 69\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/69/20240220-035849\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 69 and asking ESP for generation 70...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 69 data persisted.\n", + "Evaluated candidates:\n", + "Id: 69_48 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '67_95'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_48', 'origin': '68_96~CUW~67_95#MGNP'} Metrics: ['ELUC: 22.36039949427095', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30389841661556805', 'is_elite: False']\n", + "Id: 69_41 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_64', '2_49'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_41', 'origin': '68_64~CUW~2_49#MGNP'} Metrics: ['ELUC: 9.691812479626599', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3102658361746335', 'is_elite: False']\n", + "Id: 69_59 Identity: {'ancestor_count': 66, 'ancestor_ids': ['68_75', '67_69'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_59', 'origin': '68_75~CUW~67_69#MGNP'} Metrics: ['ELUC: 7.300124771830016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1513367694971757', 'is_elite: False']\n", + "Id: 69_98 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_32', '2_49'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_98', 'origin': '68_32~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.7209885911749465', 'NSGA-II_crowding_distance: 1.0792312626898055', 'NSGA-II_rank: 7', 'change: 0.23298994480229304', 'is_elite: False']\n", + "Id: 69_87 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_60', '67_95'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_87', 'origin': '68_60~CUW~67_95#MGNP'} Metrics: ['ELUC: 2.0561277504524345', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07173810729509301', 'is_elite: False']\n", + "Id: 69_17 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '68_89'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_17', 'origin': '68_38~CUW~68_89#MGNP'} Metrics: ['ELUC: 0.9079512357724111', 'NSGA-II_crowding_distance: 0.29502133921290885', 'NSGA-II_rank: 4', 'change: 0.0800117370385905', 'is_elite: False']\n", + "Id: 69_42 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_75', '68_96'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_42', 'origin': '67_75~CUW~68_96#MGNP'} Metrics: ['ELUC: 0.5402400224431847', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24349368985990402', 'is_elite: False']\n", + "Id: 69_18 Identity: {'ancestor_count': 67, 'ancestor_ids': ['1_1', '68_64'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_18', 'origin': '1_1~CUW~68_64#MGNP'} Metrics: ['ELUC: 0.03950377231698302', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06954871179926676', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 69_69 Identity: {'ancestor_count': 66, 'ancestor_ids': ['1_1', '68_89'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_69', 'origin': '1_1~CUW~68_89#MGNP'} Metrics: ['ELUC: -0.087478903302796', 'NSGA-II_crowding_distance: 0.13637381368665158', 'NSGA-II_rank: 1', 'change: 0.02909647091762268', 'is_elite: False']\n", + "Id: 69_89 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_64', '68_89'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_89', 'origin': '68_64~CUW~68_89#MGNP'} Metrics: ['ELUC: -0.521850378849697', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.0543163579269377', 'is_elite: False']\n", + "Id: 69_36 Identity: {'ancestor_count': 67, 'ancestor_ids': ['2_49', '68_17'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_36', 'origin': '2_49~CUW~68_17#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.05123678599014794', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 69_53 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '2_49'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_53', 'origin': '68_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 69_80 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_80', 'origin': '2_49~CUW~67_75#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.5220171738622206', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 68_89 Identity: {'ancestor_count': 65, 'ancestor_ids': ['66_74', '1_1'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_89', 'origin': '66_74~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5847852299011347', 'NSGA-II_crowding_distance: 0.1688411315140464', 'NSGA-II_rank: 1', 'change: 0.03566503224537867', 'is_elite: False']\n", + "Id: 69_78 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_56', '68_96'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_78', 'origin': '68_56~CUW~68_96#MGNP'} Metrics: ['ELUC: -0.6213403805127959', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30837011404715375', 'is_elite: False']\n", + "Id: 69_15 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '1_1'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_15', 'origin': '67_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6354983704668796', 'NSGA-II_crowding_distance: 0.07895747418134477', 'NSGA-II_rank: 2', 'change: 0.05896535808309721', 'is_elite: False']\n", + "Id: 69_38 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_38', 'origin': '2_49~CUW~67_75#MGNP'} Metrics: ['ELUC: -0.7535180382831498', 'NSGA-II_crowding_distance: 0.9207687373101945', 'NSGA-II_rank: 7', 'change: 0.26813076376631806', 'is_elite: False']\n", + "Id: 69_74 Identity: {'ancestor_count': 66, 'ancestor_ids': ['68_89', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_74', 'origin': '68_89~CUW~67_75#MGNP'} Metrics: ['ELUC: -1.412892847472488', 'NSGA-II_crowding_distance: 0.35171813919289097', 'NSGA-II_rank: 2', 'change: 0.0601349424751722', 'is_elite: False']\n", + "Id: 69_24 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_35', '68_89'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_24', 'origin': '67_35~CUW~68_89#MGNP'} Metrics: ['ELUC: -1.5136106815188772', 'NSGA-II_crowding_distance: 0.15929277066011385', 'NSGA-II_rank: 1', 'change: 0.05527300606662289', 'is_elite: False']\n", + "Id: 69_27 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_60', '68_60'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_27', 'origin': '68_60~CUW~68_60#MGNP'} Metrics: ['ELUC: -1.800897934590628', 'NSGA-II_crowding_distance: 0.0815570255305393', 'NSGA-II_rank: 1', 'change: 0.06255663770564618', 'is_elite: False']\n", + "Id: 69_55 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_64', '68_38'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_55', 'origin': '68_64~CUW~68_38#MGNP'} Metrics: ['ELUC: -1.8320731333890736', 'NSGA-II_crowding_distance: 0.3528545490928968', 'NSGA-II_rank: 4', 'change: 0.08542333376292581', 'is_elite: False']\n", + "Id: 69_30 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '1_1'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_30', 'origin': '68_21~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.243252301787386', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09741502928662371', 'is_elite: False']\n", + "Id: 69_67 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_35', '1_1'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_67', 'origin': '67_35~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2723404779939758', 'NSGA-II_crowding_distance: 0.12050048517710363', 'NSGA-II_rank: 1', 'change: 0.06673192647316359', 'is_elite: False']\n", + "Id: 69_31 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '1_1'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_31', 'origin': '68_68~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.937617853267262', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10716920479283078', 'is_elite: False']\n", + "Id: 68_64 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '66_74'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_64', 'origin': '67_75~CUW~66_74#MGNP'} Metrics: ['ELUC: -3.4873658411438835', 'NSGA-II_crowding_distance: 0.09960978121998781', 'NSGA-II_rank: 1', 'change: 0.06989141696422255', 'is_elite: False']\n", + "Id: 69_84 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_89', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_84', 'origin': '68_89~CUW~68_21#MGNP'} Metrics: ['ELUC: -3.602693104426661', 'NSGA-II_crowding_distance: 0.6827528304579609', 'NSGA-II_rank: 5', 'change: 0.10165268520591124', 'is_elite: False']\n", + "Id: 69_14 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_64', '68_64'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_14', 'origin': '68_64~CUW~68_64#MGNP'} Metrics: ['ELUC: -3.7442938474366634', 'NSGA-II_crowding_distance: 0.11072136930017369', 'NSGA-II_rank: 1', 'change: 0.07147376303462499', 'is_elite: False']\n", + "Id: 69_75 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '68_89'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_75', 'origin': '68_38~CUW~68_89#MGNP'} Metrics: ['ELUC: -4.015925975668141', 'NSGA-II_crowding_distance: 0.5711465167102682', 'NSGA-II_rank: 4', 'change: 0.09270840001855979', 'is_elite: False']\n", + "Id: 69_46 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '68_60'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_46', 'origin': '68_38~CUW~68_60#MGNP'} Metrics: ['ELUC: -4.761534394856086', 'NSGA-II_crowding_distance: 0.46283299310002474', 'NSGA-II_rank: 3', 'change: 0.0802243419665875', 'is_elite: False']\n", + "Id: 69_34 Identity: {'ancestor_count': 66, 'ancestor_ids': ['68_89', '67_69'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_34', 'origin': '68_89~CUW~67_69#MGNP'} Metrics: ['ELUC: -5.053840774860848', 'NSGA-II_crowding_distance: 0.3714334321166759', 'NSGA-II_rank: 3', 'change: 0.09721487558829571', 'is_elite: False']\n", + "Id: 69_94 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_94', 'origin': '67_75~CUW~67_75#MGNP'} Metrics: ['ELUC: -5.144226191542635', 'NSGA-II_crowding_distance: 0.3041257438894107', 'NSGA-II_rank: 2', 'change: 0.0756183660915116', 'is_elite: False']\n", + "Id: 69_90 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '67_35'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_90', 'origin': '67_75~CUW~67_35#MGNP'} Metrics: ['ELUC: -5.15878184384367', 'NSGA-II_crowding_distance: 0.12817903191109678', 'NSGA-II_rank: 2', 'change: 0.0771577178053992', 'is_elite: False']\n", + "Id: 69_19 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_19', 'origin': '67_75~CUW~67_75#MGNP'} Metrics: ['ELUC: -5.161862993308009', 'NSGA-II_crowding_distance: 0.11156168686099621', 'NSGA-II_rank: 1', 'change: 0.07451147336983903', 'is_elite: False']\n", + "Id: 69_39 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '1_1'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_39', 'origin': '67_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.379003875056365', 'NSGA-II_crowding_distance: 0.025419768076989334', 'NSGA-II_rank: 1', 'change: 0.07701975123801807', 'is_elite: False']\n", + "Id: 67_75 Identity: {'ancestor_count': 65, 'ancestor_ids': ['65_79', '66_19'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_75', 'origin': '65_79~CUW~66_19#MGNP'} Metrics: ['ELUC: -5.418067400507282', 'NSGA-II_crowding_distance: 0.030890118835970808', 'NSGA-II_rank: 1', 'change: 0.07774829792440713', 'is_elite: False']\n", + "Id: 69_57 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '67_69'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_57', 'origin': '68_68~CUW~67_69#MGNP'} Metrics: ['ELUC: -5.63374451914254', 'NSGA-II_crowding_distance: 0.2330517244208864', 'NSGA-II_rank: 2', 'change: 0.10149909750713373', 'is_elite: False']\n", + "Id: 69_81 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_81', 'origin': '68_21~CUW~67_75#MGNP'} Metrics: ['ELUC: -5.728533714417922', 'NSGA-II_crowding_distance: 0.0977965134546673', 'NSGA-II_rank: 1', 'change: 0.08030504520517777', 'is_elite: False']\n", + "Id: 69_20 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '68_64'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_20', 'origin': '68_96~CUW~68_64#MGNP'} Metrics: ['ELUC: -6.2547158188060905', 'NSGA-II_crowding_distance: 1.5298591566975273', 'NSGA-II_rank: 6', 'change: 0.267766304870398', 'is_elite: False']\n", + "Id: 69_92 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_56', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_92', 'origin': '68_56~CUW~67_75#MGNP'} Metrics: ['ELUC: -6.602323222487989', 'NSGA-II_crowding_distance: 0.16712648748878434', 'NSGA-II_rank: 1', 'change: 0.08683141183406765', 'is_elite: False']\n", + "Id: 69_77 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '68_89'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_77', 'origin': '68_96~CUW~68_89#MGNP'} Metrics: ['ELUC: -7.0258540950196435', 'NSGA-II_crowding_distance: 0.41473263378306136', 'NSGA-II_rank: 6', 'change: 0.2777625716874959', 'is_elite: False']\n", + "Id: 69_13 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_56', '67_95'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_13', 'origin': '68_56~CUW~67_95#MGNP'} Metrics: ['ELUC: -7.060390340785546', 'NSGA-II_crowding_distance: 0.22046999508114357', 'NSGA-II_rank: 2', 'change: 0.1068410825788557', 'is_elite: False']\n", + "Id: 69_66 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_69', '68_64'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_66', 'origin': '67_69~CUW~68_64#MGNP'} Metrics: ['ELUC: -7.341280254518408', 'NSGA-II_crowding_distance: 0.6354468688847461', 'NSGA-II_rank: 5', 'change: 0.13669102782292378', 'is_elite: False']\n", + "Id: 69_16 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_100', '68_32'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_16', 'origin': '67_100~CUW~68_32#MGNP'} Metrics: ['ELUC: -7.413718522494573', 'NSGA-II_crowding_distance: 0.19484847385563153', 'NSGA-II_rank: 1', 'change: 0.10157375904041109', 'is_elite: True']\n", + "Id: 69_68 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_68', 'origin': '68_68~CUW~67_75#MGNP'} Metrics: ['ELUC: -7.744839400631035', 'NSGA-II_crowding_distance: 0.3514175890867397', 'NSGA-II_rank: 3', 'change: 0.11895819744689722', 'is_elite: False']\n", + "Id: 69_47 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_64', '68_68'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_47', 'origin': '68_64~CUW~68_68#MGNP'} Metrics: ['ELUC: -8.016042819663907', 'NSGA-II_crowding_distance: 0.44037782287265886', 'NSGA-II_rank: 4', 'change: 0.12995205146532884', 'is_elite: False']\n", + "Id: 69_79 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '67_35'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_79', 'origin': '68_21~CUW~67_35#MGNP'} Metrics: ['ELUC: -8.191110432539125', 'NSGA-II_crowding_distance: 0.8076537746412908', 'NSGA-II_rank: 5', 'change: 0.1407241579457845', 'is_elite: False']\n", + "Id: 69_60 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_60', 'origin': '68_68~CUW~68_21#MGNP'} Metrics: ['ELUC: -8.248899967784656', 'NSGA-II_crowding_distance: 0.28878922656407047', 'NSGA-II_rank: 4', 'change: 0.13422586043420692', 'is_elite: False']\n", + "Id: 69_52 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '68_17'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_52', 'origin': '68_38~CUW~68_17#MGNP'} Metrics: ['ELUC: -8.410964032451574', 'NSGA-II_crowding_distance: 0.2602161586903463', 'NSGA-II_rank: 3', 'change: 0.12585820474769588', 'is_elite: False']\n", + "Id: 69_96 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '68_68'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_96', 'origin': '68_68~CUW~68_68#MGNP'} Metrics: ['ELUC: -8.652912946401326', 'NSGA-II_crowding_distance: 0.48358605705796354', 'NSGA-II_rank: 2', 'change: 0.10862454367725624', 'is_elite: False']\n", + "Id: 68_68 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_68', 'origin': '67_100~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.761487407874672', 'NSGA-II_crowding_distance: 0.22862045735386205', 'NSGA-II_rank: 1', 'change: 0.10832817250116257', 'is_elite: True']\n", + "Id: 69_91 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_75', '2_49'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_91', 'origin': '67_75~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.805077741488113', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2962865258372913', 'is_elite: False']\n", + "Id: 69_40 Identity: {'ancestor_count': 67, 'ancestor_ids': ['2_49', '68_38'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_40', 'origin': '2_49~CUW~68_38#MGNP'} Metrics: ['ELUC: -8.835775824566753', 'NSGA-II_crowding_distance: 0.47014084330247286', 'NSGA-II_rank: 6', 'change: 0.2800070579718463', 'is_elite: False']\n", + "Id: 69_99 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_95', '2_49'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_99', 'origin': '67_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -8.926723110260099', 'NSGA-II_crowding_distance: 1.2175820321493758', 'NSGA-II_rank: 5', 'change: 0.2546921971847722', 'is_elite: False']\n", + "Id: 69_95 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_56', '68_64'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_95', 'origin': '68_56~CUW~68_64#MGNP'} Metrics: ['ELUC: -9.251542569935316', 'NSGA-II_crowding_distance: 0.2740407932728121', 'NSGA-II_rank: 1', 'change: 0.1386005681211818', 'is_elite: True']\n", + "Id: 69_44 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_40', '2_49'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_44', 'origin': '68_40~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.30754222043026', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29558314432296323', 'is_elite: False']\n", + "Id: 69_25 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '68_68'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_25', 'origin': '68_21~CUW~68_68#MGNP'} Metrics: ['ELUC: -9.337061947109337', 'NSGA-II_crowding_distance: 0.24644445072286064', 'NSGA-II_rank: 3', 'change: 0.1535466358826062', 'is_elite: False']\n", + "Id: 69_63 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '67_35'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_63', 'origin': '67_69~CUW~67_35#MGNP'} Metrics: ['ELUC: -9.465963549615562', 'NSGA-II_crowding_distance: 0.7901256282955842', 'NSGA-II_rank: 4', 'change: 0.17497901814016553', 'is_elite: False']\n", + "Id: 69_23 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '68_56'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_23', 'origin': '68_21~CUW~68_56#MGNP'} Metrics: ['ELUC: -10.075958723578903', 'NSGA-II_crowding_distance: 0.13253167683203496', 'NSGA-II_rank: 3', 'change: 0.15626505097729962', 'is_elite: False']\n", + "Id: 69_93 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '2_49'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_93', 'origin': '68_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.439320240870682', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2803807170149722', 'is_elite: False']\n", + "Id: 69_54 Identity: {'ancestor_count': 67, 'ancestor_ids': ['1_1', '68_38'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_54', 'origin': '1_1~CUW~68_38#MGNP'} Metrics: ['ELUC: -10.865133184470217', 'NSGA-II_crowding_distance: 0.09547929731177464', 'NSGA-II_rank: 3', 'change: 0.16042685707611193', 'is_elite: False']\n", + "Id: 69_43 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_75', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_43', 'origin': '67_75~CUW~68_21#MGNP'} Metrics: ['ELUC: -11.0527914595155', 'NSGA-II_crowding_distance: 0.09092587477295849', 'NSGA-II_rank: 3', 'change: 0.1630785922119568', 'is_elite: False']\n", + "Id: 69_88 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_88', 'origin': '68_21~CUW~67_75#MGNP'} Metrics: ['ELUC: -11.193158049878987', 'NSGA-II_crowding_distance: 0.4547983187579894', 'NSGA-II_rank: 3', 'change: 0.17593132419874194', 'is_elite: False']\n", + "Id: 69_26 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '68_56'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_26', 'origin': '68_38~CUW~68_56#MGNP'} Metrics: ['ELUC: -11.200123173054909', 'NSGA-II_crowding_distance: 0.17678662826290878', 'NSGA-II_rank: 1', 'change: 0.14871143759858563', 'is_elite: False']\n", + "Id: 69_22 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_69'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_22', 'origin': '2_49~CUW~67_69#MGNP'} Metrics: ['ELUC: -11.219546868610712', 'NSGA-II_crowding_distance: 0.6951201269177626', 'NSGA-II_rank: 4', 'change: 0.27079490203072365', 'is_elite: False']\n", + "Id: 69_64 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_32', '68_38'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_64', 'origin': '68_32~CUW~68_38#MGNP'} Metrics: ['ELUC: -11.67227102620074', 'NSGA-II_crowding_distance: 0.06510844756113157', 'NSGA-II_rank: 1', 'change: 0.15026925030045768', 'is_elite: False']\n", + "Id: 69_35 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_17', '1_1'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_35', 'origin': '68_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.87401593815512', 'NSGA-II_crowding_distance: 0.3877698351049007', 'NSGA-II_rank: 2', 'change: 0.15353215635492778', 'is_elite: False']\n", + "Id: 69_11 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_40', '68_56'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_11', 'origin': '68_40~CUW~68_56#MGNP'} Metrics: ['ELUC: -11.924988441899744', 'NSGA-II_crowding_distance: 0.10565014147350689', 'NSGA-II_rank: 2', 'change: 0.15615883103476808', 'is_elite: False']\n", + "Id: 69_70 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '68_17'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_70', 'origin': '68_38~CUW~68_17#MGNP'} Metrics: ['ELUC: -12.188394123260462', 'NSGA-II_crowding_distance: 0.14698778809793286', 'NSGA-II_rank: 1', 'change: 0.15136708478992486', 'is_elite: False']\n", + "Id: 69_29 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '67_69'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_29', 'origin': '68_21~CUW~67_69#MGNP'} Metrics: ['ELUC: -12.506779295979944', 'NSGA-II_crowding_distance: 0.30574247234771423', 'NSGA-II_rank: 2', 'change: 0.17092647776476733', 'is_elite: False']\n", + "Id: 69_32 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '68_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_32', 'origin': '68_21~CUW~68_75#MGNP'} Metrics: ['ELUC: -12.961782672115019', 'NSGA-II_crowding_distance: 0.528309856069169', 'NSGA-II_rank: 3', 'change: 0.23661365853821978', 'is_elite: False']\n", + "Id: 68_38 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_38', 'origin': '67_69~CUW~67_26#MGNP'} Metrics: ['ELUC: -13.095768130219115', 'NSGA-II_crowding_distance: 0.24566989172650033', 'NSGA-II_rank: 1', 'change: 0.1699699460226114', 'is_elite: True']\n", + "Id: 69_56 Identity: {'ancestor_count': 67, 'ancestor_ids': ['2_49', '68_32'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_56', 'origin': '2_49~CUW~68_32#MGNP'} Metrics: ['ELUC: -13.284545732724105', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27511113708023344', 'is_elite: False']\n", + "Id: 69_72 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '67_75'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_72', 'origin': '68_21~CUW~67_75#MGNP'} Metrics: ['ELUC: -13.400648485222655', 'NSGA-II_crowding_distance: 0.2742567557621906', 'NSGA-II_rank: 2', 'change: 0.21260171899466626', 'is_elite: False']\n", + "Id: 69_97 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '67_35'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_97', 'origin': '68_96~CUW~67_35#MGNP'} Metrics: ['ELUC: -13.710825314832933', 'NSGA-II_crowding_distance: 0.2717682915757019', 'NSGA-II_rank: 4', 'change: 0.2732254876744303', 'is_elite: False']\n", + "Id: 69_62 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_32', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_62', 'origin': '68_32~CUW~68_21#MGNP'} Metrics: ['ELUC: -13.947958416355071', 'NSGA-II_crowding_distance: 0.20170624010975835', 'NSGA-II_rank: 2', 'change: 0.21953920205142838', 'is_elite: False']\n", + "Id: 67_69 Identity: {'ancestor_count': 65, 'ancestor_ids': ['63_36', '66_78'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_69', 'origin': '63_36~CUW~66_78#MGNP'} Metrics: ['ELUC: -13.9681855204079', 'NSGA-II_crowding_distance: 0.31670605260648615', 'NSGA-II_rank: 1', 'change: 0.1944658970894259', 'is_elite: True']\n", + "Id: 69_12 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '67_69'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_12', 'origin': '68_96~CUW~67_69#MGNP'} Metrics: ['ELUC: -14.198296229216258', 'NSGA-II_crowding_distance: 0.12192896276395346', 'NSGA-II_rank: 4', 'change: 0.2914965266846563', 'is_elite: False']\n", + "Id: 69_100 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '68_89'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_100', 'origin': '2_49~CUW~68_89#MGNP'} Metrics: ['ELUC: -14.33490632221791', 'NSGA-II_crowding_distance: 0.03880221261009593', 'NSGA-II_rank: 4', 'change: 0.29207626943720566', 'is_elite: False']\n", + "Id: 69_83 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_40', '1_1'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_83', 'origin': '68_40~CUW~1_1#MGNP'} Metrics: ['ELUC: -14.516277512052133', 'NSGA-II_crowding_distance: 0.38902735102061076', 'NSGA-II_rank: 3', 'change: 0.24480083008935272', 'is_elite: False']\n", + "Id: 69_28 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '68_64'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_28', 'origin': '68_96~CUW~68_64#MGNP'} Metrics: ['ELUC: -14.578593998110886', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.29505633708962975', 'is_elite: False']\n", + "Id: 69_86 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_100', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_86', 'origin': '67_100~CUW~68_21#MGNP'} Metrics: ['ELUC: -14.714267338613904', 'NSGA-II_crowding_distance: 0.30158738049448647', 'NSGA-II_rank: 2', 'change: 0.2439980811956137', 'is_elite: False']\n", + "Id: 69_85 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_75', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_85', 'origin': '67_75~CUW~68_21#MGNP'} Metrics: ['ELUC: -14.853158674984737', 'NSGA-II_crowding_distance: 0.26240354471423644', 'NSGA-II_rank: 1', 'change: 0.23464451501144146', 'is_elite: True']\n", + "Id: 69_51 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_89', '68_96'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_51', 'origin': '68_89~CUW~68_96#MGNP'} Metrics: ['ELUC: -14.957979648611255', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2940758045463291', 'is_elite: False']\n", + "Id: 69_21 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_95', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_21', 'origin': '67_95~CUW~68_21#MGNP'} Metrics: ['ELUC: -15.488705858751125', 'NSGA-II_crowding_distance: 0.10172825921033585', 'NSGA-II_rank: 1', 'change: 0.2469575682874243', 'is_elite: False']\n", + "Id: 69_50 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_21', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_50', 'origin': '68_21~CUW~68_21#MGNP'} Metrics: ['ELUC: -15.679681848622172', 'NSGA-II_crowding_distance: 0.025579947409199007', 'NSGA-II_rank: 1', 'change: 0.2509716075172557', 'is_elite: False']\n", + "Id: 68_21 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_93', '67_18'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_21', 'origin': '67_93~CUW~67_18#MGNP'} Metrics: ['ELUC: -15.687529779148477', 'NSGA-II_crowding_distance: 0.056966273030487596', 'NSGA-II_rank: 1', 'change: 0.2512159513288761', 'is_elite: False']\n", + "Id: 69_82 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_75', '68_40'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_82', 'origin': '68_75~CUW~68_40#MGNP'} Metrics: ['ELUC: -15.739221655096012', 'NSGA-II_crowding_distance: 0.2665712760675985', 'NSGA-II_rank: 2', 'change: 0.26945062446732615', 'is_elite: False']\n", + "Id: 69_76 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '67_95'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_76', 'origin': '68_96~CUW~67_95#MGNP'} Metrics: ['ELUC: -15.882404922018894', 'NSGA-II_crowding_distance: 0.2187847227202107', 'NSGA-II_rank: 2', 'change: 0.29524402914488485', 'is_elite: False']\n", + "Id: 69_73 Identity: {'ancestor_count': 67, 'ancestor_ids': ['2_49', '68_40'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_73', 'origin': '2_49~CUW~68_40#MGNP'} Metrics: ['ELUC: -16.098025373631224', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.32181288297368765', 'is_elite: False']\n", + "Id: 69_33 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_40', '67_69'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_33', 'origin': '68_40~CUW~67_69#MGNP'} Metrics: ['ELUC: -16.12583080440934', 'NSGA-II_crowding_distance: 0.181752298493212', 'NSGA-II_rank: 1', 'change: 0.2603977885919606', 'is_elite: True']\n", + "Id: 69_71 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_75', '68_96'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_71', 'origin': '67_75~CUW~68_96#MGNP'} Metrics: ['ELUC: -16.267068714855487', 'NSGA-II_crowding_distance: 0.1718711157457523', 'NSGA-II_rank: 1', 'change: 0.29561183240107075', 'is_elite: False']\n", + "Id: 69_61 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '67_95'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_61', 'origin': '68_96~CUW~67_95#MGNP'} Metrics: ['ELUC: -16.915045350987363', 'NSGA-II_crowding_distance: 0.056991026351047226', 'NSGA-II_rank: 1', 'change: 0.2982870852089075', 'is_elite: False']\n", + "Id: 69_65 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '68_38'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_65', 'origin': '68_96~CUW~68_38#MGNP'} Metrics: ['ELUC: -17.07112695729832', 'NSGA-II_crowding_distance: 0.05003178536880383', 'NSGA-II_rank: 1', 'change: 0.29897156842430933', 'is_elite: False']\n", + "Id: 69_37 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_96', '68_64'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_37', 'origin': '68_96~CUW~68_64#MGNP'} Metrics: ['ELUC: -17.56660494116072', 'NSGA-II_crowding_distance: 0.043496843550055335', 'NSGA-II_rank: 1', 'change: 0.30215828793828803', 'is_elite: False']\n", + "Id: 69_58 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_69', '68_96'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_58', 'origin': '67_69~CUW~68_96#MGNP'} Metrics: ['ELUC: -17.59733729173404', 'NSGA-II_crowding_distance: 0.004640267711290742', 'NSGA-II_rank: 1', 'change: 0.3030201056487295', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 68_96 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_67'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_96', 'origin': '2_49~CUW~67_67#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 69_45 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_45', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 69_49 Identity: {'ancestor_count': 67, 'ancestor_ids': ['2_49', '68_60'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_49', 'origin': '2_49~CUW~68_60#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 69.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 70...:\n", + "PopulationResponse:\n", + " Generation: 70\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/70/20240220-040604\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 70 and asking ESP for generation 71...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 70 data persisted.\n", + "Evaluated candidates:\n", + "Id: 70_91 Identity: {'ancestor_count': 66, 'ancestor_ids': ['2_49', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_91', 'origin': '2_49~CUW~67_69#MGNP'} Metrics: ['ELUC: 23.831813749185276', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30378634943376287', 'is_elite: False']\n", + "Id: 70_76 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_49', '69_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_76', 'origin': '69_49~CUW~69_69#MGNP'} Metrics: ['ELUC: 3.5178484145437245', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.31488661727998757', 'is_elite: False']\n", + "Id: 70_12 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_49', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_12', 'origin': '69_49~CUW~68_68#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 70_66 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_66', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.4053210757196104', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2521090552790074', 'is_elite: False']\n", + "Id: 70_28 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_24', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_28', 'origin': '69_24~CUW~69_49#MGNP'} Metrics: ['ELUC: 1.805135239254559', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3378989460442301', 'is_elite: False']\n", + "Id: 70_84 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_49', '68_89'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_84', 'origin': '69_49~CUW~68_89#MGNP'} Metrics: ['ELUC: 1.1954493337013117', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30673943547965027', 'is_elite: False']\n", + "Id: 70_92 Identity: {'ancestor_count': 66, 'ancestor_ids': ['68_89', '1_1'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_92', 'origin': '68_89~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.3935955863218556', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03592498468008275', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 70_61 Identity: {'ancestor_count': 67, 'ancestor_ids': ['1_1', '69_67'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_61', 'origin': '1_1~CUW~69_67#MGNP'} Metrics: ['ELUC: -0.274540885770492', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07461404232150784', 'is_elite: False']\n", + "Id: 70_56 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '69_92'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_56', 'origin': '1_1~CUW~69_92#MGNP'} Metrics: ['ELUC: -0.44988377074608454', 'NSGA-II_crowding_distance: 0.23836823347789557', 'NSGA-II_rank: 2', 'change: 0.06645724917066315', 'is_elite: False']\n", + "Id: 70_25 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_25', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.47588361634508797', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.26658578266207755', 'is_elite: False']\n", + "Id: 70_100 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_49', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_100', 'origin': '69_49~CUW~68_68#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 70_86 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_92', '68_38'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_86', 'origin': '69_92~CUW~68_38#MGNP'} Metrics: ['ELUC: -0.7933123352492807', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.0968950859797626', 'is_elite: False']\n", + "Id: 70_93 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '69_95'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_93', 'origin': '1_1~CUW~69_95#MGNP'} Metrics: ['ELUC: -1.1330195334020718', 'NSGA-II_crowding_distance: 0.2549507421322198', 'NSGA-II_rank: 1', 'change: 0.05533208411134758', 'is_elite: True']\n", + "Id: 70_34 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '69_16'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_34', 'origin': '1_1~CUW~69_16#MGNP'} Metrics: ['ELUC: -1.1380926423493216', 'NSGA-II_crowding_distance: 0.05564970938954446', 'NSGA-II_rank: 1', 'change: 0.061655947831516796', 'is_elite: False']\n", + "Id: 70_33 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_16', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_33', 'origin': '69_16~CUW~68_68#MGNP'} Metrics: ['ELUC: -1.691921396068612', 'NSGA-II_crowding_distance: 0.28320604903391466', 'NSGA-II_rank: 3', 'change: 0.09644080976421276', 'is_elite: False']\n", + "Id: 70_16 Identity: {'ancestor_count': 68, 'ancestor_ids': ['68_38', '69_92'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_16', 'origin': '68_38~CUW~69_92#MGNP'} Metrics: ['ELUC: -1.7095737585876392', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11766638708599914', 'is_elite: False']\n", + "Id: 70_47 Identity: {'ancestor_count': 67, 'ancestor_ids': ['1_1', '69_67'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_47', 'origin': '1_1~CUW~69_67#MGNP'} Metrics: ['ELUC: -1.7343376130081023', 'NSGA-II_crowding_distance: 0.1375753100478303', 'NSGA-II_rank: 1', 'change: 0.06173216408670189', 'is_elite: False']\n", + "Id: 70_45 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '1_1'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_45', 'origin': '68_68~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.765709166076626', 'NSGA-II_crowding_distance: 0.17551252668398876', 'NSGA-II_rank: 2', 'change: 0.06749159894742464', 'is_elite: False']\n", + "Id: 70_13 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_67', '69_71'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_13', 'origin': '69_67~CUW~69_71#MGNP'} Metrics: ['ELUC: -2.5308951018240045', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2736436961159028', 'is_elite: False']\n", + "Id: 70_23 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '69_16'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_23', 'origin': '1_1~CUW~69_16#MGNP'} Metrics: ['ELUC: -2.6177061782025195', 'NSGA-II_crowding_distance: 0.20231243632401688', 'NSGA-II_rank: 2', 'change: 0.08111088185845237', 'is_elite: False']\n", + "Id: 70_43 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '68_89'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_43', 'origin': '69_85~CUW~68_89#MGNP'} Metrics: ['ELUC: -2.7798130396399934', 'NSGA-II_crowding_distance: 0.25225612301740036', 'NSGA-II_rank: 3', 'change: 0.09969751842916602', 'is_elite: False']\n", + "Id: 70_58 Identity: {'ancestor_count': 68, 'ancestor_ids': ['68_68', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_58', 'origin': '68_68~CUW~69_49#MGNP'} Metrics: ['ELUC: -2.954884359979941', 'NSGA-II_crowding_distance: 1.4892283394586772', 'NSGA-II_rank: 8', 'change: 0.2474728039422189', 'is_elite: False']\n", + "Id: 70_41 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_16', '69_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_41', 'origin': '69_16~CUW~69_69#MGNP'} Metrics: ['ELUC: -3.2344471388238842', 'NSGA-II_crowding_distance: 0.22434056205014036', 'NSGA-II_rank: 1', 'change: 0.06712957256350689', 'is_elite: True']\n", + "Id: 70_88 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '69_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_88', 'origin': '68_68~CUW~69_69#MGNP'} Metrics: ['ELUC: -4.360210112715689', 'NSGA-II_crowding_distance: 0.3435279228880027', 'NSGA-II_rank: 2', 'change: 0.08296098997665824', 'is_elite: False']\n", + "Id: 70_51 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_33', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_51', 'origin': '69_33~CUW~68_68#MGNP'} Metrics: ['ELUC: -4.376185740916402', 'NSGA-II_crowding_distance: 1.4089009991894614', 'NSGA-II_rank: 6', 'change: 0.15992575742939846', 'is_elite: False']\n", + "Id: 70_64 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '69_85'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_64', 'origin': '1_1~CUW~69_85#MGNP'} Metrics: ['ELUC: -4.913968787401406', 'NSGA-II_crowding_distance: 0.32415325711371823', 'NSGA-II_rank: 3', 'change: 0.10210054195452432', 'is_elite: False']\n", + "Id: 70_73 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '69_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_73', 'origin': '69_95~CUW~69_69#MGNP'} Metrics: ['ELUC: -5.07427921936549', 'NSGA-II_crowding_distance: 0.16443219026198924', 'NSGA-II_rank: 1', 'change: 0.07199054990985586', 'is_elite: True']\n", + "Id: 70_21 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_26', '1_1'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_21', 'origin': '69_26~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.456058261819296', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11258985234610369', 'is_elite: False']\n", + "Id: 70_74 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '69_16'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_74', 'origin': '69_85~CUW~69_16#MGNP'} Metrics: ['ELUC: -5.467072621593641', 'NSGA-II_crowding_distance: 0.1542309885086415', 'NSGA-II_rank: 1', 'change: 0.07830413119721648', 'is_elite: False']\n", + "Id: 70_38 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '69_33'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_38', 'origin': '69_95~CUW~69_33#MGNP'} Metrics: ['ELUC: -6.246596173162469', 'NSGA-II_crowding_distance: 0.7903358475790058', 'NSGA-II_rank: 4', 'change: 0.10682887984063112', 'is_elite: False']\n", + "Id: 70_14 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '69_95'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_14', 'origin': '69_85~CUW~69_95#MGNP'} Metrics: ['ELUC: -6.705130446232746', 'NSGA-II_crowding_distance: 0.17223590357592833', 'NSGA-II_rank: 1', 'change: 0.09033359185068336', 'is_elite: True']\n", + "Id: 70_29 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_26', '1_1'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_29', 'origin': '69_26~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.008789620295908', 'NSGA-II_crowding_distance: 0.2591894604961731', 'NSGA-II_rank: 3', 'change: 0.10547833368394825', 'is_elite: False']\n", + "Id: 70_11 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_49', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_11', 'origin': '69_49~CUW~68_68#MGNP'} Metrics: ['ELUC: -7.09176752309131', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2369783079820598', 'is_elite: False']\n", + "Id: 70_72 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_26', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_72', 'origin': '69_26~CUW~69_49#MGNP'} Metrics: ['ELUC: -7.162625353430075', 'NSGA-II_crowding_distance: 1.0414873735063273', 'NSGA-II_rank: 6', 'change: 0.2155069692356038', 'is_elite: False']\n", + "Id: 70_27 Identity: {'ancestor_count': 66, 'ancestor_ids': ['1_1', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_27', 'origin': '1_1~CUW~67_69#MGNP'} Metrics: ['ELUC: -7.281280440226296', 'NSGA-II_crowding_distance: 1.4780858278461135', 'NSGA-II_rank: 5', 'change: 0.1493375366924374', 'is_elite: False']\n", + "Id: 69_16 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_100', '68_32'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_16', 'origin': '67_100~CUW~68_32#MGNP'} Metrics: ['ELUC: -7.413718522494573', 'NSGA-II_crowding_distance: 0.29789910282420845', 'NSGA-II_rank: 2', 'change: 0.10157375904041109', 'is_elite: False']\n", + "Id: 70_57 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_89', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_57', 'origin': '68_89~CUW~68_68#MGNP'} Metrics: ['ELUC: -7.428839910613703', 'NSGA-II_crowding_distance: 0.17439817199866883', 'NSGA-II_rank: 3', 'change: 0.12131718685540477', 'is_elite: False']\n", + "Id: 70_18 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_92', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_18', 'origin': '69_92~CUW~68_68#MGNP'} Metrics: ['ELUC: -7.4600563621402625', 'NSGA-II_crowding_distance: 0.1177486855820926', 'NSGA-II_rank: 1', 'change: 0.0958739381885641', 'is_elite: False']\n", + "Id: 70_69 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '69_26'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_69', 'origin': '1_1~CUW~69_26#MGNP'} Metrics: ['ELUC: -7.520618651221903', 'NSGA-II_crowding_distance: 0.11342125629013747', 'NSGA-II_rank: 2', 'change: 0.11554720325405951', 'is_elite: False']\n", + "Id: 70_19 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '2_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_19', 'origin': '67_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.648016995091261', 'NSGA-II_crowding_distance: 1.600168574952407', 'NSGA-II_rank: 8', 'change: 0.2827300022575132', 'is_elite: False']\n", + "Id: 70_44 Identity: {'ancestor_count': 68, 'ancestor_ids': ['68_68', '69_95'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_44', 'origin': '68_68~CUW~69_95#MGNP'} Metrics: ['ELUC: -7.732069544752585', 'NSGA-II_crowding_distance: 0.41959058708221897', 'NSGA-II_rank: 4', 'change: 0.13661902599236847', 'is_elite: False']\n", + "Id: 70_85 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '68_38'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_85', 'origin': '69_95~CUW~68_38#MGNP'} Metrics: ['ELUC: -7.797554873986586', 'NSGA-II_crowding_distance: 0.08538107664164057', 'NSGA-II_rank: 2', 'change: 0.1261595514410634', 'is_elite: False']\n", + "Id: 70_46 Identity: {'ancestor_count': 67, 'ancestor_ids': ['1_1', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_46', 'origin': '1_1~CUW~68_68#MGNP'} Metrics: ['ELUC: -7.918323382166488', 'NSGA-II_crowding_distance: 0.11575904819336322', 'NSGA-II_rank: 1', 'change: 0.10487891753522648', 'is_elite: False']\n", + "Id: 70_67 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_16', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_67', 'origin': '69_16~CUW~67_69#MGNP'} Metrics: ['ELUC: -8.007406056921592', 'NSGA-II_crowding_distance: 0.20197906748539432', 'NSGA-II_rank: 3', 'change: 0.13008866456856488', 'is_elite: False']\n", + "Id: 70_81 Identity: {'ancestor_count': 67, 'ancestor_ids': ['69_69', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_81', 'origin': '69_69~CUW~68_68#MGNP'} Metrics: ['ELUC: -8.33084201073098', 'NSGA-II_crowding_distance: 0.1860369117183759', 'NSGA-II_rank: 2', 'change: 0.12630736755886643', 'is_elite: False']\n", + "Id: 68_68 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_68', 'origin': '67_100~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.761487407874672', 'NSGA-II_crowding_distance: 0.22847745445366371', 'NSGA-II_rank: 1', 'change: 0.10832817250116257', 'is_elite: True']\n", + "Id: 70_89 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '68_38'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_89', 'origin': '69_85~CUW~68_38#MGNP'} Metrics: ['ELUC: -9.234422911648444', 'NSGA-II_crowding_distance: 0.26004203695364236', 'NSGA-II_rank: 4', 'change: 0.13903449711630514', 'is_elite: False']\n", + "Id: 69_95 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_56', '68_64'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_95', 'origin': '68_56~CUW~68_64#MGNP'} Metrics: ['ELUC: -9.251542569935316', 'NSGA-II_crowding_distance: 0.28263030741078443', 'NSGA-II_rank: 3', 'change: 0.1386005681211818', 'is_elite: False']\n", + "Id: 70_63 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '69_70'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_63', 'origin': '69_95~CUW~69_70#MGNP'} Metrics: ['ELUC: -9.28826917227594', 'NSGA-II_crowding_distance: 0.47196795178302187', 'NSGA-II_rank: 4', 'change: 0.16129845472503246', 'is_elite: False']\n", + "Id: 70_55 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_92', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_55', 'origin': '69_92~CUW~69_49#MGNP'} Metrics: ['ELUC: -9.574645529362662', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.2764537246191076', 'is_elite: False']\n", + "Id: 70_65 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_16', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_65', 'origin': '69_16~CUW~69_49#MGNP'} Metrics: ['ELUC: -9.814832916688779', 'NSGA-II_crowding_distance: 0.5910990008105385', 'NSGA-II_rank: 6', 'change: 0.21678143888831655', 'is_elite: False']\n", + "Id: 70_99 Identity: {'ancestor_count': 68, 'ancestor_ids': ['2_49', '69_33'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_99', 'origin': '2_49~CUW~69_33#MGNP'} Metrics: ['ELUC: -10.046960694133002', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.29801933799159475', 'is_elite: False']\n", + "Id: 70_82 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_69', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_82', 'origin': '67_69~CUW~68_68#MGNP'} Metrics: ['ELUC: -10.611246958301358', 'NSGA-II_crowding_distance: 0.22517519627600824', 'NSGA-II_rank: 2', 'change: 0.1340246473613188', 'is_elite: False']\n", + "Id: 70_48 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_48', 'origin': '68_38~CUW~68_68#MGNP'} Metrics: ['ELUC: -10.839906149711014', 'NSGA-II_crowding_distance: 0.26277316428345365', 'NSGA-II_rank: 1', 'change: 0.12347133827774338', 'is_elite: True']\n", + "Id: 70_98 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_98', 'origin': '69_95~CUW~67_69#MGNP'} Metrics: ['ELUC: -10.933551842924992', 'NSGA-II_crowding_distance: 0.22421690239249348', 'NSGA-II_rank: 3', 'change: 0.1479472407708167', 'is_elite: False']\n", + "Id: 70_36 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_26', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_36', 'origin': '69_26~CUW~67_69#MGNP'} Metrics: ['ELUC: -11.220170220793177', 'NSGA-II_crowding_distance: 0.26646562823731257', 'NSGA-II_rank: 3', 'change: 0.15870898292543334', 'is_elite: False']\n", + "Id: 70_32 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_26', '1_1'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_32', 'origin': '69_26~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.243286881936848', 'NSGA-II_crowding_distance: 0.16194006860154592', 'NSGA-II_rank: 2', 'change: 0.14315711506655462', 'is_elite: False']\n", + "Id: 70_35 Identity: {'ancestor_count': 68, 'ancestor_ids': ['68_38', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_35', 'origin': '68_38~CUW~69_49#MGNP'} Metrics: ['ELUC: -11.28114215615544', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2852183596132204', 'is_elite: False']\n", + "Id: 70_39 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_16', '69_85'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_39', 'origin': '69_16~CUW~69_85#MGNP'} Metrics: ['ELUC: -11.303974026200413', 'NSGA-II_crowding_distance: 0.14201523376790665', 'NSGA-II_rank: 2', 'change: 0.16697711290506637', 'is_elite: False']\n", + "Id: 70_17 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_16', '69_26'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_17', 'origin': '69_16~CUW~69_26#MGNP'} Metrics: ['ELUC: -11.517193700506732', 'NSGA-II_crowding_distance: 0.1390871015867298', 'NSGA-II_rank: 1', 'change: 0.13996864365254366', 'is_elite: False']\n", + "Id: 70_96 Identity: {'ancestor_count': 68, 'ancestor_ids': ['67_69', '69_71'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_96', 'origin': '67_69~CUW~69_71#MGNP'} Metrics: ['ELUC: -11.898895294138807', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.22964700605417218', 'is_elite: False']\n", + "Id: 70_75 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_75', 'origin': '69_95~CUW~67_69#MGNP'} Metrics: ['ELUC: -12.146265829036393', 'NSGA-II_crowding_distance: 0.11092272461828231', 'NSGA-II_rank: 2', 'change: 0.1676635516340472', 'is_elite: False']\n", + "Id: 70_87 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_70', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_87', 'origin': '69_70~CUW~68_68#MGNP'} Metrics: ['ELUC: -12.210259096348016', 'NSGA-II_crowding_distance: 0.10533790531922926', 'NSGA-II_rank: 1', 'change: 0.1417165179447905', 'is_elite: False']\n", + "Id: 70_20 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '69_14'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_20', 'origin': '69_85~CUW~69_14#MGNP'} Metrics: ['ELUC: -12.22211085488202', 'NSGA-II_crowding_distance: 1.5213835774589306', 'NSGA-II_rank: 5', 'change: 0.1970473946298537', 'is_elite: False']\n", + "Id: 70_31 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_33', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_31', 'origin': '69_33~CUW~69_49#MGNP'} Metrics: ['ELUC: -12.256592738377151', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2873936233824106', 'is_elite: False']\n", + "Id: 70_24 Identity: {'ancestor_count': 68, 'ancestor_ids': ['68_38', '69_70'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_24', 'origin': '68_38~CUW~69_70#MGNP'} Metrics: ['ELUC: -12.456798919099532', 'NSGA-II_crowding_distance: 0.13604991663877766', 'NSGA-II_rank: 1', 'change: 0.1554537369628822', 'is_elite: False']\n", + "Id: 70_26 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '69_85'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_26', 'origin': '69_95~CUW~69_85#MGNP'} Metrics: ['ELUC: -12.5435805922432', 'NSGA-II_crowding_distance: 0.9496221154673519', 'NSGA-II_rank: 4', 'change: 0.17608510781972767', 'is_elite: False']\n", + "Id: 70_94 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_26', '2_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_94', 'origin': '69_26~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.719686017720019', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2873842929230037', 'is_elite: False']\n", + "Id: 70_49 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_49', 'origin': '68_38~CUW~67_69#MGNP'} Metrics: ['ELUC: -13.081317443789263', 'NSGA-II_crowding_distance: 0.7369180714152094', 'NSGA-II_rank: 3', 'change: 0.17507494597011988', 'is_elite: False']\n", + "Id: 68_38 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '67_26'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_38', 'origin': '67_69~CUW~67_26#MGNP'} Metrics: ['ELUC: -13.095768130219115', 'NSGA-II_crowding_distance: 0.18567479008803517', 'NSGA-II_rank: 2', 'change: 0.1699699460226114', 'is_elite: False']\n", + "Id: 70_78 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_26', '68_38'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_78', 'origin': '69_26~CUW~68_38#MGNP'} Metrics: ['ELUC: -13.113479694766312', 'NSGA-II_crowding_distance: 0.09257619389607034', 'NSGA-II_rank: 1', 'change: 0.16698284921337797', 'is_elite: False']\n", + "Id: 70_95 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_95', 'origin': '68_38~CUW~67_69#MGNP'} Metrics: ['ELUC: -13.235091738382364', 'NSGA-II_crowding_distance: 0.0375872481459886', 'NSGA-II_rank: 1', 'change: 0.1698685411148772', 'is_elite: False']\n", + "Id: 70_37 Identity: {'ancestor_count': 68, 'ancestor_ids': ['68_38', '69_95'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_37', 'origin': '68_38~CUW~69_95#MGNP'} Metrics: ['ELUC: -13.271492300014508', 'NSGA-II_crowding_distance: 0.07867630697157228', 'NSGA-II_rank: 1', 'change: 0.17551652379927563', 'is_elite: False']\n", + "Id: 70_42 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_42', 'origin': '69_95~CUW~67_69#MGNP'} Metrics: ['ELUC: -13.815977306457311', 'NSGA-II_crowding_distance: 0.4672466375057392', 'NSGA-II_rank: 2', 'change: 0.19243428823648806', 'is_elite: False']\n", + "Id: 70_53 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_49', '2_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_53', 'origin': '69_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.825196037203847', 'NSGA-II_crowding_distance: 0.6691465862056012', 'NSGA-II_rank: 3', 'change: 0.2898923147156274', 'is_elite: False']\n", + "Id: 70_22 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_69', '68_38'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_22', 'origin': '67_69~CUW~68_38#MGNP'} Metrics: ['ELUC: -13.84731002101692', 'NSGA-II_crowding_distance: 0.10313260828931892', 'NSGA-II_rank: 1', 'change: 0.18295426484205268', 'is_elite: False']\n", + "Id: 67_69 Identity: {'ancestor_count': 65, 'ancestor_ids': ['63_36', '66_78'], 'birth_generation': 67, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '67_69', 'origin': '63_36~CUW~66_78#MGNP'} Metrics: ['ELUC: -13.9681855204079', 'NSGA-II_crowding_distance: 0.057277845198636275', 'NSGA-II_rank: 1', 'change: 0.1944658970894259', 'is_elite: False']\n", + "Id: 70_54 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_49', '1_1'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_54', 'origin': '69_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.978035816093854', 'NSGA-II_crowding_distance: 0.5174854803675784', 'NSGA-II_rank: 2', 'change: 0.28164124293050874', 'is_elite: False']\n", + "Id: 70_71 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_69', '67_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_71', 'origin': '67_69~CUW~67_69#MGNP'} Metrics: ['ELUC: -14.046267323599785', 'NSGA-II_crowding_distance: 0.1292741712354342', 'NSGA-II_rank: 1', 'change: 0.19666833063954653', 'is_elite: False']\n", + "Id: 70_59 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '69_85'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_59', 'origin': '69_85~CUW~69_85#MGNP'} Metrics: ['ELUC: -14.327801366466966', 'NSGA-II_crowding_distance: 0.17316768905303692', 'NSGA-II_rank: 1', 'change: 0.22693563710042977', 'is_elite: True']\n", + "Id: 70_15 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '2_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_15', 'origin': '68_38~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.379675660193989', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3121652839594485', 'is_elite: False']\n", + "Id: 69_85 Identity: {'ancestor_count': 67, 'ancestor_ids': ['67_75', '68_21'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_85', 'origin': '67_75~CUW~68_21#MGNP'} Metrics: ['ELUC: -14.853158674984737', 'NSGA-II_crowding_distance: 0.11256628362990734', 'NSGA-II_rank: 1', 'change: 0.23464451501144146', 'is_elite: False']\n", + "Id: 70_50 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '68_38'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_50', 'origin': '69_85~CUW~68_38#MGNP'} Metrics: ['ELUC: -15.248136667738287', 'NSGA-II_crowding_distance: 0.09670323266543694', 'NSGA-II_rank: 1', 'change: 0.2449045338450445', 'is_elite: False']\n", + "Id: 70_30 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_33', '69_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_30', 'origin': '69_33~CUW~69_69#MGNP'} Metrics: ['ELUC: -15.583683359637947', 'NSGA-II_crowding_distance: 0.08823399047563538', 'NSGA-II_rank: 1', 'change: 0.25110137552383544', 'is_elite: False']\n", + "Id: 70_62 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_33', '69_85'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_62', 'origin': '69_33~CUW~69_85#MGNP'} Metrics: ['ELUC: -16.044796214017534', 'NSGA-II_crowding_distance: 0.061991299575386495', 'NSGA-II_rank: 1', 'change: 0.2577120322479447', 'is_elite: False']\n", + "Id: 69_33 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_40', '67_69'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_33', 'origin': '68_40~CUW~67_69#MGNP'} Metrics: ['ELUC: -16.12583080440934', 'NSGA-II_crowding_distance: 0.04175873390128576', 'NSGA-II_rank: 1', 'change: 0.2603977885919606', 'is_elite: False']\n", + "Id: 70_68 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_68', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.139942258683586', 'NSGA-II_crowding_distance: 0.2801245851048987', 'NSGA-II_rank: 2', 'change: 0.2960953376733195', 'is_elite: False']\n", + "Id: 70_97 Identity: {'ancestor_count': 68, 'ancestor_ids': ['67_69', '69_33'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_97', 'origin': '67_69~CUW~69_33#MGNP'} Metrics: ['ELUC: -16.33992089462632', 'NSGA-II_crowding_distance: 0.13871167267541254', 'NSGA-II_rank: 1', 'change: 0.26516355104664535', 'is_elite: False']\n", + "Id: 70_79 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_71', '69_24'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_79', 'origin': '69_71~CUW~69_24#MGNP'} Metrics: ['ELUC: -16.41529042731335', 'NSGA-II_crowding_distance: 0.11275798236181603', 'NSGA-II_rank: 1', 'change: 0.296874041438848', 'is_elite: False']\n", + "Id: 70_70 Identity: {'ancestor_count': 68, 'ancestor_ids': ['2_49', '69_33'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_70', 'origin': '2_49~CUW~69_33#MGNP'} Metrics: ['ELUC: -16.426921054369295', 'NSGA-II_crowding_distance: 0.05680228349253058', 'NSGA-II_rank: 1', 'change: 0.2973316005795609', 'is_elite: False']\n", + "Id: 70_60 Identity: {'ancestor_count': 68, 'ancestor_ids': ['2_49', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_60', 'origin': '2_49~CUW~69_49#MGNP'} Metrics: ['ELUC: -17.16188451404026', 'NSGA-II_crowding_distance: 0.08001704651826932', 'NSGA-II_rank: 1', 'change: 0.3011526452304621', 'is_elite: False']\n", + "Id: 70_52 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_52', 'origin': '1_1~CUW~69_49#MGNP'} Metrics: ['ELUC: -17.53980974960568', 'NSGA-II_crowding_distance: 0.029263153005001583', 'NSGA-II_rank: 1', 'change: 0.3023208399158769', 'is_elite: False']\n", + "Id: 70_83 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_69', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_83', 'origin': '69_69~CUW~69_49#MGNP'} Metrics: ['ELUC: -17.575336639256726', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3029872650926589', 'is_elite: False']\n", + "Id: 70_40 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_24', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_40', 'origin': '69_24~CUW~69_49#MGNP'} Metrics: ['ELUC: -17.58545047504507', 'NSGA-II_crowding_distance: 0.005619465105876979', 'NSGA-II_rank: 1', 'change: 0.3026960730517769', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 69_49 Identity: {'ancestor_count': 67, 'ancestor_ids': ['2_49', '68_60'], 'birth_generation': 69, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '69_49', 'origin': '2_49~CUW~68_60#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 70_77 Identity: {'ancestor_count': 68, 'ancestor_ids': ['2_49', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_77', 'origin': '2_49~CUW~69_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 70_80 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_49', '69_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_80', 'origin': '69_49~CUW~69_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 70_90 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_90', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 70.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 71...:\n", + "PopulationResponse:\n", + " Generation: 71\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/71/20240220-041321\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 71 and asking ESP for generation 72...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 71 data persisted.\n", + "Evaluated candidates:\n", + "Id: 71_78 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_90', '70_73'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_78', 'origin': '70_90~CUW~70_73#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 71_34 Identity: {'ancestor_count': 69, 'ancestor_ids': ['2_49', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_34', 'origin': '2_49~CUW~70_59#MGNP'} Metrics: ['ELUC: 3.565179797541784', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27636908232750407', 'is_elite: False']\n", + "Id: 71_64 Identity: {'ancestor_count': 69, 'ancestor_ids': ['2_49', '70_93'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_64', 'origin': '2_49~CUW~70_93#MGNP'} Metrics: ['ELUC: 2.586455296142746', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2892143679653942', 'is_elite: False']\n", + "Id: 71_56 Identity: {'ancestor_count': 67, 'ancestor_ids': ['2_49', '68_68'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_56', 'origin': '2_49~CUW~68_68#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 71_30 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_93', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_30', 'origin': '70_93~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.234950076818912', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06555152995764739', 'is_elite: False']\n", + "Id: 71_25 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '70_47'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_25', 'origin': '1_1~CUW~70_47#MGNP'} Metrics: ['ELUC: 0.6453089806301597', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.02611704119426542', 'is_elite: False']\n", + "Id: 71_46 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_93', '70_48'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_46', 'origin': '70_93~CUW~70_48#MGNP'} Metrics: ['ELUC: 0.4526094453516692', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.08205145559628593', 'is_elite: False']\n", + "Id: 71_57 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_97', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_57', 'origin': '70_97~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.28061527010135295', 'NSGA-II_crowding_distance: 0.30084536404155093', 'NSGA-II_rank: 6', 'change: 0.09775904144140103', 'is_elite: False']\n", + "Id: 71_15 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_93', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_15', 'origin': '70_93~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.0359682134793976', 'NSGA-II_crowding_distance: 0.2494094706374304', 'NSGA-II_rank: 2', 'change: 0.05099350863912991', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 71_65 Identity: {'ancestor_count': 67, 'ancestor_ids': ['70_90', '70_71'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_65', 'origin': '70_90~CUW~70_71#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 71_80 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_80', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 71_50 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_50', 'origin': '70_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6682910644908597', 'NSGA-II_crowding_distance: 0.23346805212687732', 'NSGA-II_rank: 1', 'change: 0.049392437516290626', 'is_elite: True']\n", + "Id: 71_89 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_93'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_89', 'origin': '70_14~CUW~70_93#MGNP'} Metrics: ['ELUC: -0.9095379859086152', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0625566078343458', 'is_elite: False']\n", + "Id: 70_93 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '69_95'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_93', 'origin': '1_1~CUW~69_95#MGNP'} Metrics: ['ELUC: -1.1330195334020718', 'NSGA-II_crowding_distance: 0.14715970575418438', 'NSGA-II_rank: 1', 'change: 0.05533208411134758', 'is_elite: False']\n", + "Id: 71_83 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_93', '70_93'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_83', 'origin': '70_93~CUW~70_93#MGNP'} Metrics: ['ELUC: -1.1702773229408556', 'NSGA-II_crowding_distance: 0.08592272537633389', 'NSGA-II_rank: 3', 'change: 0.06352387867969055', 'is_elite: False']\n", + "Id: 71_98 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_41'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_98', 'origin': '70_14~CUW~70_41#MGNP'} Metrics: ['ELUC: -1.4976294210856973', 'NSGA-II_crowding_distance: 0.1644803050525822', 'NSGA-II_rank: 2', 'change: 0.061710532558642096', 'is_elite: False']\n", + "Id: 71_33 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '70_93'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_33', 'origin': '70_59~CUW~70_93#MGNP'} Metrics: ['ELUC: -1.6944970539134527', 'NSGA-II_crowding_distance: 0.2824916338150459', 'NSGA-II_rank: 6', 'change: 0.10182068750639693', 'is_elite: False']\n", + "Id: 71_85 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_93', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_85', 'origin': '70_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.8066079783131335', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23613191675173809', 'is_elite: False']\n", + "Id: 71_58 Identity: {'ancestor_count': 69, 'ancestor_ids': ['1_1', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_58', 'origin': '1_1~CUW~70_74#MGNP'} Metrics: ['ELUC: -2.087476242485865', 'NSGA-II_crowding_distance: 0.16845697335742552', 'NSGA-II_rank: 3', 'change: 0.06464632956062835', 'is_elite: False']\n", + "Id: 71_68 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_73', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_68', 'origin': '70_73~CUW~70_74#MGNP'} Metrics: ['ELUC: -2.132998018201753', 'NSGA-II_crowding_distance: 0.06654537238686406', 'NSGA-II_rank: 2', 'change: 0.06208766952516507', 'is_elite: False']\n", + "Id: 71_32 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_47', '70_73'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_32', 'origin': '70_47~CUW~70_73#MGNP'} Metrics: ['ELUC: -2.2504155253092923', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08192593649355695', 'is_elite: False']\n", + "Id: 71_48 Identity: {'ancestor_count': 69, 'ancestor_ids': ['1_1', '70_17'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_48', 'origin': '1_1~CUW~70_17#MGNP'} Metrics: ['ELUC: -2.388264581121505', 'NSGA-II_crowding_distance: 1.2981392443625706', 'NSGA-II_rank: 6', 'change: 0.104593719410007', 'is_elite: False']\n", + "Id: 71_93 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_93', 'origin': '70_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.5309685831028332', 'NSGA-II_crowding_distance: 0.15973825648520282', 'NSGA-II_rank: 2', 'change: 0.06364669254286238', 'is_elite: False']\n", + "Id: 71_69 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_41', '70_73'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_69', 'origin': '70_41~CUW~70_73#MGNP'} Metrics: ['ELUC: -2.5670349005264317', 'NSGA-II_crowding_distance: 0.15905800005317278', 'NSGA-II_rank: 1', 'change: 0.0610793461376868', 'is_elite: False']\n", + "Id: 70_41 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_16', '69_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_41', 'origin': '69_16~CUW~69_69#MGNP'} Metrics: ['ELUC: -3.2344471388238842', 'NSGA-II_crowding_distance: 0.0641678168987689', 'NSGA-II_rank: 1', 'change: 0.06712957256350689', 'is_elite: False']\n", + "Id: 71_49 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_41', '70_41'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_49', 'origin': '70_41~CUW~70_41#MGNP'} Metrics: ['ELUC: -3.2698224045291524', 'NSGA-II_crowding_distance: 0.18623510206408522', 'NSGA-II_rank: 3', 'change: 0.07109110387385954', 'is_elite: False']\n", + "Id: 71_24 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_18', '70_73'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_24', 'origin': '70_18~CUW~70_73#MGNP'} Metrics: ['ELUC: -3.2931162870384423', 'NSGA-II_crowding_distance: 0.3378845221821999', 'NSGA-II_rank: 5', 'change: 0.0852968172869162', 'is_elite: False']\n", + "Id: 71_44 Identity: {'ancestor_count': 69, 'ancestor_ids': ['1_1', '70_14'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_44', 'origin': '1_1~CUW~70_14#MGNP'} Metrics: ['ELUC: -3.3143791393613435', 'NSGA-II_crowding_distance: 0.07120928374533375', 'NSGA-II_rank: 1', 'change: 0.06754293063974508', 'is_elite: False']\n", + "Id: 71_92 Identity: {'ancestor_count': 69, 'ancestor_ids': ['1_1', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_92', 'origin': '1_1~CUW~70_74#MGNP'} Metrics: ['ELUC: -3.699552567446516', 'NSGA-II_crowding_distance: 0.5616615542511031', 'NSGA-II_rank: 4', 'change: 0.08120240195533533', 'is_elite: False']\n", + "Id: 71_99 Identity: {'ancestor_count': 69, 'ancestor_ids': ['68_68', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_99', 'origin': '68_68~CUW~70_74#MGNP'} Metrics: ['ELUC: -4.309820133249809', 'NSGA-II_crowding_distance: 0.14165250758383421', 'NSGA-II_rank: 3', 'change: 0.0746453749748781', 'is_elite: False']\n", + "Id: 71_13 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_47'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_13', 'origin': '70_14~CUW~70_47#MGNP'} Metrics: ['ELUC: -4.367112891551278', 'NSGA-II_crowding_distance: 0.19201069817703278', 'NSGA-II_rank: 2', 'change: 0.07077057846336948', 'is_elite: False']\n", + "Id: 71_79 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_41', '70_18'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_79', 'origin': '70_41~CUW~70_18#MGNP'} Metrics: ['ELUC: -4.452278028194491', 'NSGA-II_crowding_distance: 0.11500076687870692', 'NSGA-II_rank: 1', 'change: 0.06770987040062981', 'is_elite: False']\n", + "Id: 71_45 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_97', '70_90'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_45', 'origin': '70_97~CUW~70_90#MGNP'} Metrics: ['ELUC: -4.481387335566838', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.29529434387653475', 'is_elite: False']\n", + "Id: 71_42 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_93', '70_71'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_42', 'origin': '70_93~CUW~70_71#MGNP'} Metrics: ['ELUC: -4.536959511042703', 'NSGA-II_crowding_distance: 1.4818304043330073', 'NSGA-II_rank: 5', 'change: 0.10408505972355168', 'is_elite: False']\n", + "Id: 71_82 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_17', '70_93'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_82', 'origin': '70_17~CUW~70_93#MGNP'} Metrics: ['ELUC: -4.709063654377418', 'NSGA-II_crowding_distance: 0.2836140679514831', 'NSGA-II_rank: 4', 'change: 0.08734678209581977', 'is_elite: False']\n", + "Id: 71_14 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_47'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_14', 'origin': '70_14~CUW~70_47#MGNP'} Metrics: ['ELUC: -4.828651971194094', 'NSGA-II_crowding_distance: 0.1477366447472132', 'NSGA-II_rank: 3', 'change: 0.08087092354954177', 'is_elite: False']\n", + "Id: 71_72 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_41'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_72', 'origin': '70_14~CUW~70_41#MGNP'} Metrics: ['ELUC: -4.9119224515988344', 'NSGA-II_crowding_distance: 0.08287689270448953', 'NSGA-II_rank: 2', 'change: 0.07907195109863545', 'is_elite: False']\n", + "Id: 71_87 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_17', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_87', 'origin': '70_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.930972606758665', 'NSGA-II_crowding_distance: 0.09087396447004187', 'NSGA-II_rank: 2', 'change: 0.08502589923382935', 'is_elite: False']\n", + "Id: 71_43 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_73', '70_93'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_43', 'origin': '70_73~CUW~70_93#MGNP'} Metrics: ['ELUC: -5.04124581685412', 'NSGA-II_crowding_distance: 0.18930208412888327', 'NSGA-II_rank: 3', 'change: 0.09963286154417512', 'is_elite: False']\n", + "Id: 70_73 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_95', '69_69'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_73', 'origin': '69_95~CUW~69_69#MGNP'} Metrics: ['ELUC: -5.07427921936549', 'NSGA-II_crowding_distance: 0.10046672949931412', 'NSGA-II_rank: 1', 'change: 0.07199054990985586', 'is_elite: False']\n", + "Id: 71_53 Identity: {'ancestor_count': 69, 'ancestor_ids': ['2_49', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_53', 'origin': '2_49~CUW~70_74#MGNP'} Metrics: ['ELUC: -5.2267015433131165', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.27392517419122325', 'is_elite: False']\n", + "Id: 71_97 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_41', '70_14'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_97', 'origin': '70_41~CUW~70_14#MGNP'} Metrics: ['ELUC: -5.575410938358258', 'NSGA-II_crowding_distance: 0.1542309885086415', 'NSGA-II_rank: 1', 'change: 0.07862699192022268', 'is_elite: False']\n", + "Id: 71_66 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_73', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_66', 'origin': '70_73~CUW~70_59#MGNP'} Metrics: ['ELUC: -5.782559783423906', 'NSGA-II_crowding_distance: 0.12064535401233281', 'NSGA-II_rank: 2', 'change: 0.09056903967721426', 'is_elite: False']\n", + "Id: 71_94 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_48', '70_46'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_94', 'origin': '70_48~CUW~70_46#MGNP'} Metrics: ['ELUC: -5.873914034053832', 'NSGA-II_crowding_distance: 1.2042649107178658', 'NSGA-II_rank: 4', 'change: 0.11219619877388738', 'is_elite: False']\n", + "Id: 71_38 Identity: {'ancestor_count': 69, 'ancestor_ids': ['2_49', '70_41'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_38', 'origin': '2_49~CUW~70_41#MGNP'} Metrics: ['ELUC: -5.940090526401121', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.27738514737476433', 'is_elite: False']\n", + "Id: 71_35 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_47', '70_71'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_35', 'origin': '70_47~CUW~70_71#MGNP'} Metrics: ['ELUC: -6.093634269966743', 'NSGA-II_crowding_distance: 0.15997953401441734', 'NSGA-II_rank: 3', 'change: 0.10746911101643537', 'is_elite: False']\n", + "Id: 71_29 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_41', '70_90'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_29', 'origin': '70_41~CUW~70_90#MGNP'} Metrics: ['ELUC: -6.2636674419822205', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.25563370680803693', 'is_elite: False']\n", + "Id: 71_73 Identity: {'ancestor_count': 69, 'ancestor_ids': ['68_68', '70_17'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_73', 'origin': '68_68~CUW~70_17#MGNP'} Metrics: ['ELUC: -6.269501825520713', 'NSGA-II_crowding_distance: 0.3519481549799478', 'NSGA-II_rank: 3', 'change: 0.11947848640463161', 'is_elite: False']\n", + "Id: 71_16 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_17'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_16', 'origin': '70_14~CUW~70_17#MGNP'} Metrics: ['ELUC: -6.491058208488615', 'NSGA-II_crowding_distance: 0.17153878833522918', 'NSGA-II_rank: 2', 'change: 0.0936685353569475', 'is_elite: False']\n", + "Id: 70_14 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '69_95'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_14', 'origin': '69_85~CUW~69_95#MGNP'} Metrics: ['ELUC: -6.705130446232746', 'NSGA-II_crowding_distance: 0.2807511287866329', 'NSGA-II_rank: 1', 'change: 0.09033359185068336', 'is_elite: True']\n", + "Id: 71_27 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_79', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_27', 'origin': '70_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.354802290847546', 'NSGA-II_crowding_distance: 1.3004673932410986', 'NSGA-II_rank: 6', 'change: 0.2518862991963755', 'is_elite: False']\n", + "Id: 71_96 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_46', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_96', 'origin': '70_46~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.411455032964314', 'NSGA-II_crowding_distance: 0.19580951350677206', 'NSGA-II_rank: 2', 'change: 0.11251022014602693', 'is_elite: False']\n", + "Id: 71_74 Identity: {'ancestor_count': 68, 'ancestor_ids': ['2_49', '70_48'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_74', 'origin': '2_49~CUW~70_48#MGNP'} Metrics: ['ELUC: -7.797276323433195', 'NSGA-II_crowding_distance: 0.4010153915958784', 'NSGA-II_rank: 6', 'change: 0.25962597186316216', 'is_elite: False']\n", + "Id: 71_21 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_17', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_21', 'origin': '70_17~CUW~70_59#MGNP'} Metrics: ['ELUC: -8.44569627201127', 'NSGA-II_crowding_distance: 0.1750852416144144', 'NSGA-II_rank: 2', 'change: 0.11715356924311093', 'is_elite: False']\n", + "Id: 68_68 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_68', 'origin': '67_100~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.761487407874672', 'NSGA-II_crowding_distance: 0.25237483389306575', 'NSGA-II_rank: 1', 'change: 0.10832817250116257', 'is_elite: True']\n", + "Id: 71_90 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_17', '70_47'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_90', 'origin': '70_17~CUW~70_47#MGNP'} Metrics: ['ELUC: -9.236569592180393', 'NSGA-II_crowding_distance: 0.3433697676989265', 'NSGA-II_rank: 3', 'change: 0.14383989656838636', 'is_elite: False']\n", + "Id: 71_67 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_48', '70_41'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_67', 'origin': '70_48~CUW~70_41#MGNP'} Metrics: ['ELUC: -9.249649976796151', 'NSGA-II_crowding_distance: 0.18181409037503876', 'NSGA-II_rank: 2', 'change: 0.1320283280859514', 'is_elite: False']\n", + "Id: 71_39 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_48', '68_68'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_39', 'origin': '70_48~CUW~68_68#MGNP'} Metrics: ['ELUC: -9.37054474379553', 'NSGA-II_crowding_distance: 0.1040908021053508', 'NSGA-II_rank: 1', 'change: 0.12040371592830211', 'is_elite: False']\n", + "Id: 71_81 Identity: {'ancestor_count': 67, 'ancestor_ids': ['70_90', '68_68'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_81', 'origin': '70_90~CUW~68_68#MGNP'} Metrics: ['ELUC: -9.469965349252744', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2978429778191486', 'is_elite: False']\n", + "Id: 71_95 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_48', '70_17'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_95', 'origin': '70_48~CUW~70_17#MGNP'} Metrics: ['ELUC: -9.524533555950649', 'NSGA-II_crowding_distance: 0.26825963833405686', 'NSGA-II_rank: 3', 'change: 0.15184270079876316', 'is_elite: False']\n", + "Id: 71_12 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_17', '70_41'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_12', 'origin': '70_17~CUW~70_41#MGNP'} Metrics: ['ELUC: -9.793231388945065', 'NSGA-II_crowding_distance: 0.09385130614269054', 'NSGA-II_rank: 1', 'change: 0.12187753481150901', 'is_elite: False']\n", + "Id: 71_41 Identity: {'ancestor_count': 69, 'ancestor_ids': ['68_68', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_41', 'origin': '68_68~CUW~70_59#MGNP'} Metrics: ['ELUC: -10.015969630857466', 'NSGA-II_crowding_distance: 0.17264861629545428', 'NSGA-II_rank: 2', 'change: 0.1429674834678302', 'is_elite: False']\n", + "Id: 71_71 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_71', 'origin': '68_68~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.341591902770315', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.27599597546010685', 'is_elite: False']\n", + "Id: 71_20 Identity: {'ancestor_count': 69, 'ancestor_ids': ['2_49', '70_73'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_20', 'origin': '2_49~CUW~70_73#MGNP'} Metrics: ['ELUC: -10.550571491831358', 'NSGA-II_crowding_distance: 1.6621154778178', 'NSGA-II_rank: 5', 'change: 0.2518699341273246', 'is_elite: False']\n", + "Id: 70_48 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_38', '68_68'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_48', 'origin': '68_38~CUW~68_68#MGNP'} Metrics: ['ELUC: -10.839906149711014', 'NSGA-II_crowding_distance: 0.220753729664581', 'NSGA-II_rank: 1', 'change: 0.12347133827774338', 'is_elite: False']\n", + "Id: 71_61 Identity: {'ancestor_count': 67, 'ancestor_ids': ['70_71', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_61', 'origin': '70_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.169101105343055', 'NSGA-II_crowding_distance: 0.13675969843240265', 'NSGA-II_rank: 2', 'change: 0.14952481166147297', 'is_elite: False']\n", + "Id: 71_55 Identity: {'ancestor_count': 69, 'ancestor_ids': ['1_1', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_55', 'origin': '1_1~CUW~70_59#MGNP'} Metrics: ['ELUC: -11.241381484961494', 'NSGA-II_crowding_distance: 0.5532125051206223', 'NSGA-II_rank: 3', 'change: 0.17802342314386407', 'is_elite: False']\n", + "Id: 71_28 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_93', '70_24'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_28', 'origin': '70_93~CUW~70_24#MGNP'} Metrics: ['ELUC: -11.521108740987248', 'NSGA-II_crowding_distance: 0.15358843722436916', 'NSGA-II_rank: 2', 'change: 0.15707771524178532', 'is_elite: False']\n", + "Id: 71_86 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_17', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_86', 'origin': '70_17~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.635982998761419', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.31700828959980953', 'is_elite: False']\n", + "Id: 71_77 Identity: {'ancestor_count': 68, 'ancestor_ids': ['2_49', '70_47'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_77', 'origin': '2_49~CUW~70_47#MGNP'} Metrics: ['ELUC: -11.769012319184544', 'NSGA-II_crowding_distance: 1.1964990999711802', 'NSGA-II_rank: 4', 'change: 0.2515531157053966', 'is_elite: False']\n", + "Id: 71_47 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_41', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_47', 'origin': '70_41~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.90221274094189', 'NSGA-II_crowding_distance: 0.45485724062882665', 'NSGA-II_rank: 3', 'change: 0.2513828002742723', 'is_elite: False']\n", + "Id: 71_84 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_24'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_84', 'origin': '70_14~CUW~70_24#MGNP'} Metrics: ['ELUC: -12.193202881921717', 'NSGA-II_crowding_distance: 0.21800331658535693', 'NSGA-II_rank: 1', 'change: 0.14701727227825112', 'is_elite: False']\n", + "Id: 71_22 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_22', 'origin': '70_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.41318849819718', 'NSGA-II_crowding_distance: 0.23407353503103123', 'NSGA-II_rank: 4', 'change: 0.2824734573442996', 'is_elite: False']\n", + "Id: 71_26 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_17', '70_97'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_26', 'origin': '70_17~CUW~70_97#MGNP'} Metrics: ['ELUC: -12.524879371400772', 'NSGA-II_crowding_distance: 0.16745150098279596', 'NSGA-II_rank: 2', 'change: 0.17085163006236673', 'is_elite: False']\n", + "Id: 71_31 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_24', '70_48'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_31', 'origin': '70_24~CUW~70_48#MGNP'} Metrics: ['ELUC: -12.64792203152224', 'NSGA-II_crowding_distance: 0.16402804631591794', 'NSGA-II_rank: 1', 'change: 0.15783608291948434', 'is_elite: False']\n", + "Id: 71_70 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_90', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_70', 'origin': '70_90~CUW~70_74#MGNP'} Metrics: ['ELUC: -12.714441002388092', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28987457674647343', 'is_elite: False']\n", + "Id: 71_51 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_71', '70_47'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_51', 'origin': '70_71~CUW~70_47#MGNP'} Metrics: ['ELUC: -12.825233172326152', 'NSGA-II_crowding_distance: 0.17680131606039048', 'NSGA-II_rank: 2', 'change: 0.18318007504001352', 'is_elite: False']\n", + "Id: 71_75 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_48', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_75', 'origin': '70_48~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.957289724809247', 'NSGA-II_crowding_distance: 0.5235437209784016', 'NSGA-II_rank: 3', 'change: 0.2638188105084684', 'is_elite: False']\n", + "Id: 71_36 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_36', 'origin': '70_59~CUW~70_59#MGNP'} Metrics: ['ELUC: -13.087684734484633', 'NSGA-II_crowding_distance: 0.12295214151646766', 'NSGA-II_rank: 2', 'change: 0.21174690563269877', 'is_elite: False']\n", + "Id: 71_100 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_100', 'origin': '70_14~CUW~70_59#MGNP'} Metrics: ['ELUC: -13.138132067193967', 'NSGA-II_crowding_distance: 0.5514980947987735', 'NSGA-II_rank: 2', 'change: 0.21290535502798535', 'is_elite: False']\n", + "Id: 71_17 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_74', '70_97'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_17', 'origin': '70_74~CUW~70_97#MGNP'} Metrics: ['ELUC: -13.339045104486868', 'NSGA-II_crowding_distance: 0.2611650977773855', 'NSGA-II_rank: 1', 'change: 0.17651429020237525', 'is_elite: True']\n", + "Id: 71_37 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_73', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_37', 'origin': '70_73~CUW~70_59#MGNP'} Metrics: ['ELUC: -13.59281964351472', 'NSGA-II_crowding_distance: 0.22522072571002846', 'NSGA-II_rank: 1', 'change: 0.21972672420567696', 'is_elite: True']\n", + "Id: 70_59 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '69_85'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_59', 'origin': '69_85~CUW~69_85#MGNP'} Metrics: ['ELUC: -14.327801366466966', 'NSGA-II_crowding_distance: 0.09816588873880985', 'NSGA-II_rank: 1', 'change: 0.22693563710042977', 'is_elite: False']\n", + "Id: 71_52 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_52', 'origin': '70_59~CUW~70_74#MGNP'} Metrics: ['ELUC: -14.681517273972478', 'NSGA-II_crowding_distance: 0.426205264748706', 'NSGA-II_rank: 1', 'change: 0.23054170342647154', 'is_elite: True']\n", + "Id: 71_91 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_90', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_91', 'origin': '70_90~CUW~70_74#MGNP'} Metrics: ['ELUC: -16.08974773171062', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3135514113804574', 'is_elite: False']\n", + "Id: 71_60 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_41', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_60', 'origin': '70_41~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.65931416374004', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3095649844400603', 'is_elite: False']\n", + "Id: 71_18 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_74', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_18', 'origin': '70_74~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.44664783700847', 'NSGA-II_crowding_distance: 0.4066679821524545', 'NSGA-II_rank: 1', 'change: 0.30117800411652845', 'is_elite: True']\n", + "Id: 71_76 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_90'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_76', 'origin': '70_14~CUW~70_90#MGNP'} Metrics: ['ELUC: -17.568499090306197', 'NSGA-II_crowding_distance: 0.014748237244084788', 'NSGA-II_rank: 1', 'change: 0.3028893953515811', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 70_90 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_90', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_11 Identity: {'ancestor_count': 3, 'ancestor_ids': ['70_90', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_11', 'origin': '70_90~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_19 Identity: {'ancestor_count': 69, 'ancestor_ids': ['2_49', '70_24'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_19', 'origin': '2_49~CUW~70_24#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_23 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_23', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_40 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_40', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_54 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_48', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_54', 'origin': '70_48~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_59 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_59', 'origin': '70_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_62 Identity: {'ancestor_count': 69, 'ancestor_ids': ['2_49', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_62', 'origin': '2_49~CUW~70_59#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_63 Identity: {'ancestor_count': 3, 'ancestor_ids': ['70_90', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_63', 'origin': '70_90~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 71_88 Identity: {'ancestor_count': 3, 'ancestor_ids': ['70_90', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_88', 'origin': '70_90~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 71.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 72...:\n", + "PopulationResponse:\n", + " Generation: 72\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/72/20240220-042048\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 72 and asking ESP for generation 73...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 72 data persisted.\n", + "Evaluated candidates:\n", + "Id: 72_49 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_50', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_49', 'origin': '71_50~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 72_14 Identity: {'ancestor_count': 69, 'ancestor_ids': ['71_39', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_14', 'origin': '71_39~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.01589244460171', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.30008912026482576', 'is_elite: False']\n", + "Id: 72_43 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_43', 'origin': '70_14~CUW~71_88#MGNP'} Metrics: ['ELUC: 22.91327472798315', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.301170506814611', 'is_elite: False']\n", + "Id: 72_95 Identity: {'ancestor_count': 70, 'ancestor_ids': ['2_49', '71_97'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_95', 'origin': '2_49~CUW~71_97#MGNP'} Metrics: ['ELUC: 21.759027128012086', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2972055298740991', 'is_elite: False']\n", + "Id: 72_31 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_31', 'origin': '71_18~CUW~1_1#MGNP'} Metrics: ['ELUC: 19.75216813798394', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2857411618296481', 'is_elite: False']\n", + "Id: 72_66 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_66', 'origin': '71_52~CUW~2_49#MGNP'} Metrics: ['ELUC: 17.00578624379071', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2840211991797085', 'is_elite: False']\n", + "Id: 72_88 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_88', 'origin': '71_18~CUW~1_1#MGNP'} Metrics: ['ELUC: 5.915409045116226', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2263585049017294', 'is_elite: False']\n", + "Id: 72_54 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_31', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_54', 'origin': '71_31~CUW~71_88#MGNP'} Metrics: ['ELUC: 5.19693214778614', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.22574857534803922', 'is_elite: False']\n", + "Id: 72_68 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_37', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_68', 'origin': '71_37~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 72_37 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_48', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_37', 'origin': '70_48~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.8539004595336315', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.2700899870440588', 'is_elite: False']\n", + "Id: 72_51 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_51', 'origin': '1_1~CUW~71_88#MGNP'} Metrics: ['ELUC: 1.6878373745116588', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.32299587803838975', 'is_elite: False']\n", + "Id: 72_33 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_31', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_33', 'origin': '71_31~CUW~71_18#MGNP'} Metrics: ['ELUC: 1.214857725930434', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.3005591332446814', 'is_elite: False']\n", + "Id: 72_42 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_48', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_42', 'origin': '70_48~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.5223212951873317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07952189386586835', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 72_73 Identity: {'ancestor_count': 4, 'ancestor_ids': ['1_1', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_73', 'origin': '1_1~CUW~71_88#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.6152843256223844', 'NSGA-II_rank: 6', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 71_50 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_50', 'origin': '70_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6682910644908597', 'NSGA-II_crowding_distance: 0.30066344653452987', 'NSGA-II_rank: 1', 'change: 0.049392437516290626', 'is_elite: True']\n", + "Id: 72_62 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_50', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_62', 'origin': '71_50~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.3078181189081095', 'NSGA-II_crowding_distance: 0.4990578076651724', 'NSGA-II_rank: 6', 'change: 0.24405428877926544', 'is_elite: False']\n", + "Id: 72_47 Identity: {'ancestor_count': 70, 'ancestor_ids': ['1_1', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_47', 'origin': '1_1~CUW~71_52#MGNP'} Metrics: ['ELUC: -2.0110905183385466', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09640175418758692', 'is_elite: False']\n", + "Id: 72_83 Identity: {'ancestor_count': 70, 'ancestor_ids': ['1_1', '71_79'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_83', 'origin': '1_1~CUW~71_79#MGNP'} Metrics: ['ELUC: -2.16204139635111', 'NSGA-II_crowding_distance: 0.5956333874062523', 'NSGA-II_rank: 5', 'change: 0.11127020871246729', 'is_elite: False']\n", + "Id: 72_82 Identity: {'ancestor_count': 68, 'ancestor_ids': ['1_1', '70_48'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_82', 'origin': '1_1~CUW~70_48#MGNP'} Metrics: ['ELUC: -2.4109087330387284', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09278564365628629', 'is_elite: False']\n", + "Id: 72_13 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_13', 'origin': '70_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.5507737660835734', 'NSGA-II_crowding_distance: 0.1987482876062859', 'NSGA-II_rank: 1', 'change: 0.051321966076217355', 'is_elite: False']\n", + "Id: 72_29 Identity: {'ancestor_count': 69, 'ancestor_ids': ['1_1', '71_39'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_29', 'origin': '1_1~CUW~71_39#MGNP'} Metrics: ['ELUC: -2.607507573344365', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.07470297928928747', 'is_elite: False']\n", + "Id: 72_81 Identity: {'ancestor_count': 69, 'ancestor_ids': ['1_1', '70_14'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_81', 'origin': '1_1~CUW~70_14#MGNP'} Metrics: ['ELUC: -3.2923728804994368', 'NSGA-II_crowding_distance: 0.3186736206370886', 'NSGA-II_rank: 3', 'change: 0.09076686169484845', 'is_elite: False']\n", + "Id: 72_28 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_31', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_28', 'origin': '71_31~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.4301700339574333', 'NSGA-II_crowding_distance: 0.2872566790989095', 'NSGA-II_rank: 3', 'change: 0.0986759680787678', 'is_elite: False']\n", + "Id: 72_27 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '70_48'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_27', 'origin': '71_18~CUW~70_48#MGNP'} Metrics: ['ELUC: -3.5384491729634266', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30511194210185877', 'is_elite: False']\n", + "Id: 72_70 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_14', '71_69'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_70', 'origin': '70_14~CUW~71_69#MGNP'} Metrics: ['ELUC: -3.590849331310257', 'NSGA-II_crowding_distance: 0.10636946904573219', 'NSGA-II_rank: 1', 'change: 0.059097782881367834', 'is_elite: False']\n", + "Id: 72_18 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_79', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_18', 'origin': '71_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.7109666555898864', 'NSGA-II_crowding_distance: 0.09564680694631567', 'NSGA-II_rank: 1', 'change: 0.06337141426007153', 'is_elite: False']\n", + "Id: 72_99 Identity: {'ancestor_count': 70, 'ancestor_ids': ['1_1', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_99', 'origin': '1_1~CUW~71_17#MGNP'} Metrics: ['ELUC: -4.04019735939035', 'NSGA-II_crowding_distance: 0.6141330213916412', 'NSGA-II_rank: 4', 'change: 0.11281227774201312', 'is_elite: False']\n", + "Id: 72_26 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_26', 'origin': '70_14~CUW~71_88#MGNP'} Metrics: ['ELUC: -4.041211778529465', 'NSGA-II_crowding_distance: 0.5144571975380351', 'NSGA-II_rank: 6', 'change: 0.2625053708591613', 'is_elite: False']\n", + "Id: 72_56 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '71_69'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_56', 'origin': '71_52~CUW~71_69#MGNP'} Metrics: ['ELUC: -4.152254920697652', 'NSGA-II_crowding_distance: 0.148560427872712', 'NSGA-II_rank: 2', 'change: 0.07661279268748268', 'is_elite: False']\n", + "Id: 72_92 Identity: {'ancestor_count': 70, 'ancestor_ids': ['68_68', '71_50'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_92', 'origin': '68_68~CUW~71_50#MGNP'} Metrics: ['ELUC: -4.193041058823491', 'NSGA-II_crowding_distance: 0.1678113019169145', 'NSGA-II_rank: 2', 'change: 0.08380204860916031', 'is_elite: False']\n", + "Id: 72_39 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_14', '71_50'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_39', 'origin': '70_14~CUW~71_50#MGNP'} Metrics: ['ELUC: -4.420639659187494', 'NSGA-II_crowding_distance: 0.22571470268503424', 'NSGA-II_rank: 1', 'change: 0.07355486094629528', 'is_elite: True']\n", + "Id: 72_85 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_37', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_85', 'origin': '71_37~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.588945843096956', 'NSGA-II_crowding_distance: 0.6062142011717203', 'NSGA-II_rank: 5', 'change: 0.1380337516905299', 'is_elite: False']\n", + "Id: 72_75 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_14', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_75', 'origin': '70_14~CUW~71_17#MGNP'} Metrics: ['ELUC: -5.805694219762312', 'NSGA-II_crowding_distance: 0.2459846388215653', 'NSGA-II_rank: 2', 'change: 0.08901433862916872', 'is_elite: False']\n", + "Id: 72_90 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_37', '68_68'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_90', 'origin': '71_37~CUW~68_68#MGNP'} Metrics: ['ELUC: -5.976661847356869', 'NSGA-II_crowding_distance: 0.9606016091624093', 'NSGA-II_rank: 5', 'change: 0.15036032038239142', 'is_elite: False']\n", + "Id: 72_46 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '71_50'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_46', 'origin': '71_18~CUW~71_50#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.4136120880410114', 'NSGA-II_rank: 6', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 72_15 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_97', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_15', 'origin': '71_97~CUW~71_17#MGNP'} Metrics: ['ELUC: -6.32964610089206', 'NSGA-II_crowding_distance: 0.18616418348770014', 'NSGA-II_rank: 1', 'change: 0.08627985416800038', 'is_elite: False']\n", + "Id: 72_12 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_93', '70_48'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_12', 'origin': '70_93~CUW~70_48#MGNP'} Metrics: ['ELUC: -6.562752150919909', 'NSGA-II_crowding_distance: 0.2528426894409533', 'NSGA-II_rank: 2', 'change: 0.1028138379310796', 'is_elite: False']\n", + "Id: 72_45 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_37', '70_14'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_45', 'origin': '71_37~CUW~70_14#MGNP'} Metrics: ['ELUC: -6.591317278533907', 'NSGA-II_crowding_distance: 0.31719282615874966', 'NSGA-II_rank: 3', 'change: 0.1115897858679085', 'is_elite: False']\n", + "Id: 70_14 Identity: {'ancestor_count': 68, 'ancestor_ids': ['69_85', '69_95'], 'birth_generation': 70, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '70_14', 'origin': '69_85~CUW~69_95#MGNP'} Metrics: ['ELUC: -6.705130446232746', 'NSGA-II_crowding_distance: 0.21220557594603456', 'NSGA-II_rank: 1', 'change: 0.09033359185068336', 'is_elite: False']\n", + "Id: 72_84 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_14', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_84', 'origin': '70_14~CUW~71_17#MGNP'} Metrics: ['ELUC: -7.3527482306681575', 'NSGA-II_crowding_distance: 0.10583698741886213', 'NSGA-II_rank: 3', 'change: 0.1178966917490316', 'is_elite: False']\n", + "Id: 72_58 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_58', 'origin': '71_52~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.73930402764637', 'NSGA-II_crowding_distance: 0.4256738511351562', 'NSGA-II_rank: 4', 'change: 0.13716949444885565', 'is_elite: False']\n", + "Id: 72_11 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '68_68'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_11', 'origin': '68_68~CUW~68_68#MGNP'} Metrics: ['ELUC: -7.887057649901845', 'NSGA-II_crowding_distance: 0.0976101308022673', 'NSGA-II_rank: 3', 'change: 0.11817966991844302', 'is_elite: False']\n", + "Id: 72_61 Identity: {'ancestor_count': 70, 'ancestor_ids': ['68_68', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_61', 'origin': '68_68~CUW~71_52#MGNP'} Metrics: ['ELUC: -8.074793188552341', 'NSGA-II_crowding_distance: 0.29046113098939896', 'NSGA-II_rank: 4', 'change: 0.13779218661494977', 'is_elite: False']\n", + "Id: 72_50 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_31', '71_97'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_50', 'origin': '71_31~CUW~71_97#MGNP'} Metrics: ['ELUC: -8.155586932264848', 'NSGA-II_crowding_distance: 0.22628111415712196', 'NSGA-II_rank: 2', 'change: 0.10988199938097917', 'is_elite: False']\n", + "Id: 72_93 Identity: {'ancestor_count': 70, 'ancestor_ids': ['68_68', '71_97'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_93', 'origin': '68_68~CUW~71_97#MGNP'} Metrics: ['ELUC: -8.293356601433103', 'NSGA-II_crowding_distance: 0.18888660906581628', 'NSGA-II_rank: 3', 'change: 0.12740383549233508', 'is_elite: False']\n", + "Id: 72_24 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_88', '71_37'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_24', 'origin': '71_88~CUW~71_37#MGNP'} Metrics: ['ELUC: -8.362417058020338', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2950137204175064', 'is_elite: False']\n", + "Id: 72_77 Identity: {'ancestor_count': 70, 'ancestor_ids': ['68_68', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_77', 'origin': '68_68~CUW~71_18#MGNP'} Metrics: ['ELUC: -8.615793417675652', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.272679179964699', 'is_elite: False']\n", + "Id: 68_68 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_68', 'origin': '67_100~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.761487407874672', 'NSGA-II_crowding_distance: 0.2197485725475648', 'NSGA-II_rank: 1', 'change: 0.10832817250116257', 'is_elite: True']\n", + "Id: 72_21 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '68_68'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_21', 'origin': '68_68~CUW~68_68#MGNP'} Metrics: ['ELUC: -8.823109661206278', 'NSGA-II_crowding_distance: 0.15517478389654532', 'NSGA-II_rank: 2', 'change: 0.11906068073736682', 'is_elite: False']\n", + "Id: 72_96 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_96', 'origin': '71_52~CUW~71_18#MGNP'} Metrics: ['ELUC: -8.915667198041744', 'NSGA-II_crowding_distance: 0.6816527698033481', 'NSGA-II_rank: 6', 'change: 0.2723160914668574', 'is_elite: False']\n", + "Id: 72_48 Identity: {'ancestor_count': 67, 'ancestor_ids': ['1_1', '68_68'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_48', 'origin': '1_1~CUW~68_68#MGNP'} Metrics: ['ELUC: -9.328398474379544', 'NSGA-II_crowding_distance: 0.23799935110746215', 'NSGA-II_rank: 3', 'change: 0.14168389500389447', 'is_elite: False']\n", + "Id: 72_23 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_84', '71_50'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_23', 'origin': '71_84~CUW~71_50#MGNP'} Metrics: ['ELUC: -9.353687167307461', 'NSGA-II_crowding_distance: 0.06951172266959287', 'NSGA-II_rank: 1', 'change: 0.11095484490746799', 'is_elite: False']\n", + "Id: 72_41 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_69', '68_68'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_41', 'origin': '71_69~CUW~68_68#MGNP'} Metrics: ['ELUC: -9.477101067318314', 'NSGA-II_crowding_distance: 0.2699531982366158', 'NSGA-II_rank: 2', 'change: 0.12455160060801523', 'is_elite: False']\n", + "Id: 72_89 Identity: {'ancestor_count': 68, 'ancestor_ids': ['70_48', '68_68'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_89', 'origin': '70_48~CUW~68_68#MGNP'} Metrics: ['ELUC: -9.690146154465113', 'NSGA-II_crowding_distance: 0.07601943784206841', 'NSGA-II_rank: 1', 'change: 0.11330929632103146', 'is_elite: False']\n", + "Id: 72_30 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_93', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_30', 'origin': '70_93~CUW~71_18#MGNP'} Metrics: ['ELUC: -9.724057961797559', 'NSGA-II_crowding_distance: 1.2972765273523739', 'NSGA-II_rank: 5', 'change: 0.23615116161651534', 'is_elite: False']\n", + "Id: 72_35 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_48', '71_39'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_35', 'origin': '70_48~CUW~71_39#MGNP'} Metrics: ['ELUC: -10.080988766741994', 'NSGA-II_crowding_distance: 0.17472265096869077', 'NSGA-II_rank: 1', 'change: 0.12129481874532186', 'is_elite: False']\n", + "Id: 72_20 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_17', '71_50'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_20', 'origin': '71_17~CUW~71_50#MGNP'} Metrics: ['ELUC: -10.126694632077221', 'NSGA-II_crowding_distance: 0.9590284348225715', 'NSGA-II_rank: 4', 'change: 0.16041054382189515', 'is_elite: False']\n", + "Id: 72_36 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_37', '71_31'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_36', 'origin': '71_37~CUW~71_31#MGNP'} Metrics: ['ELUC: -10.410842013116804', 'NSGA-II_crowding_distance: 0.17133946063188832', 'NSGA-II_rank: 3', 'change: 0.15295681977180928', 'is_elite: False']\n", + "Id: 72_16 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_16', 'origin': '71_18~CUW~71_17#MGNP'} Metrics: ['ELUC: -10.452778587234354', 'NSGA-II_crowding_distance: 0.5818536825018018', 'NSGA-II_rank: 6', 'change: 0.29704444383214507', 'is_elite: False']\n", + "Id: 72_64 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_39', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_64', 'origin': '71_39~CUW~71_17#MGNP'} Metrics: ['ELUC: -10.827839064605802', 'NSGA-II_crowding_distance: 0.2211007221382969', 'NSGA-II_rank: 3', 'change: 0.160416490826346', 'is_elite: False']\n", + "Id: 72_25 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_50', '71_31'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_25', 'origin': '71_50~CUW~71_31#MGNP'} Metrics: ['ELUC: -11.0591810809031', 'NSGA-II_crowding_distance: 0.2240617729032156', 'NSGA-II_rank: 2', 'change: 0.1455524163340418', 'is_elite: False']\n", + "Id: 72_80 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_48', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_80', 'origin': '70_48~CUW~71_17#MGNP'} Metrics: ['ELUC: -11.203758136534244', 'NSGA-II_crowding_distance: 0.292723619504885', 'NSGA-II_rank: 2', 'change: 0.14853561333766405', 'is_elite: False']\n", + "Id: 72_98 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '71_84'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_98', 'origin': '71_52~CUW~71_84#MGNP'} Metrics: ['ELUC: -11.282684965973782', 'NSGA-II_crowding_distance: 0.20343681910940725', 'NSGA-II_rank: 1', 'change: 0.13841676716567644', 'is_elite: False']\n", + "Id: 72_87 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_87', 'origin': '70_14~CUW~71_88#MGNP'} Metrics: ['ELUC: -11.358600923613997', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.30806605763560346', 'is_elite: False']\n", + "Id: 72_94 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '70_14'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_94', 'origin': '71_52~CUW~70_14#MGNP'} Metrics: ['ELUC: -11.566979551789169', 'NSGA-II_crowding_distance: 0.13725881676644353', 'NSGA-II_rank: 1', 'change: 0.15677811029363617', 'is_elite: False']\n", + "Id: 72_65 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '1_1'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_65', 'origin': '71_52~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.673884941783694', 'NSGA-II_crowding_distance: 0.3868839319142754', 'NSGA-II_rank: 3', 'change: 0.18618673366743296', 'is_elite: False']\n", + "Id: 72_67 Identity: {'ancestor_count': 70, 'ancestor_ids': ['2_49', '71_79'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_67', 'origin': '2_49~CUW~71_79#MGNP'} Metrics: ['ELUC: -11.707273665874743', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.280096271113481', 'is_elite: False']\n", + "Id: 72_74 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_84', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_74', 'origin': '71_84~CUW~71_17#MGNP'} Metrics: ['ELUC: -12.431405001361554', 'NSGA-II_crowding_distance: 0.09868970355254852', 'NSGA-II_rank: 1', 'change: 0.15987760619085883', 'is_elite: False']\n", + "Id: 72_60 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_88', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_60', 'origin': '71_88~CUW~71_52#MGNP'} Metrics: ['ELUC: -12.946676936646272', 'NSGA-II_crowding_distance: 1.0954058476189599', 'NSGA-II_rank: 4', 'change: 0.26554467398663345', 'is_elite: False']\n", + "Id: 72_44 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_48', '71_84'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_44', 'origin': '70_48~CUW~71_84#MGNP'} Metrics: ['ELUC: -12.954179765525348', 'NSGA-II_crowding_distance: 0.10959534065299564', 'NSGA-II_rank: 1', 'change: 0.1626837033541779', 'is_elite: False']\n", + "Id: 72_71 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '71_79'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_71', 'origin': '71_52~CUW~71_79#MGNP'} Metrics: ['ELUC: -13.23243003269148', 'NSGA-II_crowding_distance: 0.8074233491561353', 'NSGA-II_rank: 3', 'change: 0.2159404971854311', 'is_elite: False']\n", + "Id: 71_17 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_74', '70_97'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_17', 'origin': '70_74~CUW~70_97#MGNP'} Metrics: ['ELUC: -13.339045104486868', 'NSGA-II_crowding_distance: 0.478186052095425', 'NSGA-II_rank: 2', 'change: 0.17651429020237525', 'is_elite: False']\n", + "Id: 72_34 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_31', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_34', 'origin': '71_31~CUW~71_17#MGNP'} Metrics: ['ELUC: -13.5273113291556', 'NSGA-II_crowding_distance: 0.24514908228708035', 'NSGA-II_rank: 1', 'change: 0.1739805453350563', 'is_elite: True']\n", + "Id: 71_37 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_73', '70_59'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_37', 'origin': '70_73~CUW~70_59#MGNP'} Metrics: ['ELUC: -13.59281964351472', 'NSGA-II_crowding_distance: 0.32465719445051844', 'NSGA-II_rank: 2', 'change: 0.21972672420567696', 'is_elite: False']\n", + "Id: 72_63 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_63', 'origin': '71_52~CUW~71_52#MGNP'} Metrics: ['ELUC: -14.082129004792241', 'NSGA-II_crowding_distance: 0.25520802994345854', 'NSGA-II_rank: 1', 'change: 0.216689080019543', 'is_elite: True']\n", + "Id: 72_40 Identity: {'ancestor_count': 70, 'ancestor_ids': ['68_68', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_40', 'origin': '68_68~CUW~71_52#MGNP'} Metrics: ['ELUC: -14.578909924737777', 'NSGA-II_crowding_distance: 0.39356210409808995', 'NSGA-II_rank: 2', 'change: 0.2307477144182364', 'is_elite: False']\n", + "Id: 71_52 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '70_74'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_52', 'origin': '70_59~CUW~70_74#MGNP'} Metrics: ['ELUC: -14.681517273972478', 'NSGA-II_crowding_distance: 0.10138274013553125', 'NSGA-II_rank: 1', 'change: 0.23054170342647154', 'is_elite: False']\n", + "Id: 72_53 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_53', 'origin': '71_52~CUW~71_17#MGNP'} Metrics: ['ELUC: -14.770837547627112', 'NSGA-II_crowding_distance: 0.08397130615589965', 'NSGA-II_rank: 1', 'change: 0.23525183408830136', 'is_elite: False']\n", + "Id: 72_17 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_17', 'origin': '71_52~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.776386940517254', 'NSGA-II_crowding_distance: 0.42540567217503844', 'NSGA-II_rank: 2', 'change: 0.29040187696959324', 'is_elite: False']\n", + "Id: 72_22 Identity: {'ancestor_count': 70, 'ancestor_ids': ['2_49', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_22', 'origin': '2_49~CUW~71_17#MGNP'} Metrics: ['ELUC: -15.352159460304025', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.31207805138170036', 'is_elite: False']\n", + "Id: 72_55 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_84', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_55', 'origin': '71_84~CUW~71_52#MGNP'} Metrics: ['ELUC: -15.557405191447609', 'NSGA-II_crowding_distance: 0.09678895889677963', 'NSGA-II_rank: 1', 'change: 0.24073278195012623', 'is_elite: False']\n", + "Id: 72_38 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '70_48'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_38', 'origin': '71_52~CUW~70_48#MGNP'} Metrics: ['ELUC: -15.734072622457647', 'NSGA-II_crowding_distance: 0.05402224274583246', 'NSGA-II_rank: 1', 'change: 0.2477851063624979', 'is_elite: False']\n", + "Id: 72_32 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_17', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_32', 'origin': '71_17~CUW~71_52#MGNP'} Metrics: ['ELUC: -15.861071253075375', 'NSGA-II_crowding_distance: 0.2144263196404532', 'NSGA-II_rank: 1', 'change: 0.2516985086199821', 'is_elite: True']\n", + "Id: 72_19 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_73', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_19', 'origin': '70_73~CUW~71_18#MGNP'} Metrics: ['ELUC: -16.33946740023389', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30682031904897217', 'is_elite: False']\n", + "Id: 72_91 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_91', 'origin': '71_18~CUW~71_88#MGNP'} Metrics: ['ELUC: -16.519052234258506', 'NSGA-II_crowding_distance: 0.1708933455582472', 'NSGA-II_rank: 2', 'change: 0.29694031833833223', 'is_elite: False']\n", + "Id: 72_72 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_72', 'origin': '70_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.779143430994182', 'NSGA-II_crowding_distance: 0.22350349760419022', 'NSGA-II_rank: 1', 'change: 0.29402996784010604', 'is_elite: True']\n", + "Id: 72_78 Identity: {'ancestor_count': 70, 'ancestor_ids': ['68_68', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_78', 'origin': '68_68~CUW~71_18#MGNP'} Metrics: ['ELUC: -16.833323482481948', 'NSGA-II_crowding_distance: 0.04443979884394545', 'NSGA-II_rank: 2', 'change: 0.29727117540173237', 'is_elite: False']\n", + "Id: 72_97 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_88', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_97', 'origin': '71_88~CUW~71_52#MGNP'} Metrics: ['ELUC: -17.060193779964496', 'NSGA-II_crowding_distance: 0.043503963587210315', 'NSGA-II_rank: 2', 'change: 0.29863019695801923', 'is_elite: False']\n", + "Id: 72_86 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_31', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_86', 'origin': '71_31~CUW~71_18#MGNP'} Metrics: ['ELUC: -17.24777973522066', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30070519695566617', 'is_elite: False']\n", + "Id: 72_79 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '70_14'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_79', 'origin': '71_18~CUW~70_14#MGNP'} Metrics: ['ELUC: -17.268221535938753', 'NSGA-II_crowding_distance: 0.06192081666927804', 'NSGA-II_rank: 1', 'change: 0.2945071974507894', 'is_elite: False']\n", + "Id: 71_18 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_74', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_18', 'origin': '70_74~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.44664783700847', 'NSGA-II_crowding_distance: 0.03499043362377004', 'NSGA-II_rank: 1', 'change: 0.30117800411652845', 'is_elite: False']\n", + "Id: 72_59 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_59', 'origin': '71_18~CUW~71_18#MGNP'} Metrics: ['ELUC: -17.4882918356753', 'NSGA-II_crowding_distance: 0.014748237244084788', 'NSGA-II_rank: 1', 'change: 0.3012129022552445', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 71_88 Identity: {'ancestor_count': 3, 'ancestor_ids': ['70_90', '2_49'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_88', 'origin': '70_90~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 72_52 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_18', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_52', 'origin': '71_18~CUW~71_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 72_57 Identity: {'ancestor_count': 70, 'ancestor_ids': ['2_49', '71_18'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_57', 'origin': '2_49~CUW~71_18#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 72_69 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_69', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 72_76 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_31', '71_88'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_76', 'origin': '71_31~CUW~71_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 72_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 72.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 73...:\n", + "PopulationResponse:\n", + " Generation: 73\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/73/20240220-042804\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 73 and asking ESP for generation 74...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 73 data persisted.\n", + "Evaluated candidates:\n", + "Id: 73_77 Identity: {'ancestor_count': 69, 'ancestor_ids': ['2_49', '70_14'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_77', 'origin': '2_49~CUW~70_14#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 73_92 Identity: {'ancestor_count': 3, 'ancestor_ids': ['72_100', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_92', 'origin': '72_100~CUW~1_1#MGNP'} Metrics: ['ELUC: 19.09901484211506', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2950384290280268', 'is_elite: False']\n", + "Id: 73_45 Identity: {'ancestor_count': 70, 'ancestor_ids': ['2_49', '72_13'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_45', 'origin': '2_49~CUW~72_13#MGNP'} Metrics: ['ELUC: 18.354585119378417', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.29233552270327107', 'is_elite: False']\n", + "Id: 73_39 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_50', '2_49'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_39', 'origin': '71_50~CUW~2_49#MGNP'} Metrics: ['ELUC: 7.516744166186763', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24981296345715084', 'is_elite: False']\n", + "Id: 73_71 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '72_100'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_71', 'origin': '1_1~CUW~72_100#MGNP'} Metrics: ['ELUC: 7.130554040543462', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2665112964666347', 'is_elite: False']\n", + "Id: 73_56 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_39', '72_100'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_56', 'origin': '72_39~CUW~72_100#MGNP'} Metrics: ['ELUC: 6.291662874236994', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2677116232856469', 'is_elite: False']\n", + "Id: 73_24 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_100', '72_70'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_24', 'origin': '72_100~CUW~72_70#MGNP'} Metrics: ['ELUC: 5.863272515725273', 'NSGA-II_crowding_distance: 0.9144624924678862', 'NSGA-II_rank: 7', 'change: 0.26174854091939215', 'is_elite: False']\n", + "Id: 73_65 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '72_72'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_65', 'origin': '71_52~CUW~72_72#MGNP'} Metrics: ['ELUC: 2.393169841434071', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.23637308196908682', 'is_elite: False']\n", + "Id: 73_95 Identity: {'ancestor_count': 71, 'ancestor_ids': ['2_49', '72_98'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_95', 'origin': '2_49~CUW~72_98#MGNP'} Metrics: ['ELUC: 2.1708261399989843', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2948664224644996', 'is_elite: False']\n", + "Id: 73_72 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_72', 'origin': '1_1~CUW~72_34#MGNP'} Metrics: ['ELUC: 1.703305706182047', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08446392534555469', 'is_elite: False']\n", + "Id: 73_89 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_89', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.6607463132232692', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.034920510501031544', 'is_elite: False']\n", + "Id: 73_67 Identity: {'ancestor_count': 71, 'ancestor_ids': ['2_49', '72_39'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_67', 'origin': '2_49~CUW~72_39#MGNP'} Metrics: ['ELUC: 0.5434701259463471', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26839117372326454', 'is_elite: False']\n", + "Id: 73_21 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_39', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_21', 'origin': '72_39~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.5141955810990023', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08666442355453302', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 71_50 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_50', 'origin': '70_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6682910644908597', 'NSGA-II_crowding_distance: 0.2827511208931386', 'NSGA-II_rank: 1', 'change: 0.049392437516290626', 'is_elite: True']\n", + "Id: 73_11 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_11', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9495909127385941', 'NSGA-II_crowding_distance: 1.2642794231525365', 'NSGA-II_rank: 6', 'change: 0.24369734706032528', 'is_elite: False']\n", + "Id: 73_58 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_58', 'origin': '70_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2547793172532231', 'NSGA-II_crowding_distance: 0.19244540752694705', 'NSGA-II_rank: 2', 'change: 0.05345062185130576', 'is_elite: False']\n", + "Id: 73_28 Identity: {'ancestor_count': 70, 'ancestor_ids': ['1_1', '71_50'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_28', 'origin': '1_1~CUW~71_50#MGNP'} Metrics: ['ELUC: -1.5470046613749966', 'NSGA-II_crowding_distance: 0.06714885199589712', 'NSGA-II_rank: 2', 'change: 0.053859381188415545', 'is_elite: False']\n", + "Id: 73_97 Identity: {'ancestor_count': 69, 'ancestor_ids': ['1_1', '70_14'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_97', 'origin': '1_1~CUW~70_14#MGNP'} Metrics: ['ELUC: -2.080050089235647', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06154232822652141', 'is_elite: False']\n", + "Id: 73_30 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_50', '72_13'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_30', 'origin': '71_50~CUW~72_13#MGNP'} Metrics: ['ELUC: -2.16715172531464', 'NSGA-II_crowding_distance: 0.1893339081120073', 'NSGA-II_rank: 2', 'change: 0.057955374775828884', 'is_elite: False']\n", + "Id: 73_49 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '72_70'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_49', 'origin': '1_1~CUW~72_70#MGNP'} Metrics: ['ELUC: -2.2159625523484894', 'NSGA-II_crowding_distance: 0.10935655950549883', 'NSGA-II_rank: 1', 'change: 0.05165917676737064', 'is_elite: False']\n", + "Id: 73_99 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_13', '72_39'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_99', 'origin': '72_13~CUW~72_39#MGNP'} Metrics: ['ELUC: -2.2611602919596123', 'NSGA-II_crowding_distance: 0.07056796003285318', 'NSGA-II_rank: 1', 'change: 0.054990516132000074', 'is_elite: False']\n", + "Id: 73_84 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '72_98'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_84', 'origin': '1_1~CUW~72_98#MGNP'} Metrics: ['ELUC: -2.558691786009908', 'NSGA-II_crowding_distance: 0.32717288023596863', 'NSGA-II_rank: 4', 'change: 0.08499216083377663', 'is_elite: False']\n", + "Id: 73_23 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_23', 'origin': '72_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.59218531084212', 'NSGA-II_crowding_distance: 0.2591529552900974', 'NSGA-II_rank: 4', 'change: 0.09006346974892603', 'is_elite: False']\n", + "Id: 73_52 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '2_49'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_52', 'origin': '68_68~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.6371276913304564', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2672952984954359', 'is_elite: False']\n", + "Id: 73_98 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_34', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_98', 'origin': '72_34~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.72449356387945', 'NSGA-II_crowding_distance: 0.8495005269344504', 'NSGA-II_rank: 5', 'change: 0.11548690314012325', 'is_elite: False']\n", + "Id: 73_91 Identity: {'ancestor_count': 71, 'ancestor_ids': ['2_49', '72_39'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_91', 'origin': '2_49~CUW~72_39#MGNP'} Metrics: ['ELUC: -2.8402939759544807', 'NSGA-II_crowding_distance: 0.8060726131782001', 'NSGA-II_rank: 7', 'change: 0.26539296821698993', 'is_elite: False']\n", + "Id: 73_93 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_70', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_93', 'origin': '72_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.2286045650259187', 'NSGA-II_crowding_distance: 0.11826315106551666', 'NSGA-II_rank: 1', 'change: 0.055530236371086464', 'is_elite: False']\n", + "Id: 73_70 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_70', 'origin': '1_1~CUW~72_63#MGNP'} Metrics: ['ELUC: -3.25257706445774', 'NSGA-II_crowding_distance: 0.2433964056185344', 'NSGA-II_rank: 3', 'change: 0.08001264421533041', 'is_elite: False']\n", + "Id: 73_15 Identity: {'ancestor_count': 71, 'ancestor_ids': ['68_68', '72_39'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_15', 'origin': '68_68~CUW~72_39#MGNP'} Metrics: ['ELUC: -3.639663989958454', 'NSGA-II_crowding_distance: 0.19183306194365035', 'NSGA-II_rank: 2', 'change: 0.0736678699802207', 'is_elite: False']\n", + "Id: 73_42 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '72_13'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_42', 'origin': '72_63~CUW~72_13#MGNP'} Metrics: ['ELUC: -3.7950079860945665', 'NSGA-II_crowding_distance: 0.13342978290566013', 'NSGA-II_rank: 3', 'change: 0.09332906193343334', 'is_elite: False']\n", + "Id: 73_88 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_98', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_88', 'origin': '72_98~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.8849513473529074', 'NSGA-II_crowding_distance: 0.23052429062195615', 'NSGA-II_rank: 3', 'change: 0.10255061967352119', 'is_elite: False']\n", + "Id: 73_86 Identity: {'ancestor_count': 71, 'ancestor_ids': ['70_14', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_86', 'origin': '70_14~CUW~72_63#MGNP'} Metrics: ['ELUC: -3.9201386150604467', 'NSGA-II_crowding_distance: 0.12820604766151172', 'NSGA-II_rank: 1', 'change: 0.06212423145466598', 'is_elite: False']\n", + "Id: 73_44 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_70', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_44', 'origin': '72_70~CUW~72_35#MGNP'} Metrics: ['ELUC: -4.103088143413007', 'NSGA-II_crowding_distance: 0.4954370669039465', 'NSGA-II_rank: 4', 'change: 0.112718241976302', 'is_elite: False']\n", + "Id: 73_80 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_14', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_80', 'origin': '70_14~CUW~72_35#MGNP'} Metrics: ['ELUC: -4.129878691022211', 'NSGA-II_crowding_distance: 0.18905051974704623', 'NSGA-II_rank: 2', 'change: 0.08035865316870854', 'is_elite: False']\n", + "Id: 72_39 Identity: {'ancestor_count': 70, 'ancestor_ids': ['70_14', '71_50'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_39', 'origin': '70_14~CUW~71_50#MGNP'} Metrics: ['ELUC: -4.420639659187494', 'NSGA-II_crowding_distance: 0.1103639513962058', 'NSGA-II_rank: 1', 'change: 0.07355486094629528', 'is_elite: False']\n", + "Id: 73_74 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '72_39'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_74', 'origin': '1_1~CUW~72_39#MGNP'} Metrics: ['ELUC: -5.116947354410713', 'NSGA-II_crowding_distance: 0.10577280655537952', 'NSGA-II_rank: 1', 'change: 0.07474416189667768', 'is_elite: False']\n", + "Id: 73_60 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '72_39'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_60', 'origin': '72_63~CUW~72_39#MGNP'} Metrics: ['ELUC: -5.198971909290923', 'NSGA-II_crowding_distance: 0.2719220147789791', 'NSGA-II_rank: 2', 'change: 0.10129903933165872', 'is_elite: False']\n", + "Id: 73_94 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_39', '72_100'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_94', 'origin': '72_39~CUW~72_100#MGNP'} Metrics: ['ELUC: -5.220916750204419', 'NSGA-II_crowding_distance: 0.2624046265696273', 'NSGA-II_rank: 7', 'change: 0.2690881350372052', 'is_elite: False']\n", + "Id: 73_22 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_72', '72_32'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_22', 'origin': '72_72~CUW~72_32#MGNP'} Metrics: ['ELUC: -5.481895076825764', 'NSGA-II_crowding_distance: 0.8732350338457534', 'NSGA-II_rank: 7', 'change: 0.2709441623269833', 'is_elite: False']\n", + "Id: 73_82 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_70', '70_14'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_82', 'origin': '72_70~CUW~70_14#MGNP'} Metrics: ['ELUC: -5.59560579130877', 'NSGA-II_crowding_distance: 0.14035034900338317', 'NSGA-II_rank: 1', 'change: 0.0851755718602119', 'is_elite: False']\n", + "Id: 73_63 Identity: {'ancestor_count': 71, 'ancestor_ids': ['70_14', '72_94'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_63', 'origin': '70_14~CUW~72_94#MGNP'} Metrics: ['ELUC: -6.078943160148818', 'NSGA-II_crowding_distance: 0.2118827516929784', 'NSGA-II_rank: 3', 'change: 0.11247642409449342', 'is_elite: False']\n", + "Id: 73_43 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_98', '72_100'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_43', 'origin': '72_98~CUW~72_100#MGNP'} Metrics: ['ELUC: -6.128440001216131', 'NSGA-II_crowding_distance: 1.0644678364049833', 'NSGA-II_rank: 6', 'change: 0.26240903326493586', 'is_elite: False']\n", + "Id: 73_17 Identity: {'ancestor_count': 71, 'ancestor_ids': ['68_68', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_17', 'origin': '68_68~CUW~72_34#MGNP'} Metrics: ['ELUC: -6.310352462436421', 'NSGA-II_crowding_distance: 0.029334999896354044', 'NSGA-II_rank: 3', 'change: 0.1147315616940599', 'is_elite: False']\n", + "Id: 73_87 Identity: {'ancestor_count': 69, 'ancestor_ids': ['68_68', '70_14'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_87', 'origin': '68_68~CUW~70_14#MGNP'} Metrics: ['ELUC: -6.317162134536984', 'NSGA-II_crowding_distance: 0.11284603483921998', 'NSGA-II_rank: 3', 'change: 0.11578377029790053', 'is_elite: False']\n", + "Id: 73_13 Identity: {'ancestor_count': 71, 'ancestor_ids': ['2_49', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_13', 'origin': '2_49~CUW~72_63#MGNP'} Metrics: ['ELUC: -6.690557616002181', 'NSGA-II_crowding_distance: 0.7357205768474635', 'NSGA-II_rank: 6', 'change: 0.2701675395793683', 'is_elite: False']\n", + "Id: 73_54 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '70_14'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_54', 'origin': '70_14~CUW~70_14#MGNP'} Metrics: ['ELUC: -6.760375716366408', 'NSGA-II_crowding_distance: 0.18133013964352268', 'NSGA-II_rank: 1', 'change: 0.08873209248957434', 'is_elite: False']\n", + "Id: 73_32 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_34', '72_39'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_32', 'origin': '72_34~CUW~72_39#MGNP'} Metrics: ['ELUC: -6.943004166586237', 'NSGA-II_crowding_distance: 0.21680810123706634', 'NSGA-II_rank: 2', 'change: 0.1116564329784254', 'is_elite: False']\n", + "Id: 73_37 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_37', 'origin': '72_32~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.048577127100882', 'NSGA-II_crowding_distance: 1.1966842548271948', 'NSGA-II_rank: 5', 'change: 0.1363908675133377', 'is_elite: False']\n", + "Id: 73_18 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_15', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_18', 'origin': '72_15~CUW~72_35#MGNP'} Metrics: ['ELUC: -7.291863403814085', 'NSGA-II_crowding_distance: 0.41049646943129736', 'NSGA-II_rank: 4', 'change: 0.12116818175464322', 'is_elite: False']\n", + "Id: 73_38 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_98', '72_94'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_38', 'origin': '72_98~CUW~72_94#MGNP'} Metrics: ['ELUC: -7.523003766739635', 'NSGA-II_crowding_distance: 0.17948914920582448', 'NSGA-II_rank: 1', 'change: 0.1065719068688127', 'is_elite: False']\n", + "Id: 73_31 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_70', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_31', 'origin': '72_70~CUW~72_35#MGNP'} Metrics: ['ELUC: -7.768779209268703', 'NSGA-II_crowding_distance: 0.28341573809018594', 'NSGA-II_rank: 3', 'change: 0.11844997870593994', 'is_elite: False']\n", + "Id: 73_14 Identity: {'ancestor_count': 71, 'ancestor_ids': ['71_50', '72_32'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_14', 'origin': '71_50~CUW~72_32#MGNP'} Metrics: ['ELUC: -8.207961141371145', 'NSGA-II_crowding_distance: 0.24794137396618882', 'NSGA-II_rank: 4', 'change: 0.13584611329653784', 'is_elite: False']\n", + "Id: 73_78 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '68_68'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_78', 'origin': '68_68~CUW~68_68#MGNP'} Metrics: ['ELUC: -8.297449376625273', 'NSGA-II_crowding_distance: 0.23831920302237802', 'NSGA-II_rank: 2', 'change: 0.11358333558867678', 'is_elite: False']\n", + "Id: 68_68 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_68', 'origin': '67_100~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.761487407874672', 'NSGA-II_crowding_distance: 0.2485255957497341', 'NSGA-II_rank: 1', 'change: 0.10832817250116257', 'is_elite: True']\n", + "Id: 73_68 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_68', 'origin': '72_63~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.844570437884114', 'NSGA-II_crowding_distance: 0.450602793862778', 'NSGA-II_rank: 4', 'change: 0.14675307421446152', 'is_elite: False']\n", + "Id: 73_33 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_50', '2_49'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_33', 'origin': '71_50~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.017897429289944', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.303895498728702', 'is_elite: False']\n", + "Id: 73_48 Identity: {'ancestor_count': 70, 'ancestor_ids': ['72_72', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_48', 'origin': '72_72~CUW~72_35#MGNP'} Metrics: ['ELUC: -9.187795970655877', 'NSGA-II_crowding_distance: 1.078005868008544', 'NSGA-II_rank: 5', 'change: 0.2541824879574908', 'is_elite: False']\n", + "Id: 73_64 Identity: {'ancestor_count': 71, 'ancestor_ids': ['68_68', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_64', 'origin': '68_68~CUW~72_63#MGNP'} Metrics: ['ELUC: -9.511595580694383', 'NSGA-II_crowding_distance: 0.23289974150468257', 'NSGA-II_rank: 3', 'change: 0.13290432060479856', 'is_elite: False']\n", + "Id: 73_79 Identity: {'ancestor_count': 71, 'ancestor_ids': ['70_14', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_79', 'origin': '70_14~CUW~72_34#MGNP'} Metrics: ['ELUC: -9.879968792393973', 'NSGA-II_crowding_distance: 0.3154978166281748', 'NSGA-II_rank: 3', 'change: 0.14105520502897542', 'is_elite: False']\n", + "Id: 73_90 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_98', '72_32'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_90', 'origin': '72_98~CUW~72_32#MGNP'} Metrics: ['ELUC: -10.045110522137854', 'NSGA-II_crowding_distance: 0.16500850077229373', 'NSGA-II_rank: 2', 'change: 0.12965860062791132', 'is_elite: False']\n", + "Id: 73_73 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_73', 'origin': '72_63~CUW~72_35#MGNP'} Metrics: ['ELUC: -10.124929832633596', 'NSGA-II_crowding_distance: 0.06756687542745868', 'NSGA-II_rank: 2', 'change: 0.130792298815757', 'is_elite: False']\n", + "Id: 73_85 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_98', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_85', 'origin': '72_98~CUW~72_34#MGNP'} Metrics: ['ELUC: -10.804970161266661', 'NSGA-II_crowding_distance: 0.2376565722876171', 'NSGA-II_rank: 2', 'change: 0.13653416452882283', 'is_elite: False']\n", + "Id: 73_27 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_98', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_27', 'origin': '72_98~CUW~72_35#MGNP'} Metrics: ['ELUC: -10.81389723024378', 'NSGA-II_crowding_distance: 0.3704790986684242', 'NSGA-II_rank: 1', 'change: 0.12487892986855983', 'is_elite: True']\n", + "Id: 73_66 Identity: {'ancestor_count': 71, 'ancestor_ids': ['2_49', '72_32'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_66', 'origin': '2_49~CUW~72_32#MGNP'} Metrics: ['ELUC: -10.838151050842479', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2783509039285468', 'is_elite: False']\n", + "Id: 73_76 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_94', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_76', 'origin': '72_94~CUW~72_63#MGNP'} Metrics: ['ELUC: -11.832270505024397', 'NSGA-II_crowding_distance: 0.929448678893896', 'NSGA-II_rank: 4', 'change: 0.17228470348471467', 'is_elite: False']\n", + "Id: 73_34 Identity: {'ancestor_count': 70, 'ancestor_ids': ['72_72', '2_49'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_34', 'origin': '72_72~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.846197993201125', 'NSGA-II_crowding_distance: 0.4026935405305403', 'NSGA-II_rank: 5', 'change: 0.27811841412309135', 'is_elite: False']\n", + "Id: 73_12 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_12', 'origin': '1_1~CUW~72_34#MGNP'} Metrics: ['ELUC: -11.927560335667557', 'NSGA-II_crowding_distance: 0.7121548862675351', 'NSGA-II_rank: 3', 'change: 0.17090144908819951', 'is_elite: False']\n", + "Id: 73_62 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_100', '72_32'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_62', 'origin': '72_100~CUW~72_32#MGNP'} Metrics: ['ELUC: -11.961576406239873', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2910445162208318', 'is_elite: False']\n", + "Id: 73_35 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_34', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_35', 'origin': '72_34~CUW~72_63#MGNP'} Metrics: ['ELUC: -12.12957696200975', 'NSGA-II_crowding_distance: 0.4796279124968589', 'NSGA-II_rank: 2', 'change: 0.16486959894063596', 'is_elite: False']\n", + "Id: 73_25 Identity: {'ancestor_count': 71, 'ancestor_ids': ['71_50', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_25', 'origin': '71_50~CUW~72_34#MGNP'} Metrics: ['ELUC: -12.3276101914385', 'NSGA-II_crowding_distance: 0.26101214721901694', 'NSGA-II_rank: 1', 'change: 0.15835267658330512', 'is_elite: True']\n", + "Id: 73_19 Identity: {'ancestor_count': 70, 'ancestor_ids': ['72_72', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_19', 'origin': '72_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.791183593983424', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.266152333141958', 'is_elite: False']\n", + "Id: 73_81 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_34', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_81', 'origin': '72_34~CUW~72_34#MGNP'} Metrics: ['ELUC: -13.125767196431175', 'NSGA-II_crowding_distance: 0.10226221266435145', 'NSGA-II_rank: 1', 'change: 0.1635259920091304', 'is_elite: False']\n", + "Id: 73_16 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '72_72'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_16', 'origin': '72_63~CUW~72_72#MGNP'} Metrics: ['ELUC: -13.287783154971942', 'NSGA-II_crowding_distance: 0.7446881288724075', 'NSGA-II_rank: 3', 'change: 0.26080490930471806', 'is_elite: False']\n", + "Id: 73_26 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_34', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_26', 'origin': '72_34~CUW~72_34#MGNP'} Metrics: ['ELUC: -13.325600427516981', 'NSGA-II_crowding_distance: 0.05787590751389691', 'NSGA-II_rank: 1', 'change: 0.1719292400100514', 'is_elite: False']\n", + "Id: 72_34 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_31', '71_17'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_34', 'origin': '71_31~CUW~71_17#MGNP'} Metrics: ['ELUC: -13.5273113291556', 'NSGA-II_crowding_distance: 0.1929704292860114', 'NSGA-II_rank: 1', 'change: 0.1739805453350563', 'is_elite: False']\n", + "Id: 72_63 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_52', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_63', 'origin': '71_52~CUW~71_52#MGNP'} Metrics: ['ELUC: -14.082129004792241', 'NSGA-II_crowding_distance: 0.49152950988167', 'NSGA-II_rank: 2', 'change: 0.216689080019543', 'is_elite: False']\n", + "Id: 73_40 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_40', 'origin': '72_63~CUW~72_63#MGNP'} Metrics: ['ELUC: -14.171832324180382', 'NSGA-II_crowding_distance: 0.2564159420529762', 'NSGA-II_rank: 1', 'change: 0.21514649957411305', 'is_elite: True']\n", + "Id: 73_55 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_39', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_55', 'origin': '72_39~CUW~72_63#MGNP'} Metrics: ['ELUC: -14.76505769426639', 'NSGA-II_crowding_distance: 0.20379350426965548', 'NSGA-II_rank: 1', 'change: 0.22948441080401413', 'is_elite: False']\n", + "Id: 73_50 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_39', '72_32'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_50', 'origin': '72_39~CUW~72_32#MGNP'} Metrics: ['ELUC: -15.334271133999838', 'NSGA-II_crowding_distance: 0.3784964377242567', 'NSGA-II_rank: 2', 'change: 0.2492909875687094', 'is_elite: False']\n", + "Id: 73_36 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_34', '2_49'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_36', 'origin': '72_34~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.613388440231349', 'NSGA-II_crowding_distance: 0.443549343327875', 'NSGA-II_rank: 3', 'change: 0.2940894585856532', 'is_elite: False']\n", + "Id: 73_53 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '2_49'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_53', 'origin': '72_63~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.799718340109694', 'NSGA-II_crowding_distance: 0.24649581154565753', 'NSGA-II_rank: 2', 'change: 0.2928061366148931', 'is_elite: False']\n", + "Id: 73_96 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_34', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_96', 'origin': '72_34~CUW~72_63#MGNP'} Metrics: ['ELUC: -15.806646362998057', 'NSGA-II_crowding_distance: 0.13678563679221448', 'NSGA-II_rank: 1', 'change: 0.24821064154626704', 'is_elite: False']\n", + "Id: 72_32 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_17', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_32', 'origin': '71_17~CUW~71_52#MGNP'} Metrics: ['ELUC: -15.861071253075375', 'NSGA-II_crowding_distance: 0.21149032859512523', 'NSGA-II_rank: 1', 'change: 0.2516985086199821', 'is_elite: True']\n", + "Id: 72_72 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_59', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_72', 'origin': '70_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.779143430994182', 'NSGA-II_crowding_distance: 0.08177529144817755', 'NSGA-II_rank: 2', 'change: 0.29402996784010604', 'is_elite: False']\n", + "Id: 73_59 Identity: {'ancestor_count': 3, 'ancestor_ids': ['72_100', '72_100'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_59', 'origin': '72_100~CUW~72_100#MGNP'} Metrics: ['ELUC: -16.887536281582715', 'NSGA-II_crowding_distance: 0.029704250277167756', 'NSGA-II_rank: 2', 'change: 0.298637012576518', 'is_elite: False']\n", + "Id: 73_75 Identity: {'ancestor_count': 71, 'ancestor_ids': ['2_49', '72_32'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_75', 'origin': '2_49~CUW~72_32#MGNP'} Metrics: ['ELUC: -16.929483590604494', 'NSGA-II_crowding_distance: 0.0485181123283743', 'NSGA-II_rank: 2', 'change: 0.29977339759860494', 'is_elite: False']\n", + "Id: 73_69 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_15', '72_72'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_69', 'origin': '72_15~CUW~72_72#MGNP'} Metrics: ['ELUC: -16.938432685539972', 'NSGA-II_crowding_distance: 0.21941100993304216', 'NSGA-II_rank: 1', 'change: 0.2921078797307474', 'is_elite: True']\n", + "Id: 73_57 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_57', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.987703792169068', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3091842345470329', 'is_elite: False']\n", + "Id: 73_83 Identity: {'ancestor_count': 70, 'ancestor_ids': ['72_72', '72_72'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_83', 'origin': '72_72~CUW~72_72#MGNP'} Metrics: ['ELUC: -17.16142935934743', 'NSGA-II_crowding_distance: 0.07399190579271153', 'NSGA-II_rank: 1', 'change: 0.2950983864800425', 'is_elite: False']\n", + "Id: 73_41 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_50', '2_49'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_41', 'origin': '71_50~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.45647319112601', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3032291168869581', 'is_elite: False']\n", + "Id: 73_29 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '72_100'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_29', 'origin': '72_32~CUW~72_100#MGNP'} Metrics: ['ELUC: -17.596366609198288', 'NSGA-II_crowding_distance: 0.05134568595271344', 'NSGA-II_rank: 1', 'change: 0.30302007402470577', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 72_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 73_20 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '72_100'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_20', 'origin': '72_63~CUW~72_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 73_46 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '72_100'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_46', 'origin': '2_49~CUW~72_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 73_47 Identity: {'ancestor_count': 70, 'ancestor_ids': ['2_49', '72_72'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_47', 'origin': '2_49~CUW~72_72#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 73_51 Identity: {'ancestor_count': 70, 'ancestor_ids': ['72_100', '72_72'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_51', 'origin': '72_100~CUW~72_72#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 73_61 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_15', '2_49'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_61', 'origin': '72_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 73_100 Identity: {'ancestor_count': 70, 'ancestor_ids': ['72_100', '72_13'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_100', 'origin': '72_100~CUW~72_13#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 73.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 74...:\n", + "PopulationResponse:\n", + " Generation: 74\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/74/20240220-043521\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 74 and asking ESP for generation 75...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 74 data persisted.\n", + "Evaluated candidates:\n", + "Id: 74_31 Identity: {'ancestor_count': 71, 'ancestor_ids': ['73_100', '71_50'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_31', 'origin': '73_100~CUW~71_50#MGNP'} Metrics: ['ELUC: 22.8263695294807', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3042977131006889', 'is_elite: False']\n", + "Id: 74_95 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '73_54'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_95', 'origin': '73_69~CUW~73_54#MGNP'} Metrics: ['ELUC: 8.110592831014207', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.25854633415497896', 'is_elite: False']\n", + "Id: 74_83 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_83', 'origin': '73_69~CUW~1_1#MGNP'} Metrics: ['ELUC: 6.540045043527687', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.22663259206737782', 'is_elite: False']\n", + "Id: 74_60 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '73_96'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_60', 'origin': '1_1~CUW~73_96#MGNP'} Metrics: ['ELUC: 3.2218875872599253', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08379768151926711', 'is_elite: False']\n", + "Id: 74_71 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_25', '73_86'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_71', 'origin': '73_25~CUW~73_86#MGNP'} Metrics: ['ELUC: 1.2124065144880931', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.10279602756039607', 'is_elite: False']\n", + "Id: 74_85 Identity: {'ancestor_count': 72, 'ancestor_ids': ['68_68', '73_93'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_85', 'origin': '68_68~CUW~73_93#MGNP'} Metrics: ['ELUC: 0.4904218973259105', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07342681760916862', 'is_elite: False']\n", + "Id: 74_89 Identity: {'ancestor_count': 72, 'ancestor_ids': ['71_50', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_89', 'origin': '71_50~CUW~73_27#MGNP'} Metrics: ['ELUC: 0.2801622827273741', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.054322335024716964', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 74_73 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_73', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.6063359425685908', 'NSGA-II_crowding_distance: 1.6269694386651739', 'NSGA-II_rank: 7', 'change: 0.23757660713372786', 'is_elite: False']\n", + "Id: 74_52 Identity: {'ancestor_count': 71, 'ancestor_ids': ['71_50', '72_39'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_52', 'origin': '71_50~CUW~72_39#MGNP'} Metrics: ['ELUC: -0.6248238171403031', 'NSGA-II_crowding_distance: 0.313032713447143', 'NSGA-II_rank: 2', 'change: 0.05623290296616646', 'is_elite: False']\n", + "Id: 71_50 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_50', 'origin': '70_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6682910644908597', 'NSGA-II_crowding_distance: 0.26564925065203215', 'NSGA-II_rank: 1', 'change: 0.049392437516290626', 'is_elite: True']\n", + "Id: 74_39 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_39', 'origin': '68_68~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4118490188174992', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.09669352451426232', 'is_elite: False']\n", + "Id: 74_100 Identity: {'ancestor_count': 72, 'ancestor_ids': ['71_50', '73_25'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_100', 'origin': '71_50~CUW~73_25#MGNP'} Metrics: ['ELUC: -1.6175268009793229', 'NSGA-II_crowding_distance: 1.76932553643845', 'NSGA-II_rank: 6', 'change: 0.10435869882101519', 'is_elite: False']\n", + "Id: 74_37 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_37', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.789422768386175', 'NSGA-II_crowding_distance: 0.13147010644346327', 'NSGA-II_rank: 1', 'change: 0.053794871393013345', 'is_elite: False']\n", + "Id: 74_93 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_93', 'origin': '1_1~CUW~73_27#MGNP'} Metrics: ['ELUC: -2.3704471233021387', 'NSGA-II_crowding_distance: 0.28128154544128703', 'NSGA-II_rank: 3', 'change: 0.07522977792330462', 'is_elite: False']\n", + "Id: 74_77 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_25', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_77', 'origin': '73_25~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.4838664449851167', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.0866042764088032', 'is_elite: False']\n", + "Id: 74_18 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_100', '73_25'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_18', 'origin': '73_100~CUW~73_25#MGNP'} Metrics: ['ELUC: -2.523504624531445', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3134541760805207', 'is_elite: False']\n", + "Id: 74_80 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_93', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_80', 'origin': '73_93~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.5694839964179295', 'NSGA-II_crowding_distance: 0.10834838871184127', 'NSGA-II_rank: 1', 'change: 0.056356357443917766', 'is_elite: False']\n", + "Id: 74_19 Identity: {'ancestor_count': 72, 'ancestor_ids': ['2_49', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_19', 'origin': '2_49~CUW~73_27#MGNP'} Metrics: ['ELUC: -2.733401443992317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2685351180845103', 'is_elite: False']\n", + "Id: 74_61 Identity: {'ancestor_count': 72, 'ancestor_ids': ['71_50', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_61', 'origin': '71_50~CUW~73_27#MGNP'} Metrics: ['ELUC: -2.8155037239773155', 'NSGA-II_crowding_distance: 0.5007780345658508', 'NSGA-II_rank: 4', 'change: 0.08612344062026503', 'is_elite: False']\n", + "Id: 74_40 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_93', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_40', 'origin': '73_93~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.146933920746018', 'NSGA-II_crowding_distance: 0.1501126228738479', 'NSGA-II_rank: 1', 'change: 0.06308623337600144', 'is_elite: False']\n", + "Id: 74_14 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '68_68'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_14', 'origin': '73_40~CUW~68_68#MGNP'} Metrics: ['ELUC: -3.6874525639662017', 'NSGA-II_crowding_distance: 1.123704357005048', 'NSGA-II_rank: 5', 'change: 0.12929164519521336', 'is_elite: False']\n", + "Id: 74_81 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_82', '72_34'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_81', 'origin': '73_82~CUW~72_34#MGNP'} Metrics: ['ELUC: -3.7623838027096066', 'NSGA-II_crowding_distance: 0.25642162707953897', 'NSGA-II_rank: 3', 'change: 0.08230391657623098', 'is_elite: False']\n", + "Id: 74_84 Identity: {'ancestor_count': 70, 'ancestor_ids': ['68_68', '71_50'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_84', 'origin': '68_68~CUW~71_50#MGNP'} Metrics: ['ELUC: -3.9507045402915058', 'NSGA-II_crowding_distance: 0.5050692696229351', 'NSGA-II_rank: 4', 'change: 0.10602538539855601', 'is_elite: False']\n", + "Id: 74_32 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '71_50'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_32', 'origin': '73_27~CUW~71_50#MGNP'} Metrics: ['ELUC: -4.136949165043886', 'NSGA-II_crowding_distance: 0.3928504144375494', 'NSGA-II_rank: 2', 'change: 0.0704177600382329', 'is_elite: False']\n", + "Id: 74_94 Identity: {'ancestor_count': 70, 'ancestor_ids': ['73_54', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_94', 'origin': '73_54~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.660541971518446', 'NSGA-II_crowding_distance: 0.11789466429812549', 'NSGA-II_rank: 1', 'change: 0.06566072052124665', 'is_elite: False']\n", + "Id: 74_54 Identity: {'ancestor_count': 70, 'ancestor_ids': ['73_54', '71_50'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_54', 'origin': '73_54~CUW~71_50#MGNP'} Metrics: ['ELUC: -4.7226552360001905', 'NSGA-II_crowding_distance: 0.03788844380813497', 'NSGA-II_rank: 1', 'change: 0.07152289753952659', 'is_elite: False']\n", + "Id: 74_24 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_49', '73_82'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_24', 'origin': '73_49~CUW~73_82#MGNP'} Metrics: ['ELUC: -4.739418186916195', 'NSGA-II_crowding_distance: 0.12246466473490157', 'NSGA-II_rank: 1', 'change: 0.07562723410344686', 'is_elite: False']\n", + "Id: 74_63 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_38', '73_54'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_63', 'origin': '73_38~CUW~73_54#MGNP'} Metrics: ['ELUC: -5.087169410939127', 'NSGA-II_crowding_distance: 0.16683422193177905', 'NSGA-II_rank: 2', 'change: 0.09149948197131721', 'is_elite: False']\n", + "Id: 74_16 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_38', '71_50'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_16', 'origin': '73_38~CUW~71_50#MGNP'} Metrics: ['ELUC: -5.190652932068957', 'NSGA-II_crowding_distance: 0.3497322908963683', 'NSGA-II_rank: 3', 'change: 0.09733606711488038', 'is_elite: False']\n", + "Id: 74_30 Identity: {'ancestor_count': 72, 'ancestor_ids': ['68_68', '73_86'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_30', 'origin': '68_68~CUW~73_86#MGNP'} Metrics: ['ELUC: -5.450400319624645', 'NSGA-II_crowding_distance: 0.09122117648020912', 'NSGA-II_rank: 2', 'change: 0.09350068802148351', 'is_elite: False']\n", + "Id: 74_82 Identity: {'ancestor_count': 72, 'ancestor_ids': ['71_50', '73_69'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_82', 'origin': '71_50~CUW~73_69#MGNP'} Metrics: ['ELUC: -5.836015557143781', 'NSGA-II_crowding_distance: 1.625916868812015', 'NSGA-II_rank: 8', 'change: 0.26088014801871157', 'is_elite: False']\n", + "Id: 74_49 Identity: {'ancestor_count': 70, 'ancestor_ids': ['1_1', '73_54'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_49', 'origin': '1_1~CUW~73_54#MGNP'} Metrics: ['ELUC: -5.948967875889006', 'NSGA-II_crowding_distance: 0.12352654213099126', 'NSGA-II_rank: 2', 'change: 0.10211882073429615', 'is_elite: False']\n", + "Id: 74_48 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '72_34'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_48', 'origin': '73_69~CUW~72_34#MGNP'} Metrics: ['ELUC: -6.052465531334882', 'NSGA-II_crowding_distance: 0.3120802344348245', 'NSGA-II_rank: 8', 'change: 0.2626692710207942', 'is_elite: False']\n", + "Id: 74_70 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_54', '73_40'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_70', 'origin': '73_54~CUW~73_40#MGNP'} Metrics: ['ELUC: -6.158897564798026', 'NSGA-II_crowding_distance: 0.13290821670815817', 'NSGA-II_rank: 1', 'change: 0.08369014937116148', 'is_elite: False']\n", + "Id: 74_58 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_58', 'origin': '73_40~CUW~73_27#MGNP'} Metrics: ['ELUC: -6.1929585078767815', 'NSGA-II_crowding_distance: 0.0932053359909997', 'NSGA-II_rank: 1', 'change: 0.09061705684510865', 'is_elite: False']\n", + "Id: 74_55 Identity: {'ancestor_count': 67, 'ancestor_ids': ['68_68', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_55', 'origin': '68_68~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.636424096063544', 'NSGA-II_crowding_distance: 0.1479962434700735', 'NSGA-II_rank: 2', 'change: 0.1076156309405403', 'is_elite: False']\n", + "Id: 74_21 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_38', '73_69'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_21', 'origin': '73_38~CUW~73_69#MGNP'} Metrics: ['ELUC: -6.663215919647336', 'NSGA-II_crowding_distance: 1.1103179118329725', 'NSGA-II_rank: 5', 'change: 0.2249582146593985', 'is_elite: False']\n", + "Id: 74_36 Identity: {'ancestor_count': 71, 'ancestor_ids': ['73_54', '72_34'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_36', 'origin': '73_54~CUW~72_34#MGNP'} Metrics: ['ELUC: -6.782418636038156', 'NSGA-II_crowding_distance: 0.14260776094926378', 'NSGA-II_rank: 1', 'change: 0.10091919976341698', 'is_elite: False']\n", + "Id: 74_72 Identity: {'ancestor_count': 71, 'ancestor_ids': ['73_100', '71_50'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_72', 'origin': '73_100~CUW~71_50#MGNP'} Metrics: ['ELUC: -6.892079884724383', 'NSGA-II_crowding_distance: 0.3740831311879851', 'NSGA-II_rank: 8', 'change: 0.27251110328690453', 'is_elite: False']\n", + "Id: 74_59 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '68_68'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_59', 'origin': '73_40~CUW~68_68#MGNP'} Metrics: ['ELUC: -6.949569942135692', 'NSGA-II_crowding_distance: 0.6699168916912484', 'NSGA-II_rank: 4', 'change: 0.14444790082019937', 'is_elite: False']\n", + "Id: 74_42 Identity: {'ancestor_count': 72, 'ancestor_ids': ['71_50', '73_25'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_42', 'origin': '71_50~CUW~73_25#MGNP'} Metrics: ['ELUC: -6.976732754289595', 'NSGA-II_crowding_distance: 0.44554136563070784', 'NSGA-II_rank: 3', 'change: 0.12083733711463682', 'is_elite: False']\n", + "Id: 74_46 Identity: {'ancestor_count': 71, 'ancestor_ids': ['73_54', '73_100'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_46', 'origin': '73_54~CUW~73_100#MGNP'} Metrics: ['ELUC: -7.0540078524767065', 'NSGA-II_crowding_distance: 0.9729014258141429', 'NSGA-II_rank: 7', 'change: 0.24383178980315043', 'is_elite: False']\n", + "Id: 74_99 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_38', '2_49'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_99', 'origin': '73_38~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.603606998193064', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2756229366809586', 'is_elite: False']\n", + "Id: 74_15 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '68_68'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_15', 'origin': '73_40~CUW~68_68#MGNP'} Metrics: ['ELUC: -7.638960276841354', 'NSGA-II_crowding_distance: 0.2703989304016596', 'NSGA-II_rank: 2', 'change: 0.11528028487459668', 'is_elite: False']\n", + "Id: 74_34 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '73_38'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_34', 'origin': '73_27~CUW~73_38#MGNP'} Metrics: ['ELUC: -8.088932638341701', 'NSGA-II_crowding_distance: 0.1373908898234307', 'NSGA-II_rank: 1', 'change: 0.10099276933672971', 'is_elite: False']\n", + "Id: 74_56 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_100', '73_49'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_56', 'origin': '73_100~CUW~73_49#MGNP'} Metrics: ['ELUC: -8.665107928472285', 'NSGA-II_crowding_distance: 1.92745988677486', 'NSGA-II_rank: 6', 'change: 0.2406618971307736', 'is_elite: False']\n", + "Id: 68_68 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_68', 'origin': '67_100~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.761487407874672', 'NSGA-II_crowding_distance: 0.21432694403534883', 'NSGA-II_rank: 1', 'change: 0.10832817250116257', 'is_elite: True']\n", + "Id: 74_78 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '73_69'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_78', 'origin': '1_1~CUW~73_69#MGNP'} Metrics: ['ELUC: -8.907116276631251', 'NSGA-II_crowding_distance: 0.37303056133482604', 'NSGA-II_rank: 7', 'change: 0.2648906964069809', 'is_elite: False']\n", + "Id: 74_69 Identity: {'ancestor_count': 72, 'ancestor_ids': ['68_68', '73_69'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_69', 'origin': '68_68~CUW~73_69#MGNP'} Metrics: ['ELUC: -8.972668120527274', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2757719628403786', 'is_elite: False']\n", + "Id: 74_20 Identity: {'ancestor_count': 72, 'ancestor_ids': ['71_50', '73_69'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_20', 'origin': '71_50~CUW~73_69#MGNP'} Metrics: ['ELUC: -9.291950656482053', 'NSGA-II_crowding_distance: 0.42768727198048845', 'NSGA-II_rank: 5', 'change: 0.23624986547074717', 'is_elite: False']\n", + "Id: 74_92 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '72_39'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_92', 'origin': '73_40~CUW~72_39#MGNP'} Metrics: ['ELUC: -9.425597706849993', 'NSGA-II_crowding_distance: 0.43241645891789393', 'NSGA-II_rank: 3', 'change: 0.14456877205988491', 'is_elite: False']\n", + "Id: 74_13 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_100', '73_25'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_13', 'origin': '73_100~CUW~73_25#MGNP'} Metrics: ['ELUC: -9.744277058714854', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2568648434711581', 'is_elite: False']\n", + "Id: 74_67 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_67', 'origin': '73_27~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.744786764147157', 'NSGA-II_crowding_distance: 0.208517275414422', 'NSGA-II_rank: 2', 'change: 0.13137490087551465', 'is_elite: False']\n", + "Id: 74_62 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_25', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_62', 'origin': '73_25~CUW~73_27#MGNP'} Metrics: ['ELUC: -9.787271816971202', 'NSGA-II_crowding_distance: 0.2589911438501125', 'NSGA-II_rank: 2', 'change: 0.1370683169171711', 'is_elite: False']\n", + "Id: 74_22 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '72_32'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_22', 'origin': '73_69~CUW~72_32#MGNP'} Metrics: ['ELUC: -10.028444263524305', 'NSGA-II_crowding_distance: 0.179009659057829', 'NSGA-II_rank: 5', 'change: 0.2418260760491028', 'is_elite: False']\n", + "Id: 74_50 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_96', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_50', 'origin': '73_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.266827761388136', 'NSGA-II_crowding_distance: 0.37489342032614426', 'NSGA-II_rank: 4', 'change: 0.17374057966234555', 'is_elite: False']\n", + "Id: 74_57 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_57', 'origin': '73_27~CUW~73_27#MGNP'} Metrics: ['ELUC: -10.623446576838816', 'NSGA-II_crowding_distance: 0.1722004763248089', 'NSGA-II_rank: 1', 'change: 0.12193167043452074', 'is_elite: True']\n", + "Id: 74_11 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_25', '73_100'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_11', 'origin': '73_25~CUW~73_100#MGNP'} Metrics: ['ELUC: -10.67818497162054', 'NSGA-II_crowding_distance: 0.44860837101446344', 'NSGA-II_rank: 5', 'change: 0.24375953596975694', 'is_elite: False']\n", + "Id: 73_27 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_98', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_27', 'origin': '72_98~CUW~72_35#MGNP'} Metrics: ['ELUC: -10.81389723024378', 'NSGA-II_crowding_distance: 0.21898816402663623', 'NSGA-II_rank: 1', 'change: 0.12487892986855983', 'is_elite: True']\n", + "Id: 74_65 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '1_1'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_65', 'origin': '73_40~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.99003447129023', 'NSGA-II_crowding_distance: 0.27325563758679533', 'NSGA-II_rank: 4', 'change: 0.17648257774167692', 'is_elite: False']\n", + "Id: 74_76 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_38', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_76', 'origin': '73_38~CUW~73_27#MGNP'} Metrics: ['ELUC: -11.402341106278273', 'NSGA-II_crowding_distance: 0.4397527020478579', 'NSGA-II_rank: 3', 'change: 0.162495762040127', 'is_elite: False']\n", + "Id: 74_91 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_25', '72_32'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_91', 'origin': '73_25~CUW~72_32#MGNP'} Metrics: ['ELUC: -12.134076493734803', 'NSGA-II_crowding_distance: 0.3253940875123704', 'NSGA-II_rank: 2', 'change: 0.16232613214419572', 'is_elite: False']\n", + "Id: 74_68 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '68_68'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_68', 'origin': '72_32~CUW~68_68#MGNP'} Metrics: ['ELUC: -12.205098673217506', 'NSGA-II_crowding_distance: 0.4895136243019233', 'NSGA-II_rank: 4', 'change: 0.20875152823469398', 'is_elite: False']\n", + "Id: 74_27 Identity: {'ancestor_count': 72, 'ancestor_ids': ['2_49', '73_40'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_27', 'origin': '2_49~CUW~73_40#MGNP'} Metrics: ['ELUC: -12.307790268545748', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28473998188303185', 'is_elite: False']\n", + "Id: 73_25 Identity: {'ancestor_count': 71, 'ancestor_ids': ['71_50', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_25', 'origin': '71_50~CUW~72_34#MGNP'} Metrics: ['ELUC: -12.3276101914385', 'NSGA-II_crowding_distance: 0.2850110792341066', 'NSGA-II_rank: 1', 'change: 0.15835267658330512', 'is_elite: True']\n", + "Id: 74_79 Identity: {'ancestor_count': 72, 'ancestor_ids': ['72_32', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_79', 'origin': '72_32~CUW~73_27#MGNP'} Metrics: ['ELUC: -12.394558280237774', 'NSGA-II_crowding_distance: 0.3552876099115169', 'NSGA-II_rank: 3', 'change: 0.20724685683564234', 'is_elite: False']\n", + "Id: 74_51 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '73_54'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_51', 'origin': '73_69~CUW~73_54#MGNP'} Metrics: ['ELUC: -12.606726682394232', 'NSGA-II_crowding_distance: 0.5560494361561055', 'NSGA-II_rank: 4', 'change: 0.26069395231047926', 'is_elite: False']\n", + "Id: 74_90 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_25', '73_38'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_90', 'origin': '73_25~CUW~73_38#MGNP'} Metrics: ['ELUC: -12.988175333523408', 'NSGA-II_crowding_distance: 0.32645941934901074', 'NSGA-II_rank: 2', 'change: 0.17318129446861735', 'is_elite: False']\n", + "Id: 74_28 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '71_50'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_28', 'origin': '72_32~CUW~71_50#MGNP'} Metrics: ['ELUC: -13.174294113340707', 'NSGA-II_crowding_distance: 0.21421923024991776', 'NSGA-II_rank: 3', 'change: 0.2214465553262989', 'is_elite: False']\n", + "Id: 74_33 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '72_34'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_33', 'origin': '72_32~CUW~72_34#MGNP'} Metrics: ['ELUC: -13.207569208678171', 'NSGA-II_crowding_distance: 0.29523264195036286', 'NSGA-II_rank: 1', 'change: 0.16929853313459975', 'is_elite: True']\n", + "Id: 74_86 Identity: {'ancestor_count': 72, 'ancestor_ids': ['72_32', '73_55'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_86', 'origin': '72_32~CUW~73_55#MGNP'} Metrics: ['ELUC: -13.955193427432269', 'NSGA-II_crowding_distance: 0.24554085100888196', 'NSGA-II_rank: 3', 'change: 0.23626316691207488', 'is_elite: False']\n", + "Id: 74_75 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_55', '73_96'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_75', 'origin': '73_55~CUW~73_96#MGNP'} Metrics: ['ELUC: -14.126059361066789', 'NSGA-II_crowding_distance: 0.2365520858723588', 'NSGA-II_rank: 2', 'change: 0.21555271302373466', 'is_elite: False']\n", + "Id: 74_35 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '73_40'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_35', 'origin': '73_40~CUW~73_40#MGNP'} Metrics: ['ELUC: -14.135087526497882', 'NSGA-II_crowding_distance: 0.1508122450085504', 'NSGA-II_rank: 2', 'change: 0.21588133853203662', 'is_elite: False']\n", + "Id: 74_26 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '72_32'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_26', 'origin': '73_69~CUW~72_32#MGNP'} Metrics: ['ELUC: -14.156684024685577', 'NSGA-II_crowding_distance: 0.2816631042895885', 'NSGA-II_rank: 3', 'change: 0.2653998167111667', 'is_elite: False']\n", + "Id: 73_40 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_40', 'origin': '72_63~CUW~72_63#MGNP'} Metrics: ['ELUC: -14.171832324180382', 'NSGA-II_crowding_distance: 0.2595751317006391', 'NSGA-II_rank: 1', 'change: 0.21514649957411305', 'is_elite: True']\n", + "Id: 74_53 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_55', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_53', 'origin': '73_55~CUW~73_27#MGNP'} Metrics: ['ELUC: -14.451340286818905', 'NSGA-II_crowding_distance: 0.08304401966517745', 'NSGA-II_rank: 1', 'change: 0.22564278915315647', 'is_elite: False']\n", + "Id: 74_98 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_55', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_98', 'origin': '73_55~CUW~73_27#MGNP'} Metrics: ['ELUC: -14.498780739340617', 'NSGA-II_crowding_distance: 0.0789230974987421', 'NSGA-II_rank: 1', 'change: 0.23437656899388123', 'is_elite: False']\n", + "Id: 74_44 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '2_49'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_44', 'origin': '73_40~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.933128336586948', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2940820393609432', 'is_elite: False']\n", + "Id: 74_66 Identity: {'ancestor_count': 72, 'ancestor_ids': ['72_34', '73_40'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_66', 'origin': '72_34~CUW~73_40#MGNP'} Metrics: ['ELUC: -15.152428297765347', 'NSGA-II_crowding_distance: 0.29670887895281256', 'NSGA-II_rank: 2', 'change: 0.23866202620467503', 'is_elite: False']\n", + "Id: 74_23 Identity: {'ancestor_count': 72, 'ancestor_ids': ['72_34', '73_55'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_23', 'origin': '72_34~CUW~73_55#MGNP'} Metrics: ['ELUC: -15.267667779583993', 'NSGA-II_crowding_distance: 0.07157342138529432', 'NSGA-II_rank: 1', 'change: 0.2353383534779484', 'is_elite: False']\n", + "Id: 74_29 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '73_100'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_29', 'origin': '1_1~CUW~73_100#MGNP'} Metrics: ['ELUC: -15.391867890252865', 'NSGA-II_crowding_distance: 0.335741243824052', 'NSGA-II_rank: 3', 'change: 0.2825746451937186', 'is_elite: False']\n", + "Id: 74_96 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '73_100'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_96', 'origin': '73_27~CUW~73_100#MGNP'} Metrics: ['ELUC: -15.474464748558985', 'NSGA-II_crowding_distance: 0.186804297670959', 'NSGA-II_rank: 2', 'change: 0.2708229251021879', 'is_elite: False']\n", + "Id: 74_17 Identity: {'ancestor_count': 72, 'ancestor_ids': ['68_68', '73_55'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_17', 'origin': '68_68~CUW~73_55#MGNP'} Metrics: ['ELUC: -15.481123904031998', 'NSGA-II_crowding_distance: 0.06778600499311188', 'NSGA-II_rank: 1', 'change: 0.23906181664528237', 'is_elite: False']\n", + "Id: 74_87 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '73_69'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_87', 'origin': '73_40~CUW~73_69#MGNP'} Metrics: ['ELUC: -15.661950860747387', 'NSGA-II_crowding_distance: 0.24221629907509806', 'NSGA-II_rank: 2', 'change: 0.27790397834110975', 'is_elite: False']\n", + "Id: 74_38 Identity: {'ancestor_count': 72, 'ancestor_ids': ['72_34', '73_40'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_38', 'origin': '72_34~CUW~73_40#MGNP'} Metrics: ['ELUC: -15.754074654849445', 'NSGA-II_crowding_distance: 0.06396092823365457', 'NSGA-II_rank: 1', 'change: 0.24730971214604472', 'is_elite: False']\n", + "Id: 72_32 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_17', '71_52'], 'birth_generation': 72, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '72_32', 'origin': '71_17~CUW~71_52#MGNP'} Metrics: ['ELUC: -15.861071253075375', 'NSGA-II_crowding_distance: 0.02977075676118301', 'NSGA-II_rank: 1', 'change: 0.2516985086199821', 'is_elite: False']\n", + "Id: 74_88 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '72_32'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_88', 'origin': '72_32~CUW~72_32#MGNP'} Metrics: ['ELUC: -15.92595138749958', 'NSGA-II_crowding_distance: 0.0903129099742469', 'NSGA-II_rank: 1', 'change: 0.25327584138364045', 'is_elite: False']\n", + "Id: 74_12 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_96', '72_32'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_12', 'origin': '73_96~CUW~72_32#MGNP'} Metrics: ['ELUC: -16.46907622268366', 'NSGA-II_crowding_distance: 0.14044738120957634', 'NSGA-II_rank: 1', 'change: 0.26832783657462245', 'is_elite: False']\n", + "Id: 74_74 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '73_69'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_74', 'origin': '73_69~CUW~73_69#MGNP'} Metrics: ['ELUC: -16.499413482549244', 'NSGA-II_crowding_distance: 0.09393683041551375', 'NSGA-II_rank: 1', 'change: 0.28545038150302915', 'is_elite: False']\n", + "Id: 74_47 Identity: {'ancestor_count': 71, 'ancestor_ids': ['73_100', '73_54'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_47', 'origin': '73_100~CUW~73_54#MGNP'} Metrics: ['ELUC: -16.926908546104336', 'NSGA-II_crowding_distance: 0.04728164576139987', 'NSGA-II_rank: 1', 'change: 0.2885869377117804', 'is_elite: False']\n", + "Id: 73_69 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_15', '72_72'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_69', 'origin': '72_15~CUW~72_72#MGNP'} Metrics: ['ELUC: -16.938432685539972', 'NSGA-II_crowding_distance: 0.06472693215982951', 'NSGA-II_rank: 1', 'change: 0.2921078797307474', 'is_elite: False']\n", + "Id: 74_43 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_100', '73_40'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_43', 'origin': '73_100~CUW~73_40#MGNP'} Metrics: ['ELUC: -17.00876975289846', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30549053909438917', 'is_elite: False']\n", + "Id: 74_97 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '73_100'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_97', 'origin': '72_32~CUW~73_100#MGNP'} Metrics: ['ELUC: -17.32889882150725', 'NSGA-II_crowding_distance: 0.06958698045984399', 'NSGA-II_rank: 1', 'change: 0.3010781129339305', 'is_elite: False']\n", + "Id: 74_45 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_96', '73_100'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_45', 'origin': '73_96~CUW~73_100#MGNP'} Metrics: ['ELUC: -17.5197077634263', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30240770773014364', 'is_elite: False']\n", + "Id: 74_64 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_100', '73_38'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_64', 'origin': '73_100~CUW~73_38#MGNP'} Metrics: ['ELUC: -17.568132763202275', 'NSGA-II_crowding_distance: 0.02174438973383143', 'NSGA-II_rank: 1', 'change: 0.30218487953921763', 'is_elite: False']\n", + "Id: 74_25 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_55', '2_49'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_25', 'origin': '73_55~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.596982338125176', 'NSGA-II_crowding_distance: 0.004464251845257225', 'NSGA-II_rank: 1', 'change: 0.30301669435141787', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 73_100 Identity: {'ancestor_count': 70, 'ancestor_ids': ['72_100', '72_13'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_100', 'origin': '72_100~CUW~72_13#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 74_41 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '73_55'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_41', 'origin': '73_69~CUW~73_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 74.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 75...:\n", + "PopulationResponse:\n", + " Generation: 75\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/75/20240220-044237\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 75 and asking ESP for generation 76...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 75 data persisted.\n", + "Evaluated candidates:\n", + "Id: 75_80 Identity: {'ancestor_count': 73, 'ancestor_ids': ['1_1', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_80', 'origin': '1_1~CUW~74_41#MGNP'} Metrics: ['ELUC: 20.83696543789787', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2634376653507324', 'is_elite: False']\n", + "Id: 75_51 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '74_37'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_51', 'origin': '2_49~CUW~74_37#MGNP'} Metrics: ['ELUC: 2.224375498076022', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3445771929965503', 'is_elite: False']\n", + "Id: 75_60 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_25', '1_1'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_60', 'origin': '73_25~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.1023679893951104', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.13088366734817244', 'is_elite: False']\n", + "Id: 75_44 Identity: {'ancestor_count': 70, 'ancestor_ids': ['2_49', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_44', 'origin': '2_49~CUW~71_50#MGNP'} Metrics: ['ELUC: 0.9867995660713337', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.22643181368384663', 'is_elite: False']\n", + "Id: 75_89 Identity: {'ancestor_count': 70, 'ancestor_ids': ['74_37', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_89', 'origin': '74_37~CUW~71_50#MGNP'} Metrics: ['ELUC: 0.16724991208542536', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.06515926577239188', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 75_15 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_37', '74_34'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_15', 'origin': '74_37~CUW~74_34#MGNP'} Metrics: ['ELUC: -0.17096925448518382', 'NSGA-II_crowding_distance: 0.17637802104294947', 'NSGA-II_rank: 2', 'change: 0.06614328917769943', 'is_elite: False']\n", + "Id: 71_50 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_50', 'origin': '70_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6682910644908597', 'NSGA-II_crowding_distance: 0.3461942876669976', 'NSGA-II_rank: 1', 'change: 0.049392437516290626', 'is_elite: True']\n", + "Id: 75_87 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_87', 'origin': '74_57~CUW~74_40#MGNP'} Metrics: ['ELUC: -1.7883348972758588', 'NSGA-II_crowding_distance: 0.23821434390846374', 'NSGA-II_rank: 2', 'change: 0.08090127379454497', 'is_elite: False']\n", + "Id: 75_97 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_97', 'origin': '74_41~CUW~71_50#MGNP'} Metrics: ['ELUC: -1.8532695453107726', 'NSGA-II_crowding_distance: 0.6940746184487626', 'NSGA-II_rank: 7', 'change: 0.24441900702793382', 'is_elite: False']\n", + "Id: 75_74 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_74', 'origin': '74_57~CUW~71_50#MGNP'} Metrics: ['ELUC: -2.0472247680308167', 'NSGA-II_crowding_distance: 0.2921101707154583', 'NSGA-II_rank: 1', 'change: 0.07345273606135509', 'is_elite: True']\n", + "Id: 75_36 Identity: {'ancestor_count': 72, 'ancestor_ids': ['71_50', '74_36'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_36', 'origin': '71_50~CUW~74_36#MGNP'} Metrics: ['ELUC: -2.5965622112187274', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08550348572797138', 'is_elite: False']\n", + "Id: 75_20 Identity: {'ancestor_count': 73, 'ancestor_ids': ['73_40', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_20', 'origin': '73_40~CUW~74_41#MGNP'} Metrics: ['ELUC: -2.622282207324475', 'NSGA-II_crowding_distance: 0.3504440823237622', 'NSGA-II_rank: 7', 'change: 0.25342399192312004', 'is_elite: False']\n", + "Id: 75_54 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_54', 'origin': '1_1~CUW~73_40#MGNP'} Metrics: ['ELUC: -2.8350453581625135', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.08297017099189789', 'is_elite: False']\n", + "Id: 75_98 Identity: {'ancestor_count': 72, 'ancestor_ids': ['68_68', '73_25'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_98', 'origin': '68_68~CUW~73_25#MGNP'} Metrics: ['ELUC: -3.127568137290079', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09921011920962024', 'is_elite: False']\n", + "Id: 75_41 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_40', '1_1'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_41', 'origin': '74_40~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.1743239542514265', 'NSGA-II_crowding_distance: 0.16912491111633168', 'NSGA-II_rank: 2', 'change: 0.08254732934442999', 'is_elite: False']\n", + "Id: 75_73 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_73', 'origin': '73_40~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.469174147731571', 'NSGA-II_crowding_distance: 0.7175168081489317', 'NSGA-II_rank: 7', 'change: 0.2593591982174706', 'is_elite: False']\n", + "Id: 75_33 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_33', 'origin': '73_27~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.908516633140817', 'NSGA-II_crowding_distance: 1.9338502805320985', 'NSGA-II_rank: 8', 'change: 0.29337912522488996', 'is_elite: False']\n", + "Id: 75_63 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_63', 'origin': '74_57~CUW~74_40#MGNP'} Metrics: ['ELUC: -4.180977039095768', 'NSGA-II_crowding_distance: 0.3536990148826678', 'NSGA-II_rank: 5', 'change: 0.12351651960697164', 'is_elite: False']\n", + "Id: 75_42 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_40', '74_57'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_42', 'origin': '74_40~CUW~74_57#MGNP'} Metrics: ['ELUC: -4.237649712299562', 'NSGA-II_crowding_distance: 0.2687653123337841', 'NSGA-II_rank: 1', 'change: 0.07597848638455729', 'is_elite: True']\n", + "Id: 75_95 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_70'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_95', 'origin': '74_57~CUW~74_70#MGNP'} Metrics: ['ELUC: -4.5089435523192325', 'NSGA-II_crowding_distance: 0.17914628803551044', 'NSGA-II_rank: 2', 'change: 0.08465770114704094', 'is_elite: False']\n", + "Id: 75_34 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_33', '74_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_34', 'origin': '74_33~CUW~74_40#MGNP'} Metrics: ['ELUC: -4.689732736557759', 'NSGA-II_crowding_distance: 0.8054960477988274', 'NSGA-II_rank: 5', 'change: 0.1288877881407765', 'is_elite: False']\n", + "Id: 75_64 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_64', 'origin': '74_41~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.773816807407573', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3127704548798452', 'is_elite: False']\n", + "Id: 75_84 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_33'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_84', 'origin': '74_57~CUW~74_33#MGNP'} Metrics: ['ELUC: -5.179165828122863', 'NSGA-II_crowding_distance: 0.4588488212902383', 'NSGA-II_rank: 4', 'change: 0.09882824632806562', 'is_elite: False']\n", + "Id: 75_32 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_32', 'origin': '73_27~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.433015942158975', 'NSGA-II_crowding_distance: 0.44890892206778304', 'NSGA-II_rank: 8', 'change: 0.30878581817295736', 'is_elite: False']\n", + "Id: 75_47 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_47', 'origin': '74_57~CUW~71_50#MGNP'} Metrics: ['ELUC: -5.814980277733725', 'NSGA-II_crowding_distance: 0.47044411691977267', 'NSGA-II_rank: 3', 'change: 0.08704410002858169', 'is_elite: False']\n", + "Id: 75_19 Identity: {'ancestor_count': 73, 'ancestor_ids': ['71_50', '74_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_19', 'origin': '71_50~CUW~74_40#MGNP'} Metrics: ['ELUC: -5.959778374463411', 'NSGA-II_crowding_distance: 0.1989667904555678', 'NSGA-II_rank: 4', 'change: 0.11018019260204527', 'is_elite: False']\n", + "Id: 75_72 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_37'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_72', 'origin': '74_57~CUW~74_37#MGNP'} Metrics: ['ELUC: -6.064327766744584', 'NSGA-II_crowding_distance: 0.20579861376609146', 'NSGA-II_rank: 2', 'change: 0.08641653968249756', 'is_elite: False']\n", + "Id: 75_71 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_70', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_71', 'origin': '74_70~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.147460899705534', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3106592654376493', 'is_elite: False']\n", + "Id: 75_88 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '68_68'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_88', 'origin': '74_33~CUW~68_68#MGNP'} Metrics: ['ELUC: -6.282104507000365', 'NSGA-II_crowding_distance: 0.3194084895190702', 'NSGA-II_rank: 4', 'change: 0.11470786700155737', 'is_elite: False']\n", + "Id: 75_81 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_94', '73_27'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_81', 'origin': '74_94~CUW~73_27#MGNP'} Metrics: ['ELUC: -6.335147045407135', 'NSGA-II_crowding_distance: 0.2081825783335874', 'NSGA-II_rank: 1', 'change: 0.08087895321137822', 'is_elite: True']\n", + "Id: 75_61 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_40', '74_70'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_61', 'origin': '74_40~CUW~74_70#MGNP'} Metrics: ['ELUC: -6.379513857752427', 'NSGA-II_crowding_distance: 0.323360599876035', 'NSGA-II_rank: 3', 'change: 0.10478154505095295', 'is_elite: False']\n", + "Id: 75_90 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '68_68'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_90', 'origin': '74_33~CUW~68_68#MGNP'} Metrics: ['ELUC: -7.028493316756113', 'NSGA-II_crowding_distance: 0.12675825237903476', 'NSGA-II_rank: 1', 'change: 0.0907340522640954', 'is_elite: False']\n", + "Id: 75_55 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_34', '73_27'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_55', 'origin': '74_34~CUW~73_27#MGNP'} Metrics: ['ELUC: -7.087949950894965', 'NSGA-II_crowding_distance: 0.14636699823369376', 'NSGA-II_rank: 2', 'change: 0.09903949943632319', 'is_elite: False']\n", + "Id: 75_79 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_79', 'origin': '74_57~CUW~74_40#MGNP'} Metrics: ['ELUC: -7.2405229168386835', 'NSGA-II_crowding_distance: 0.28346581295344936', 'NSGA-II_rank: 3', 'change: 0.1161660785754777', 'is_elite: False']\n", + "Id: 75_70 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_34'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_70', 'origin': '74_57~CUW~74_34#MGNP'} Metrics: ['ELUC: -7.3134954290964105', 'NSGA-II_crowding_distance: 0.2154140863994758', 'NSGA-II_rank: 2', 'change: 0.10449132077570088', 'is_elite: False']\n", + "Id: 75_67 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_67', 'origin': '74_41~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.400263850236954', 'NSGA-II_crowding_distance: 0.6977754508280697', 'NSGA-II_rank: 7', 'change: 0.2746728240594133', 'is_elite: False']\n", + "Id: 75_93 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '1_1'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_93', 'origin': '74_41~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.444757488574116', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.2132995137906308', 'is_elite: False']\n", + "Id: 75_14 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_34', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_14', 'origin': '74_34~CUW~74_41#MGNP'} Metrics: ['ELUC: -7.4663414879840255', 'NSGA-II_crowding_distance: 0.755214582170741', 'NSGA-II_rank: 5', 'change: 0.19622687531369454', 'is_elite: False']\n", + "Id: 75_92 Identity: {'ancestor_count': 71, 'ancestor_ids': ['68_68', '74_94'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_92', 'origin': '68_68~CUW~74_94#MGNP'} Metrics: ['ELUC: -7.522100745484426', 'NSGA-II_crowding_distance: 0.06669676132089944', 'NSGA-II_rank: 1', 'change: 0.09855782076285441', 'is_elite: False']\n", + "Id: 75_53 Identity: {'ancestor_count': 73, 'ancestor_ids': ['73_27', '74_70'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_53', 'origin': '73_27~CUW~74_70#MGNP'} Metrics: ['ELUC: -7.538346117695978', 'NSGA-II_crowding_distance: 0.035160708688383856', 'NSGA-II_rank: 1', 'change: 0.1019825203109069', 'is_elite: False']\n", + "Id: 75_18 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '74_34'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_18', 'origin': '74_41~CUW~74_34#MGNP'} Metrics: ['ELUC: -7.711973478886355', 'NSGA-II_crowding_distance: 0.2628847880580201', 'NSGA-II_rank: 5', 'change: 0.1981518136037386', 'is_elite: False']\n", + "Id: 75_56 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_37', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_56', 'origin': '74_37~CUW~74_41#MGNP'} Metrics: ['ELUC: -7.721831762794213', 'NSGA-II_crowding_distance: 0.4508064875114203', 'NSGA-II_rank: 7', 'change: 0.2825269007632416', 'is_elite: False']\n", + "Id: 75_94 Identity: {'ancestor_count': 73, 'ancestor_ids': ['71_50', '74_34'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_94', 'origin': '71_50~CUW~74_34#MGNP'} Metrics: ['ELUC: -7.76829325409956', 'NSGA-II_crowding_distance: 0.0908336498064838', 'NSGA-II_rank: 1', 'change: 0.1048710299172094', 'is_elite: False']\n", + "Id: 75_82 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '73_27'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_82', 'origin': '1_1~CUW~73_27#MGNP'} Metrics: ['ELUC: -7.882746204510676', 'NSGA-II_crowding_distance: 0.22866322161780017', 'NSGA-II_rank: 3', 'change: 0.12676583311310619', 'is_elite: False']\n", + "Id: 75_29 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_24', '74_12'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_29', 'origin': '74_24~CUW~74_12#MGNP'} Metrics: ['ELUC: -8.163421446498424', 'NSGA-II_crowding_distance: 0.32956677900934606', 'NSGA-II_rank: 4', 'change: 0.12936179810016565', 'is_elite: False']\n", + "Id: 75_77 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_40', '74_33'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_77', 'origin': '74_40~CUW~74_33#MGNP'} Metrics: ['ELUC: -8.738280916545495', 'NSGA-II_crowding_distance: 0.4215671317042097', 'NSGA-II_rank: 4', 'change: 0.13184084492042147', 'is_elite: False']\n", + "Id: 68_68 Identity: {'ancestor_count': 66, 'ancestor_ids': ['67_100', '67_100'], 'birth_generation': 68, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '68_68', 'origin': '67_100~CUW~67_100#MGNP'} Metrics: ['ELUC: -8.761487407874672', 'NSGA-II_crowding_distance: 0.09471479398312693', 'NSGA-II_rank: 1', 'change: 0.10832817250116257', 'is_elite: False']\n", + "Id: 75_91 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '73_27'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_91', 'origin': '74_41~CUW~73_27#MGNP'} Metrics: ['ELUC: -8.817116535357018', 'NSGA-II_crowding_distance: 0.4336831281372908', 'NSGA-II_rank: 5', 'change: 0.21471397097820846', 'is_elite: False']\n", + "Id: 75_25 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_25', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_25', 'origin': '73_25~CUW~73_40#MGNP'} Metrics: ['ELUC: -8.884097169316206', 'NSGA-II_crowding_distance: 0.15127426208088948', 'NSGA-II_rank: 3', 'change: 0.12787546792760865', 'is_elite: False']\n", + "Id: 75_30 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_24', '68_68'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_30', 'origin': '74_24~CUW~68_68#MGNP'} Metrics: ['ELUC: -8.887540465426698', 'NSGA-II_crowding_distance: 0.1161696555436871', 'NSGA-II_rank: 1', 'change: 0.11413784357096773', 'is_elite: False']\n", + "Id: 75_96 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_33', '74_34'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_96', 'origin': '74_33~CUW~74_34#MGNP'} Metrics: ['ELUC: -9.37238504312259', 'NSGA-II_crowding_distance: 0.14916973159090566', 'NSGA-II_rank: 3', 'change: 0.12888807316192782', 'is_elite: False']\n", + "Id: 75_99 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '68_68'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_99', 'origin': '74_57~CUW~68_68#MGNP'} Metrics: ['ELUC: -9.40525617725543', 'NSGA-II_crowding_distance: 0.22975065726943847', 'NSGA-II_rank: 2', 'change: 0.11921891759893359', 'is_elite: False']\n", + "Id: 75_75 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_33', '74_74'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_75', 'origin': '74_33~CUW~74_74#MGNP'} Metrics: ['ELUC: -9.416478111206287', 'NSGA-II_crowding_distance: 0.6674039895980614', 'NSGA-II_rank: 5', 'change: 0.23851068285958973', 'is_elite: False']\n", + "Id: 75_43 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_43', 'origin': '73_40~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.696548198894837', 'NSGA-II_crowding_distance: 0.45082286136071537', 'NSGA-II_rank: 7', 'change: 0.2925085236818887', 'is_elite: False']\n", + "Id: 75_16 Identity: {'ancestor_count': 70, 'ancestor_ids': ['68_68', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_16', 'origin': '68_68~CUW~71_50#MGNP'} Metrics: ['ELUC: -10.053950909562356', 'NSGA-II_crowding_distance: 0.15918392464501613', 'NSGA-II_rank: 3', 'change: 0.13414892587494123', 'is_elite: False']\n", + "Id: 75_78 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '68_68'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_78', 'origin': '74_57~CUW~68_68#MGNP'} Metrics: ['ELUC: -10.139801082437035', 'NSGA-II_crowding_distance: 0.16148776622905314', 'NSGA-II_rank: 2', 'change: 0.12125586968031157', 'is_elite: False']\n", + "Id: 75_35 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_35', 'origin': '74_33~CUW~71_50#MGNP'} Metrics: ['ELUC: -10.190613904050956', 'NSGA-II_crowding_distance: 0.16475289792417283', 'NSGA-II_rank: 3', 'change: 0.1415961388967645', 'is_elite: False']\n", + "Id: 75_86 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_74', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_86', 'origin': '74_74~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.3313659462716', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2983726899742052', 'is_elite: False']\n", + "Id: 75_40 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_34'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_40', 'origin': '74_57~CUW~74_34#MGNP'} Metrics: ['ELUC: -10.33382633207815', 'NSGA-II_crowding_distance: 0.12485077380179159', 'NSGA-II_rank: 1', 'change: 0.11630753271373978', 'is_elite: False']\n", + "Id: 75_37 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_37', 'origin': '74_33~CUW~71_50#MGNP'} Metrics: ['ELUC: -10.583287712661123', 'NSGA-II_crowding_distance: 1.1541416185651396', 'NSGA-II_rank: 4', 'change: 0.1617980495179933', 'is_elite: False']\n", + "Id: 75_57 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_57', 'origin': '74_33~CUW~73_40#MGNP'} Metrics: ['ELUC: -10.597108850611994', 'NSGA-II_crowding_distance: 0.33241179884506156', 'NSGA-II_rank: 3', 'change: 0.1515471156813807', 'is_elite: False']\n", + "Id: 74_57 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '73_27'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_57', 'origin': '73_27~CUW~73_27#MGNP'} Metrics: ['ELUC: -10.623446576838816', 'NSGA-II_crowding_distance: 0.05603082078112179', 'NSGA-II_rank: 1', 'change: 0.12193167043452074', 'is_elite: False']\n", + "Id: 73_27 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_98', '72_35'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_27', 'origin': '72_98~CUW~72_35#MGNP'} Metrics: ['ELUC: -10.81389723024378', 'NSGA-II_crowding_distance: 0.03745044459292079', 'NSGA-II_rank: 1', 'change: 0.12487892986855983', 'is_elite: False']\n", + "Id: 75_59 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '68_68'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_59', 'origin': '73_27~CUW~68_68#MGNP'} Metrics: ['ELUC: -10.875207421669522', 'NSGA-II_crowding_distance: 0.04945236188401543', 'NSGA-II_rank: 1', 'change: 0.12883358937302836', 'is_elite: False']\n", + "Id: 75_46 Identity: {'ancestor_count': 73, 'ancestor_ids': ['2_49', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_46', 'origin': '2_49~CUW~74_41#MGNP'} Metrics: ['ELUC: -11.027175936289954', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2811255686916856', 'is_elite: False']\n", + "Id: 75_58 Identity: {'ancestor_count': 73, 'ancestor_ids': ['73_40', '74_34'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_58', 'origin': '73_40~CUW~74_34#MGNP'} Metrics: ['ELUC: -11.036881306771102', 'NSGA-II_crowding_distance: 0.27921315830805854', 'NSGA-II_rank: 2', 'change: 0.1357624799965194', 'is_elite: False']\n", + "Id: 75_24 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '74_33'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_24', 'origin': '73_40~CUW~74_33#MGNP'} Metrics: ['ELUC: -11.098541892831934', 'NSGA-II_crowding_distance: 0.13982468090729153', 'NSGA-II_rank: 1', 'change: 0.13480390493539648', 'is_elite: False']\n", + "Id: 75_17 Identity: {'ancestor_count': 72, 'ancestor_ids': ['2_49', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_17', 'origin': '2_49~CUW~73_40#MGNP'} Metrics: ['ELUC: -12.00207258479644', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2662476724977446', 'is_elite: False']\n", + "Id: 75_62 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '73_27'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_62', 'origin': '74_33~CUW~73_27#MGNP'} Metrics: ['ELUC: -12.082947775492464', 'NSGA-II_crowding_distance: 0.15037461087272094', 'NSGA-II_rank: 1', 'change: 0.15005843208393924', 'is_elite: False']\n", + "Id: 75_66 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '73_25'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_66', 'origin': '73_40~CUW~73_25#MGNP'} Metrics: ['ELUC: -12.211085629325003', 'NSGA-II_crowding_distance: 0.7300009843613209', 'NSGA-II_rank: 3', 'change: 0.16377424630393947', 'is_elite: False']\n", + "Id: 73_25 Identity: {'ancestor_count': 71, 'ancestor_ids': ['71_50', '72_34'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_25', 'origin': '71_50~CUW~72_34#MGNP'} Metrics: ['ELUC: -12.3276101914385', 'NSGA-II_crowding_distance: 0.3071110175813557', 'NSGA-II_rank: 2', 'change: 0.15835267658330512', 'is_elite: False']\n", + "Id: 75_26 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_26', 'origin': '73_27~CUW~73_40#MGNP'} Metrics: ['ELUC: -12.579000469303365', 'NSGA-II_crowding_distance: 0.07097076703057573', 'NSGA-II_rank: 1', 'change: 0.15454849935485493', 'is_elite: False']\n", + "Id: 75_48 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '74_33'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_48', 'origin': '73_27~CUW~74_33#MGNP'} Metrics: ['ELUC: -12.61238649344973', 'NSGA-II_crowding_distance: 0.08518410647737024', 'NSGA-II_rank: 1', 'change: 0.16224978913808516', 'is_elite: False']\n", + "Id: 75_76 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_76', 'origin': '1_1~CUW~73_40#MGNP'} Metrics: ['ELUC: -12.803188733824665', 'NSGA-II_crowding_distance: 0.21524359252184372', 'NSGA-II_rank: 2', 'change: 0.18515021683845415', 'is_elite: False']\n", + "Id: 75_31 Identity: {'ancestor_count': 73, 'ancestor_ids': ['73_25', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_31', 'origin': '73_25~CUW~74_41#MGNP'} Metrics: ['ELUC: -13.098689133359779', 'NSGA-II_crowding_distance: 0.20320267217959537', 'NSGA-II_rank: 2', 'change: 0.199227982484795', 'is_elite: False']\n", + "Id: 75_65 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_12', '74_37'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_65', 'origin': '74_12~CUW~74_37#MGNP'} Metrics: ['ELUC: -13.147958567111761', 'NSGA-II_crowding_distance: 0.603220084555811', 'NSGA-II_rank: 3', 'change: 0.22662090670338259', 'is_elite: False']\n", + "Id: 74_33 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '72_34'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_33', 'origin': '72_32~CUW~72_34#MGNP'} Metrics: ['ELUC: -13.207569208678171', 'NSGA-II_crowding_distance: 0.25991137950390214', 'NSGA-II_rank: 1', 'change: 0.16929853313459975', 'is_elite: True']\n", + "Id: 75_69 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '74_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_69', 'origin': '74_41~CUW~74_40#MGNP'} Metrics: ['ELUC: -13.61684487237768', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.24609156965456622', 'is_elite: False']\n", + "Id: 75_22 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '74_12'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_22', 'origin': '74_41~CUW~74_12#MGNP'} Metrics: ['ELUC: -13.68586091216799', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.23465973866307377', 'is_elite: False']\n", + "Id: 73_40 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_63', '72_63'], 'birth_generation': 73, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '73_40', 'origin': '72_63~CUW~72_63#MGNP'} Metrics: ['ELUC: -14.171832324180382', 'NSGA-II_crowding_distance: 0.44875266168980743', 'NSGA-II_rank: 2', 'change: 0.21514649957411305', 'is_elite: False']\n", + "Id: 75_27 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_12', '68_68'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_27', 'origin': '74_12~CUW~68_68#MGNP'} Metrics: ['ELUC: -14.20664053760566', 'NSGA-II_crowding_distance: 0.2959540109816174', 'NSGA-II_rank: 1', 'change: 0.21274657006678627', 'is_elite: True']\n", + "Id: 75_52 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_52', 'origin': '74_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.399602729604444', 'NSGA-II_crowding_distance: 0.4162879981146699', 'NSGA-II_rank: 2', 'change: 0.28856010988925634', 'is_elite: False']\n", + "Id: 75_68 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_36', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_68', 'origin': '74_36~CUW~73_40#MGNP'} Metrics: ['ELUC: -14.67311842777939', 'NSGA-II_crowding_distance: 0.12616790798717753', 'NSGA-II_rank: 1', 'change: 0.23273379260746824', 'is_elite: False']\n", + "Id: 75_85 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_40', '73_25'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_85', 'origin': '73_40~CUW~73_25#MGNP'} Metrics: ['ELUC: -15.092675731565237', 'NSGA-II_crowding_distance: 0.07029009759256548', 'NSGA-II_rank: 1', 'change: 0.23535597179015064', 'is_elite: False']\n", + "Id: 75_12 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '74_12'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_12', 'origin': '74_57~CUW~74_12#MGNP'} Metrics: ['ELUC: -15.359471386356306', 'NSGA-II_crowding_distance: 0.0713756730704605', 'NSGA-II_rank: 1', 'change: 0.24205917005121935', 'is_elite: False']\n", + "Id: 75_39 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_27', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_39', 'origin': '73_27~CUW~73_40#MGNP'} Metrics: ['ELUC: -15.725900754030654', 'NSGA-II_crowding_distance: 0.04234688768918719', 'NSGA-II_rank: 1', 'change: 0.2459068582119086', 'is_elite: False']\n", + "Id: 75_23 Identity: {'ancestor_count': 73, 'ancestor_ids': ['73_25', '74_12'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_23', 'origin': '73_25~CUW~74_12#MGNP'} Metrics: ['ELUC: -15.786916578913116', 'NSGA-II_crowding_distance: 0.12782038385194947', 'NSGA-II_rank: 1', 'change: 0.24744066096816955', 'is_elite: False']\n", + "Id: 75_50 Identity: {'ancestor_count': 73, 'ancestor_ids': ['2_49', '74_12'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_50', 'origin': '2_49~CUW~74_12#MGNP'} Metrics: ['ELUC: -15.829298568617201', 'NSGA-II_crowding_distance: 0.24011421133983868', 'NSGA-II_rank: 2', 'change: 0.2919720780288236', 'is_elite: False']\n", + "Id: 75_45 Identity: {'ancestor_count': 73, 'ancestor_ids': ['73_25', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_45', 'origin': '73_25~CUW~74_41#MGNP'} Metrics: ['ELUC: -16.27048880984466', 'NSGA-II_crowding_distance: 0.20997502332133017', 'NSGA-II_rank: 1', 'change: 0.2748037850642168', 'is_elite: True']\n", + "Id: 75_11 Identity: {'ancestor_count': 73, 'ancestor_ids': ['1_1', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_11', 'origin': '1_1~CUW~74_41#MGNP'} Metrics: ['ELUC: -16.80587068219165', 'NSGA-II_crowding_distance: 0.16967198794658434', 'NSGA-II_rank: 1', 'change: 0.2928005633606387', 'is_elite: False']\n", + "Id: 75_83 Identity: {'ancestor_count': 72, 'ancestor_ids': ['2_49', '73_40'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_83', 'origin': '2_49~CUW~73_40#MGNP'} Metrics: ['ELUC: -17.575311346710915', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3031047763870331', 'is_elite: False']\n", + "Id: 75_38 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_38', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.592989527448054', 'NSGA-II_crowding_distance: 0.07926923064505326', 'NSGA-II_rank: 1', 'change: 0.30298688029088694', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 74_41 Identity: {'ancestor_count': 72, 'ancestor_ids': ['73_69', '73_55'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_41', 'origin': '73_69~CUW~73_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 75_13 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '74_70'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_13', 'origin': '74_41~CUW~74_70#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 75_21 Identity: {'ancestor_count': 72, 'ancestor_ids': ['2_49', '73_25'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_21', 'origin': '2_49~CUW~73_25#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 75_28 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_41', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_28', 'origin': '74_41~CUW~74_41#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 75_49 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_49', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 75_100 Identity: {'ancestor_count': 72, 'ancestor_ids': ['2_49', '73_25'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_100', 'origin': '2_49~CUW~73_25#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 75.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 76...:\n", + "PopulationResponse:\n", + " Generation: 76\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/76/20240220-044952\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 76 and asking ESP for generation 77...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 76 data persisted.\n", + "Evaluated candidates:\n", + "Id: 76_67 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_42', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_67', 'origin': '75_42~CUW~75_100#MGNP'} Metrics: ['ELUC: 16.971835371890258', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.286259392350798', 'is_elite: False']\n", + "Id: 76_55 Identity: {'ancestor_count': 73, 'ancestor_ids': ['2_49', '75_81'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_55', 'origin': '2_49~CUW~75_81#MGNP'} Metrics: ['ELUC: 13.297589414471032', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2684021401489486', 'is_elite: False']\n", + "Id: 76_86 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_86', 'origin': '75_74~CUW~2_49#MGNP'} Metrics: ['ELUC: 12.58247029093505', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.28118286829544376', 'is_elite: False']\n", + "Id: 76_53 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_45', '75_74'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_53', 'origin': '75_45~CUW~75_74#MGNP'} Metrics: ['ELUC: 7.649430804893386', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2066738564408836', 'is_elite: False']\n", + "Id: 76_22 Identity: {'ancestor_count': 74, 'ancestor_ids': ['1_1', '75_23'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_22', 'origin': '1_1~CUW~75_23#MGNP'} Metrics: ['ELUC: 5.8096854575235035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.10089783365554983', 'is_elite: False']\n", + "Id: 76_39 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_11', '1_1'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_39', 'origin': '75_11~CUW~1_1#MGNP'} Metrics: ['ELUC: 4.568201481886468', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.17538693111970963', 'is_elite: False']\n", + "Id: 76_46 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_81', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_46', 'origin': '75_81~CUW~75_100#MGNP'} Metrics: ['ELUC: 2.5068278764798166', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.351394501419715', 'is_elite: False']\n", + "Id: 76_83 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_100', '75_45'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_83', 'origin': '75_100~CUW~75_45#MGNP'} Metrics: ['ELUC: 1.7690420293780729', 'NSGA-II_crowding_distance: 1.6416820476293872', 'NSGA-II_rank: 9', 'change: 0.2351554949267611', 'is_elite: False']\n", + "Id: 76_18 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '71_50'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_18', 'origin': '75_74~CUW~71_50#MGNP'} Metrics: ['ELUC: 1.7040187701551563', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08153120939195363', 'is_elite: False']\n", + "Id: 76_89 Identity: {'ancestor_count': 70, 'ancestor_ids': ['1_1', '71_50'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_89', 'origin': '1_1~CUW~71_50#MGNP'} Metrics: ['ELUC: 1.431148784034423', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.044238554594516435', 'is_elite: False']\n", + "Id: 76_93 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_93', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.9184466166797314', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.024755398152432512', 'is_elite: False']\n", + "Id: 76_45 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_45', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.14896022790903274', 'NSGA-II_crowding_distance: 0.33517346818419624', 'NSGA-II_rank: 2', 'change: 0.028071323728168056', 'is_elite: False']\n", + "Id: 76_88 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_88', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.09308405403921784', 'NSGA-II_crowding_distance: 1.1769656174457257', 'NSGA-II_rank: 9', 'change: 0.3067390530280986', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 76_92 Identity: {'ancestor_count': 70, 'ancestor_ids': ['71_50', '1_1'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_92', 'origin': '71_50~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.3470877951259456', 'NSGA-II_crowding_distance: 0.18713003403490192', 'NSGA-II_rank: 1', 'change: 0.034273788579084884', 'is_elite: False']\n", + "Id: 71_50 Identity: {'ancestor_count': 69, 'ancestor_ids': ['70_14', '1_1'], 'birth_generation': 71, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '71_50', 'origin': '70_14~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6682910644908597', 'NSGA-II_crowding_distance: 0.1700821432485159', 'NSGA-II_rank: 1', 'change: 0.049392437516290626', 'is_elite: False']\n", + "Id: 76_12 Identity: {'ancestor_count': 74, 'ancestor_ids': ['2_49', '75_74'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_12', 'origin': '2_49~CUW~75_74#MGNP'} Metrics: ['ELUC: -0.684174641805941', 'NSGA-II_crowding_distance: 1.1161909621993815', 'NSGA-II_rank: 8', 'change: 0.23175077930047727', 'is_elite: False']\n", + "Id: 76_70 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_45', '75_81'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_70', 'origin': '75_45~CUW~75_81#MGNP'} Metrics: ['ELUC: -1.3685837963757677', 'NSGA-II_crowding_distance: 1.5198076090423376', 'NSGA-II_rank: 7', 'change: 0.15722078270696419', 'is_elite: False']\n", + "Id: 76_31 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '75_74'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_31', 'origin': '75_74~CUW~75_74#MGNP'} Metrics: ['ELUC: -1.6925737591353804', 'NSGA-II_crowding_distance: 0.5447674687859798', 'NSGA-II_rank: 3', 'change: 0.08342514249603507', 'is_elite: False']\n", + "Id: 76_81 Identity: {'ancestor_count': 73, 'ancestor_ids': ['2_49', '75_81'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_81', 'origin': '2_49~CUW~75_81#MGNP'} Metrics: ['ELUC: -1.7374783188797782', 'NSGA-II_crowding_distance: 0.4874925675804709', 'NSGA-II_rank: 8', 'change: 0.24881488436801522', 'is_elite: False']\n", + "Id: 76_35 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '75_23'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_35', 'origin': '75_74~CUW~75_23#MGNP'} Metrics: ['ELUC: -1.8319510105226593', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.09564772530035953', 'is_elite: False']\n", + "Id: 76_37 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_42', '71_50'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_37', 'origin': '75_42~CUW~71_50#MGNP'} Metrics: ['ELUC: -1.9856538481975252', 'NSGA-II_crowding_distance: 0.18138103413285595', 'NSGA-II_rank: 1', 'change: 0.057215538863216696', 'is_elite: False']\n", + "Id: 75_74 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_57', '71_50'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_74', 'origin': '74_57~CUW~71_50#MGNP'} Metrics: ['ELUC: -2.0472247680308167', 'NSGA-II_crowding_distance: 0.3420790234071383', 'NSGA-II_rank: 2', 'change: 0.07345273606135509', 'is_elite: False']\n", + "Id: 76_65 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_42', '75_42'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_65', 'origin': '75_42~CUW~75_42#MGNP'} Metrics: ['ELUC: -2.815174771598541', 'NSGA-II_crowding_distance: 0.19959346077867476', 'NSGA-II_rank: 1', 'change: 0.06707921780129368', 'is_elite: True']\n", + "Id: 76_33 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_33', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.8340644914895474', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3153344314725327', 'is_elite: False']\n", + "Id: 76_64 Identity: {'ancestor_count': 73, 'ancestor_ids': ['71_50', '75_68'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_64', 'origin': '71_50~CUW~75_68#MGNP'} Metrics: ['ELUC: -3.0084711946256526', 'NSGA-II_crowding_distance: 0.28266758673440073', 'NSGA-II_rank: 6', 'change: 0.10271579935548049', 'is_elite: False']\n", + "Id: 76_23 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_42', '75_74'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_23', 'origin': '75_42~CUW~75_74#MGNP'} Metrics: ['ELUC: -3.078188416828767', 'NSGA-II_crowding_distance: 0.1273771685975314', 'NSGA-II_rank: 2', 'change: 0.07476062022108229', 'is_elite: False']\n", + "Id: 76_15 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '1_1'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_15', 'origin': '74_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.3824302133011757', 'NSGA-II_crowding_distance: 1.2382548689123674', 'NSGA-II_rank: 6', 'change: 0.10823698338322509', 'is_elite: False']\n", + "Id: 76_19 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_62', '75_42'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_19', 'origin': '75_62~CUW~75_42#MGNP'} Metrics: ['ELUC: -4.10913510379428', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09457430805677383', 'is_elite: False']\n", + "Id: 75_42 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_40', '74_57'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_42', 'origin': '74_40~CUW~74_57#MGNP'} Metrics: ['ELUC: -4.237649712299562', 'NSGA-II_crowding_distance: 0.17743940243545842', 'NSGA-II_rank: 2', 'change: 0.07597848638455729', 'is_elite: False']\n", + "Id: 76_95 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_95', 'origin': '75_62~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.252146892223708', 'NSGA-II_crowding_distance: 0.8838090378006184', 'NSGA-II_rank: 8', 'change: 0.256845788466241', 'is_elite: False']\n", + "Id: 76_69 Identity: {'ancestor_count': 74, 'ancestor_ids': ['71_50', '75_74'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_69', 'origin': '71_50~CUW~75_74#MGNP'} Metrics: ['ELUC: -4.589116691469706', 'NSGA-II_crowding_distance: 1.2829618117852928', 'NSGA-II_rank: 4', 'change: 0.0885218613096381', 'is_elite: False']\n", + "Id: 76_100 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '75_42'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_100', 'origin': '75_74~CUW~75_42#MGNP'} Metrics: ['ELUC: -4.776196103429231', 'NSGA-II_crowding_distance: 0.24644853183302382', 'NSGA-II_rank: 1', 'change: 0.06941341746745261', 'is_elite: True']\n", + "Id: 76_20 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_81', '71_50'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_20', 'origin': '75_81~CUW~71_50#MGNP'} Metrics: ['ELUC: -5.707891972551476', 'NSGA-II_crowding_distance: 0.12832647994827212', 'NSGA-II_rank: 2', 'change: 0.08461522232623062', 'is_elite: False']\n", + "Id: 76_17 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '75_40'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_17', 'origin': '75_74~CUW~75_40#MGNP'} Metrics: ['ELUC: -5.733272120606616', 'NSGA-II_crowding_distance: 0.24329929885138377', 'NSGA-II_rank: 3', 'change: 0.08751960159803299', 'is_elite: False']\n", + "Id: 76_42 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '68_68'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_42', 'origin': '75_62~CUW~68_68#MGNP'} Metrics: ['ELUC: -5.810523900320607', 'NSGA-II_crowding_distance: 0.2234616009693101', 'NSGA-II_rank: 3', 'change: 0.0901748211226973', 'is_elite: False']\n", + "Id: 76_49 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_68', '75_81'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_49', 'origin': '75_68~CUW~75_81#MGNP'} Metrics: ['ELUC: -5.918840157592022', 'NSGA-II_crowding_distance: 0.15369073171634984', 'NSGA-II_rank: 2', 'change: 0.08642143330205623', 'is_elite: False']\n", + "Id: 76_82 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '1_1'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_82', 'origin': '74_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.299169260508134', 'NSGA-II_crowding_distance: 0.22535954309931697', 'NSGA-II_rank: 2', 'change: 0.11849591952002808', 'is_elite: False']\n", + "Id: 75_81 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_94', '73_27'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_81', 'origin': '74_94~CUW~73_27#MGNP'} Metrics: ['ELUC: -6.335147045407135', 'NSGA-II_crowding_distance: 0.173918824036048', 'NSGA-II_rank: 1', 'change: 0.08087895321137822', 'is_elite: False']\n", + "Id: 76_44 Identity: {'ancestor_count': 74, 'ancestor_ids': ['1_1', '75_40'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_44', 'origin': '1_1~CUW~75_40#MGNP'} Metrics: ['ELUC: -6.656914956031488', 'NSGA-II_crowding_distance: 0.23796614592733653', 'NSGA-II_rank: 1', 'change: 0.08939054016400569', 'is_elite: True']\n", + "Id: 76_63 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_30', '75_74'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_63', 'origin': '75_30~CUW~75_74#MGNP'} Metrics: ['ELUC: -6.671231629704553', 'NSGA-II_crowding_distance: 0.5570872223054397', 'NSGA-II_rank: 3', 'change: 0.13268565092038154', 'is_elite: False']\n", + "Id: 76_11 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_11', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_11', 'origin': '75_11~CUW~75_27#MGNP'} Metrics: ['ELUC: -6.6938446366286435', 'NSGA-II_crowding_distance: 1.0596367099351536', 'NSGA-II_rank: 7', 'change: 0.21557422509559254', 'is_elite: False']\n", + "Id: 76_90 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_68', '75_74'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_90', 'origin': '75_68~CUW~75_74#MGNP'} Metrics: ['ELUC: -7.468209480611377', 'NSGA-II_crowding_distance: 0.27035945587039', 'NSGA-II_rank: 2', 'change: 0.12584633776148219', 'is_elite: False']\n", + "Id: 76_72 Identity: {'ancestor_count': 73, 'ancestor_ids': ['2_49', '75_68'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_72', 'origin': '2_49~CUW~75_68#MGNP'} Metrics: ['ELUC: -7.554636027870675', 'NSGA-II_crowding_distance: 0.48019239095766253', 'NSGA-II_rank: 7', 'change: 0.2643808691555329', 'is_elite: False']\n", + "Id: 76_56 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '75_24'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_56', 'origin': '75_62~CUW~75_24#MGNP'} Metrics: ['ELUC: -8.430452407801242', 'NSGA-II_crowding_distance: 0.2724272686190212', 'NSGA-II_rank: 1', 'change: 0.11632477022572306', 'is_elite: True']\n", + "Id: 76_98 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_45', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_98', 'origin': '75_45~CUW~74_33#MGNP'} Metrics: ['ELUC: -8.72959413972311', 'NSGA-II_crowding_distance: 1.5909775519626554', 'NSGA-II_rank: 6', 'change: 0.17529357724266575', 'is_elite: False']\n", + "Id: 76_24 Identity: {'ancestor_count': 74, 'ancestor_ids': ['2_49', '75_74'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_24', 'origin': '2_49~CUW~75_74#MGNP'} Metrics: ['ELUC: -8.758840080276176', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.28957540839657914', 'is_elite: False']\n", + "Id: 76_74 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_42', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_74', 'origin': '75_42~CUW~74_33#MGNP'} Metrics: ['ELUC: -9.137520737780703', 'NSGA-II_crowding_distance: 0.18669300211289222', 'NSGA-II_rank: 1', 'change: 0.12858012134816163', 'is_elite: False']\n", + "Id: 76_48 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_48', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.438799547934591', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2647627930915975', 'is_elite: False']\n", + "Id: 76_52 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_45', '75_62'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_52', 'origin': '75_45~CUW~75_62#MGNP'} Metrics: ['ELUC: -10.04360632146523', 'NSGA-II_crowding_distance: 0.5658236211783234', 'NSGA-II_rank: 6', 'change: 0.21271276710457837', 'is_elite: False']\n", + "Id: 76_96 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_68', '75_45'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_96', 'origin': '75_68~CUW~75_45#MGNP'} Metrics: ['ELUC: -10.053650270474416', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2294567174573959', 'is_elite: False']\n", + "Id: 76_41 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_90', '75_40'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_41', 'origin': '75_90~CUW~75_40#MGNP'} Metrics: ['ELUC: -10.269454301226666', 'NSGA-II_crowding_distance: 0.24699760452354294', 'NSGA-II_rank: 2', 'change: 0.1340599534804071', 'is_elite: False']\n", + "Id: 76_79 Identity: {'ancestor_count': 72, 'ancestor_ids': ['71_50', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_79', 'origin': '71_50~CUW~74_33#MGNP'} Metrics: ['ELUC: -10.547297576894236', 'NSGA-II_crowding_distance: 0.199036416380223', 'NSGA-II_rank: 2', 'change: 0.14830295554271844', 'is_elite: False']\n", + "Id: 76_77 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_30', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_77', 'origin': '75_30~CUW~74_33#MGNP'} Metrics: ['ELUC: -10.69275202479392', 'NSGA-II_crowding_distance: 0.22532550260535794', 'NSGA-II_rank: 1', 'change: 0.13363787981721081', 'is_elite: True']\n", + "Id: 76_94 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_68', '75_81'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_94', 'origin': '75_68~CUW~75_81#MGNP'} Metrics: ['ELUC: -11.137371487360506', 'NSGA-II_crowding_distance: 1.8950589598227152', 'NSGA-II_rank: 5', 'change: 0.17235259404516334', 'is_elite: False']\n", + "Id: 76_54 Identity: {'ancestor_count': 73, 'ancestor_ids': ['71_50', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_54', 'origin': '71_50~CUW~75_100#MGNP'} Metrics: ['ELUC: -11.16319781800226', 'NSGA-II_crowding_distance: 0.6373236782759678', 'NSGA-II_rank: 5', 'change: 0.27250780192486385', 'is_elite: False']\n", + "Id: 76_78 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_27', '75_42'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_78', 'origin': '75_27~CUW~75_42#MGNP'} Metrics: ['ELUC: -11.224004311997092', 'NSGA-II_crowding_distance: 1.2001876789340247', 'NSGA-II_rank: 4', 'change: 0.1677552862052222', 'is_elite: False']\n", + "Id: 76_84 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_11', '75_45'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_84', 'origin': '75_11~CUW~75_45#MGNP'} Metrics: ['ELUC: -11.318359531390321', 'NSGA-II_crowding_distance: 0.4283558863254532', 'NSGA-II_rank: 4', 'change: 0.24461840975684998', 'is_elite: False']\n", + "Id: 76_75 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_27', '1_1'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_75', 'origin': '75_27~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.409592470219582', 'NSGA-II_crowding_distance: 0.4085916592798987', 'NSGA-II_rank: 3', 'change: 0.15810014836390981', 'is_elite: False']\n", + "Id: 76_50 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_45', '75_42'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_50', 'origin': '75_45~CUW~75_42#MGNP'} Metrics: ['ELUC: -11.480035857385838', 'NSGA-II_crowding_distance: 0.26294022050858445', 'NSGA-II_rank: 4', 'change: 0.25363880926784743', 'is_elite: False']\n", + "Id: 76_60 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_60', 'origin': '75_62~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.49207392782531', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28394495991075763', 'is_elite: False']\n", + "Id: 76_61 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '75_62'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_61', 'origin': '75_62~CUW~75_62#MGNP'} Metrics: ['ELUC: -11.826335382449034', 'NSGA-II_crowding_distance: 0.15045401274052317', 'NSGA-II_rank: 1', 'change: 0.15018221667922643', 'is_elite: False']\n", + "Id: 76_91 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_62', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_91', 'origin': '75_62~CUW~75_27#MGNP'} Metrics: ['ELUC: -12.25927987074819', 'NSGA-II_crowding_distance: 0.08883583876538832', 'NSGA-II_rank: 3', 'change: 0.16220871008647125', 'is_elite: False']\n", + "Id: 76_25 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_33', '75_24'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_25', 'origin': '74_33~CUW~75_24#MGNP'} Metrics: ['ELUC: -12.356055372871507', 'NSGA-II_crowding_distance: 0.07753294369884028', 'NSGA-II_rank: 1', 'change: 0.15030323386346642', 'is_elite: False']\n", + "Id: 76_28 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_23', '75_81'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_28', 'origin': '75_23~CUW~75_81#MGNP'} Metrics: ['ELUC: -12.430606683895238', 'NSGA-II_crowding_distance: 0.4636221300011672', 'NSGA-II_rank: 3', 'change: 0.16717603117584437', 'is_elite: False']\n", + "Id: 76_97 Identity: {'ancestor_count': 72, 'ancestor_ids': ['74_33', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_97', 'origin': '74_33~CUW~74_33#MGNP'} Metrics: ['ELUC: -12.449865187553913', 'NSGA-II_crowding_distance: 0.3742728676735065', 'NSGA-II_rank: 2', 'change: 0.15667644373700826', 'is_elite: False']\n", + "Id: 76_62 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_81', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_62', 'origin': '75_81~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.512819458026415', 'NSGA-II_crowding_distance: 0.2886823018892539', 'NSGA-II_rank: 4', 'change: 0.28275084709499326', 'is_elite: False']\n", + "Id: 76_59 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '75_68'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_59', 'origin': '75_62~CUW~75_68#MGNP'} Metrics: ['ELUC: -12.815653689878404', 'NSGA-II_crowding_distance: 0.087591780173181', 'NSGA-II_rank: 1', 'change: 0.15652728265551866', 'is_elite: False']\n", + "Id: 76_71 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_24', '75_81'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_71', 'origin': '75_24~CUW~75_81#MGNP'} Metrics: ['ELUC: -12.978970102987956', 'NSGA-II_crowding_distance: 0.06509258792902456', 'NSGA-II_rank: 1', 'change: 0.16586761409702086', 'is_elite: False']\n", + "Id: 76_34 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_81', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_34', 'origin': '75_81~CUW~75_27#MGNP'} Metrics: ['ELUC: -13.145809542497851', 'NSGA-II_crowding_distance: 0.4932597859453002', 'NSGA-II_rank: 2', 'change: 0.21339813823052875', 'is_elite: False']\n", + "Id: 76_30 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_42', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_30', 'origin': '75_42~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.152197495493123', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.29043158441238576', 'is_elite: False']\n", + "Id: 74_33 Identity: {'ancestor_count': 71, 'ancestor_ids': ['72_32', '72_34'], 'birth_generation': 74, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '74_33', 'origin': '72_32~CUW~72_34#MGNP'} Metrics: ['ELUC: -13.207569208678171', 'NSGA-II_crowding_distance: 0.06568904138286576', 'NSGA-II_rank: 1', 'change: 0.16929853313459975', 'is_elite: False']\n", + "Id: 76_73 Identity: {'ancestor_count': 73, 'ancestor_ids': ['1_1', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_73', 'origin': '1_1~CUW~75_100#MGNP'} Metrics: ['ELUC: -13.325200061903173', 'NSGA-II_crowding_distance: 0.5010735160147297', 'NSGA-II_rank: 3', 'change: 0.26797348430547535', 'is_elite: False']\n", + "Id: 76_66 Identity: {'ancestor_count': 74, 'ancestor_ids': ['74_33', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_66', 'origin': '74_33~CUW~75_27#MGNP'} Metrics: ['ELUC: -13.331230834587755', 'NSGA-II_crowding_distance: 0.10990604728832323', 'NSGA-II_rank: 1', 'change: 0.17948978695350237', 'is_elite: False']\n", + "Id: 76_21 Identity: {'ancestor_count': 74, 'ancestor_ids': ['74_33', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_21', 'origin': '74_33~CUW~75_27#MGNP'} Metrics: ['ELUC: -13.843812538004462', 'NSGA-II_crowding_distance: 0.13346589879569828', 'NSGA-II_rank: 1', 'change: 0.1912948029518374', 'is_elite: False']\n", + "Id: 76_32 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_27', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_32', 'origin': '75_27~CUW~75_27#MGNP'} Metrics: ['ELUC: -13.854954895220978', 'NSGA-II_crowding_distance: 0.0925306038292394', 'NSGA-II_rank: 1', 'change: 0.21042527807901396', 'is_elite: False']\n", + "Id: 76_57 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_27', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_57', 'origin': '75_27~CUW~75_100#MGNP'} Metrics: ['ELUC: -14.009786873605261', 'NSGA-II_crowding_distance: 0.3595571409636441', 'NSGA-II_rank: 3', 'change: 0.2756323410243779', 'is_elite: False']\n", + "Id: 75_27 Identity: {'ancestor_count': 73, 'ancestor_ids': ['74_12', '68_68'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_27', 'origin': '74_12~CUW~68_68#MGNP'} Metrics: ['ELUC: -14.20664053760566', 'NSGA-II_crowding_distance: 0.15146568880327832', 'NSGA-II_rank: 1', 'change: 0.21274657006678627', 'is_elite: False']\n", + "Id: 76_26 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_30', '75_68'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_26', 'origin': '75_30~CUW~75_68#MGNP'} Metrics: ['ELUC: -14.945560972483408', 'NSGA-II_crowding_distance: 0.1996814629516464', 'NSGA-II_rank: 1', 'change: 0.23711134288917363', 'is_elite: True']\n", + "Id: 76_51 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '75_68'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_51', 'origin': '75_74~CUW~75_68#MGNP'} Metrics: ['ELUC: -15.269365738779626', 'NSGA-II_crowding_distance: 0.4147294840125425', 'NSGA-II_rank: 2', 'change: 0.2515603633694792', 'is_elite: False']\n", + "Id: 76_43 Identity: {'ancestor_count': 74, 'ancestor_ids': ['2_49', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_43', 'origin': '2_49~CUW~75_27#MGNP'} Metrics: ['ELUC: -15.725308653625408', 'NSGA-II_crowding_distance: 0.3106603541547921', 'NSGA-II_rank: 2', 'change: 0.2900367065527157', 'is_elite: False']\n", + "Id: 76_14 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_68', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_14', 'origin': '75_68~CUW~74_33#MGNP'} Metrics: ['ELUC: -15.734787458826037', 'NSGA-II_crowding_distance: 0.20168019586083946', 'NSGA-II_rank: 1', 'change: 0.24639394440606752', 'is_elite: True']\n", + "Id: 75_45 Identity: {'ancestor_count': 73, 'ancestor_ids': ['73_25', '74_41'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_45', 'origin': '73_25~CUW~74_41#MGNP'} Metrics: ['ELUC: -16.27048880984466', 'NSGA-II_crowding_distance: 0.1678010940143417', 'NSGA-II_rank: 1', 'change: 0.2748037850642168', 'is_elite: False']\n", + "Id: 76_13 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_11', '75_23'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_13', 'origin': '75_11~CUW~75_23#MGNP'} Metrics: ['ELUC: -16.720117982881646', 'NSGA-II_crowding_distance: 0.07120709714531492', 'NSGA-II_rank: 1', 'change: 0.279740688666917', 'is_elite: False']\n", + "Id: 76_40 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_23', '75_11'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_40', 'origin': '75_23~CUW~75_11#MGNP'} Metrics: ['ELUC: -16.9284488871604', 'NSGA-II_crowding_distance: 0.04419847541751798', 'NSGA-II_rank: 1', 'change: 0.28488461068337323', 'is_elite: False']\n", + "Id: 76_68 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '75_45'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_68', 'origin': '75_74~CUW~75_45#MGNP'} Metrics: ['ELUC: -17.05063394355699', 'NSGA-II_crowding_distance: 0.03848341884373037', 'NSGA-II_rank: 1', 'change: 0.28731957103370764', 'is_elite: False']\n", + "Id: 76_29 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_42', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_29', 'origin': '75_42~CUW~75_100#MGNP'} Metrics: ['ELUC: -17.130460862763343', 'NSGA-II_crowding_distance: 0.06978078974040794', 'NSGA-II_rank: 1', 'change: 0.29293899975964', 'is_elite: False']\n", + "Id: 76_85 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_11', '75_45'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_85', 'origin': '75_11~CUW~75_45#MGNP'} Metrics: ['ELUC: -17.50708926627571', 'NSGA-II_crowding_distance: 0.05446350567450625', 'NSGA-II_rank: 1', 'change: 0.3003944160921911', 'is_elite: False']\n", + "Id: 76_36 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_36', 'origin': '75_62~CUW~75_100#MGNP'} Metrics: ['ELUC: -17.519245071663438', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3038641543174045', 'is_elite: False']\n", + "Id: 76_80 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_100', '71_50'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_80', 'origin': '75_100~CUW~71_50#MGNP'} Metrics: ['ELUC: -17.558771956307766', 'NSGA-II_crowding_distance: 0.013932214097335655', 'NSGA-II_rank: 1', 'change: 0.3019211248503752', 'is_elite: False']\n", + "Id: 76_38 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_45', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_38', 'origin': '75_45~CUW~75_100#MGNP'} Metrics: ['ELUC: -17.597342916491048', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030201603717027', 'is_elite: False']\n", + "Id: 76_16 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_16', 'origin': '75_62~CUW~75_100#MGNP'} Metrics: ['ELUC: -17.597358463770995', 'NSGA-II_crowding_distance: 0.005880612539051861', 'NSGA-II_rank: 1', 'change: 0.30301958219114783', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 75_100 Identity: {'ancestor_count': 72, 'ancestor_ids': ['2_49', '73_25'], 'birth_generation': 75, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '75_100', 'origin': '2_49~CUW~73_25#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 76_27 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_27', 'origin': '75_74~CUW~75_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 76_47 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_47', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 76_58 Identity: {'ancestor_count': 73, 'ancestor_ids': ['1_1', '75_100'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_58', 'origin': '1_1~CUW~75_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 76_76 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_100', '2_49'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_76', 'origin': '75_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 76_87 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_100', '75_40'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_87', 'origin': '75_100~CUW~75_40#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 76_99 Identity: {'ancestor_count': 74, 'ancestor_ids': ['2_49', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_99', 'origin': '2_49~CUW~75_27#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 76.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 77...:\n", + "PopulationResponse:\n", + " Generation: 77\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/77/20240220-045709\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 77 and asking ESP for generation 78...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 77 data persisted.\n", + "Evaluated candidates:\n", + "Id: 77_46 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_56', '76_99'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_46', 'origin': '76_56~CUW~76_99#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 77_29 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_26', '76_99'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_29', 'origin': '76_26~CUW~76_99#MGNP'} Metrics: ['ELUC: 10.5213250152206', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2770356671506128', 'is_elite: False']\n", + "Id: 77_39 Identity: {'ancestor_count': 75, 'ancestor_ids': ['2_49', '76_65'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_39', 'origin': '2_49~CUW~76_65#MGNP'} Metrics: ['ELUC: 7.961581354984573', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27040027762419233', 'is_elite: False']\n", + "Id: 77_78 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_78', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 6.228532585452912', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.26216964684441235', 'is_elite: False']\n", + "Id: 77_53 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_53', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.100469161853449', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.22366194539690734', 'is_elite: False']\n", + "Id: 77_42 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_100', '2_49'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_42', 'origin': '76_100~CUW~2_49#MGNP'} Metrics: ['ELUC: 3.216806427388498', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.26783584176629077', 'is_elite: False']\n", + "Id: 77_40 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_81', '76_61'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_40', 'origin': '75_81~CUW~76_61#MGNP'} Metrics: ['ELUC: 2.9325198232911367', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.10604973457395091', 'is_elite: False']\n", + "Id: 77_43 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '76_92'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_43', 'origin': '1_1~CUW~76_92#MGNP'} Metrics: ['ELUC: 2.601043521633844', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.0624201925006763', 'is_elite: False']\n", + "Id: 77_71 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_99', '76_14'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_71', 'origin': '76_99~CUW~76_14#MGNP'} Metrics: ['ELUC: 1.8797596671380299', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.34761575103865966', 'is_elite: False']\n", + "Id: 77_14 Identity: {'ancestor_count': 75, 'ancestor_ids': ['1_1', '76_100'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_14', 'origin': '1_1~CUW~76_100#MGNP'} Metrics: ['ELUC: 1.2170279189623256', 'NSGA-II_crowding_distance: 0.20496437859161099', 'NSGA-II_rank: 4', 'change: 0.06275633991328253', 'is_elite: False']\n", + "Id: 77_23 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_65', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_23', 'origin': '76_65~CUW~76_77#MGNP'} Metrics: ['ELUC: 1.1055323909601822', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.09711652942444347', 'is_elite: False']\n", + "Id: 77_51 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_51', 'origin': '76_77~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.0727694755933022', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06237867957550174', 'is_elite: False']\n", + "Id: 77_66 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_74', '76_44'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_66', 'origin': '76_74~CUW~76_44#MGNP'} Metrics: ['ELUC: 0.9730346535801829', 'NSGA-II_crowding_distance: 0.4494346806196158', 'NSGA-II_rank: 4', 'change: 0.08236999883199599', 'is_elite: False']\n", + "Id: 77_62 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_62', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.9415006670840075', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.026874901399333292', 'is_elite: False']\n", + "Id: 77_73 Identity: {'ancestor_count': 74, 'ancestor_ids': ['1_1', '76_56'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_73', 'origin': '1_1~CUW~76_56#MGNP'} Metrics: ['ELUC: 0.6296265579514458', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08452690650013285', 'is_elite: False']\n", + "Id: 77_27 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_21', '2_49'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_27', 'origin': '76_21~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.07438910342139637', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2613927621350819', 'is_elite: False']\n", + "Id: 77_59 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_59', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.026271882773201784', 'NSGA-II_crowding_distance: 0.25125844593949287', 'NSGA-II_rank: 2', 'change: 0.046125620298516114', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 77_64 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_65', '75_27'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_64', 'origin': '76_65~CUW~75_27#MGNP'} Metrics: ['ELUC: -0.270107779415021', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.09426196214246431', 'is_elite: False']\n", + "Id: 77_44 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_44', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.45079096353431003', 'NSGA-II_crowding_distance: 0.164399398078293', 'NSGA-II_rank: 1', 'change: 0.03240658063170547', 'is_elite: False']\n", + "Id: 77_86 Identity: {'ancestor_count': 71, 'ancestor_ids': ['76_92', '2_49'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_86', 'origin': '76_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 77_20 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_99', '76_65'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_20', 'origin': '76_99~CUW~76_65#MGNP'} Metrics: ['ELUC: -0.5793262203198647', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.267854582983668', 'is_elite: False']\n", + "Id: 77_11 Identity: {'ancestor_count': 71, 'ancestor_ids': ['1_1', '76_92'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_11', 'origin': '1_1~CUW~76_92#MGNP'} Metrics: ['ELUC: -0.6857750350233771', 'NSGA-II_crowding_distance: 0.09799070839503843', 'NSGA-II_rank: 1', 'change: 0.042313413945383675', 'is_elite: False']\n", + "Id: 77_82 Identity: {'ancestor_count': 75, 'ancestor_ids': ['2_49', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_82', 'origin': '2_49~CUW~76_77#MGNP'} Metrics: ['ELUC: -0.7451373566725985', 'NSGA-II_crowding_distance: 1.5794453450589039', 'NSGA-II_rank: 7', 'change: 0.22323694998813406', 'is_elite: False']\n", + "Id: 77_68 Identity: {'ancestor_count': 75, 'ancestor_ids': ['1_1', '76_100'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_68', 'origin': '1_1~CUW~76_100#MGNP'} Metrics: ['ELUC: -1.0130182969913861', 'NSGA-II_crowding_distance: 0.22198760744783963', 'NSGA-II_rank: 2', 'change: 0.05624201462471802', 'is_elite: False']\n", + "Id: 77_18 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_65', '76_37'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_18', 'origin': '76_65~CUW~76_37#MGNP'} Metrics: ['ELUC: -1.147230513087965', 'NSGA-II_crowding_distance: 0.08266594375078679', 'NSGA-II_rank: 1', 'change: 0.04982603045619024', 'is_elite: False']\n", + "Id: 77_75 Identity: {'ancestor_count': 71, 'ancestor_ids': ['76_92', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_75', 'origin': '76_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2098870963273631', 'NSGA-II_crowding_distance: 0.16947577102564068', 'NSGA-II_rank: 1', 'change: 0.05808474610340236', 'is_elite: True']\n", + "Id: 77_48 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_92', '76_100'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_48', 'origin': '76_92~CUW~76_100#MGNP'} Metrics: ['ELUC: -1.7900693564388659', 'NSGA-II_crowding_distance: 0.23647258345920272', 'NSGA-II_rank: 3', 'change: 0.06615425991820531', 'is_elite: False']\n", + "Id: 77_79 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_56', '76_37'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_79', 'origin': '76_56~CUW~76_37#MGNP'} Metrics: ['ELUC: -2.08306503579424', 'NSGA-II_crowding_distance: 0.054541915819599884', 'NSGA-II_rank: 3', 'change: 0.06670225338882191', 'is_elite: False']\n", + "Id: 77_96 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_65', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_96', 'origin': '76_65~CUW~76_77#MGNP'} Metrics: ['ELUC: -2.3403166887401383', 'NSGA-II_crowding_distance: 0.07948922681296018', 'NSGA-II_rank: 3', 'change: 0.06994669955326852', 'is_elite: False']\n", + "Id: 77_80 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_74', '76_44'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_80', 'origin': '76_74~CUW~76_44#MGNP'} Metrics: ['ELUC: -2.37652393890684', 'NSGA-II_crowding_distance: 0.12563780531398688', 'NSGA-II_rank: 2', 'change: 0.06278069817319072', 'is_elite: False']\n", + "Id: 77_95 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_92', '76_74'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_95', 'origin': '76_92~CUW~76_74#MGNP'} Metrics: ['ELUC: -2.4314886801222775', 'NSGA-II_crowding_distance: 0.04614686527408194', 'NSGA-II_rank: 2', 'change: 0.06486329800953121', 'is_elite: False']\n", + "Id: 77_84 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_56', '76_65'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_84', 'origin': '76_56~CUW~76_65#MGNP'} Metrics: ['ELUC: -2.7199484055910434', 'NSGA-II_crowding_distance: 0.5325237487276261', 'NSGA-II_rank: 5', 'change: 0.0924607432051045', 'is_elite: False']\n", + "Id: 76_65 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_42', '75_42'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_65', 'origin': '75_42~CUW~75_42#MGNP'} Metrics: ['ELUC: -2.815174771598541', 'NSGA-II_crowding_distance: 0.1644276148413605', 'NSGA-II_rank: 2', 'change: 0.06707921780129368', 'is_elite: False']\n", + "Id: 77_41 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_65', '76_100'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_41', 'origin': '76_65~CUW~76_100#MGNP'} Metrics: ['ELUC: -2.8431844954131815', 'NSGA-II_crowding_distance: 0.13448558098662625', 'NSGA-II_rank: 3', 'change: 0.07288722833100275', 'is_elite: False']\n", + "Id: 77_28 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_28', 'origin': '76_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.515599218727335', 'NSGA-II_crowding_distance: 0.24080228105287454', 'NSGA-II_rank: 1', 'change: 0.060201876866619694', 'is_elite: True']\n", + "Id: 77_70 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_56', '76_44'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_70', 'origin': '76_56~CUW~76_44#MGNP'} Metrics: ['ELUC: -3.816599538476146', 'NSGA-II_crowding_distance: 0.39012528537771995', 'NSGA-II_rank: 4', 'change: 0.08330265379567171', 'is_elite: False']\n", + "Id: 77_21 Identity: {'ancestor_count': 74, 'ancestor_ids': ['76_56', '75_81'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_21', 'origin': '76_56~CUW~75_81#MGNP'} Metrics: ['ELUC: -3.8879373137076243', 'NSGA-II_crowding_distance: 0.09719144784589748', 'NSGA-II_rank: 3', 'change: 0.0762945836432448', 'is_elite: False']\n", + "Id: 77_50 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_37', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_50', 'origin': '76_37~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.9593872389399745', 'NSGA-II_crowding_distance: 0.48578129685975535', 'NSGA-II_rank: 5', 'change: 0.09968397683361119', 'is_elite: False']\n", + "Id: 77_38 Identity: {'ancestor_count': 75, 'ancestor_ids': ['75_81', '76_37'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_38', 'origin': '75_81~CUW~76_37#MGNP'} Metrics: ['ELUC: -4.0142429637902035', 'NSGA-II_crowding_distance: 0.04991854353273345', 'NSGA-II_rank: 3', 'change: 0.07664698233259326', 'is_elite: False']\n", + "Id: 77_52 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_37', '75_81'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_52', 'origin': '76_37~CUW~75_81#MGNP'} Metrics: ['ELUC: -4.25897471884044', 'NSGA-II_crowding_distance: 0.3143979635626368', 'NSGA-II_rank: 4', 'change: 0.08653382341596304', 'is_elite: False']\n", + "Id: 77_56 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_92', '76_100'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_56', 'origin': '76_92~CUW~76_100#MGNP'} Metrics: ['ELUC: -4.4761985875239745', 'NSGA-II_crowding_distance: 0.09421253975732877', 'NSGA-II_rank: 3', 'change: 0.0784334428503943', 'is_elite: False']\n", + "Id: 77_26 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_65', '76_100'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_26', 'origin': '76_65~CUW~76_100#MGNP'} Metrics: ['ELUC: -4.645355513810477', 'NSGA-II_crowding_distance: 0.2029490710324503', 'NSGA-II_rank: 2', 'change: 0.07123334806400705', 'is_elite: False']\n", + "Id: 76_100 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_74', '75_42'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_100', 'origin': '75_74~CUW~75_42#MGNP'} Metrics: ['ELUC: -4.776196103429231', 'NSGA-II_crowding_distance: 0.11716055849821971', 'NSGA-II_rank: 1', 'change: 0.06941341746745261', 'is_elite: False']\n", + "Id: 77_85 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_100', '76_44'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_85', 'origin': '76_100~CUW~76_44#MGNP'} Metrics: ['ELUC: -4.78213184522579', 'NSGA-II_crowding_distance: 0.20622444164197015', 'NSGA-II_rank: 3', 'change: 0.0860707241138098', 'is_elite: False']\n", + "Id: 77_72 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '71_50'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_72', 'origin': '76_77~CUW~71_50#MGNP'} Metrics: ['ELUC: -4.824623917518303', 'NSGA-II_crowding_distance: 0.1865070826907677', 'NSGA-II_rank: 2', 'change: 0.08487985690075743', 'is_elite: False']\n", + "Id: 77_98 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_27', '76_92'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_98', 'origin': '75_27~CUW~76_92#MGNP'} Metrics: ['ELUC: -4.837225514914816', 'NSGA-II_crowding_distance: 1.548380295534916', 'NSGA-II_rank: 6', 'change: 0.13785260603270025', 'is_elite: False']\n", + "Id: 77_35 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_100', '76_44'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_35', 'origin': '76_100~CUW~76_44#MGNP'} Metrics: ['ELUC: -4.943849064653076', 'NSGA-II_crowding_distance: 0.1656857805588836', 'NSGA-II_rank: 1', 'change: 0.07092213649992865', 'is_elite: False']\n", + "Id: 77_54 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_92', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_54', 'origin': '76_92~CUW~76_77#MGNP'} Metrics: ['ELUC: -5.351472560680054', 'NSGA-II_crowding_distance: 0.23347300607393678', 'NSGA-II_rank: 3', 'change: 0.11173739490117046', 'is_elite: False']\n", + "Id: 77_88 Identity: {'ancestor_count': 75, 'ancestor_ids': ['75_81', '76_44'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_88', 'origin': '75_81~CUW~76_44#MGNP'} Metrics: ['ELUC: -5.765302044704815', 'NSGA-II_crowding_distance: 0.30407136467039125', 'NSGA-II_rank: 2', 'change: 0.09758003023941539', 'is_elite: False']\n", + "Id: 77_94 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_56', '76_37'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_94', 'origin': '76_56~CUW~76_37#MGNP'} Metrics: ['ELUC: -5.914505448128677', 'NSGA-II_crowding_distance: 0.5225335793741583', 'NSGA-II_rank: 5', 'change: 0.12262296264980525', 'is_elite: False']\n", + "Id: 77_74 Identity: {'ancestor_count': 74, 'ancestor_ids': ['2_49', '76_14'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_74', 'origin': '2_49~CUW~76_14#MGNP'} Metrics: ['ELUC: -5.932957614186841', 'NSGA-II_crowding_distance: 0.9966384178582419', 'NSGA-II_rank: 7', 'change: 0.27123461416880446', 'is_elite: False']\n", + "Id: 77_36 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '76_99'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_36', 'origin': '76_77~CUW~76_99#MGNP'} Metrics: ['ELUC: -5.973306508577521', 'NSGA-II_crowding_distance: 1.269962098081834', 'NSGA-II_rank: 6', 'change: 0.2619265166938606', 'is_elite: False']\n", + "Id: 77_91 Identity: {'ancestor_count': 74, 'ancestor_ids': ['76_56', '75_45'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_91', 'origin': '76_56~CUW~75_45#MGNP'} Metrics: ['ELUC: -6.150548222509118', 'NSGA-II_crowding_distance: 0.9985073815935259', 'NSGA-II_rank: 5', 'change: 0.15263846298342074', 'is_elite: False']\n", + "Id: 77_90 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_74', '76_100'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_90', 'origin': '76_74~CUW~76_100#MGNP'} Metrics: ['ELUC: -6.2710145370103065', 'NSGA-II_crowding_distance: 0.5176736825086306', 'NSGA-II_rank: 4', 'change: 0.11458245355776205', 'is_elite: False']\n", + "Id: 77_97 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_26', '75_81'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_97', 'origin': '76_26~CUW~75_81#MGNP'} Metrics: ['ELUC: -6.425664437736361', 'NSGA-II_crowding_distance: 0.2134913201688629', 'NSGA-II_rank: 3', 'change: 0.11350613904574292', 'is_elite: False']\n", + "Id: 77_58 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_66', '75_81'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_58', 'origin': '76_66~CUW~75_81#MGNP'} Metrics: ['ELUC: -6.562875606646197', 'NSGA-II_crowding_distance: 0.1593271127923057', 'NSGA-II_rank: 1', 'change: 0.0885298602079291', 'is_elite: False']\n", + "Id: 76_44 Identity: {'ancestor_count': 74, 'ancestor_ids': ['1_1', '75_40'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_44', 'origin': '1_1~CUW~75_40#MGNP'} Metrics: ['ELUC: -6.656914956031488', 'NSGA-II_crowding_distance: 0.15553442718433985', 'NSGA-II_rank: 1', 'change: 0.08939054016400569', 'is_elite: False']\n", + "Id: 77_45 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_99', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_45', 'origin': '76_99~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.51186701650573', 'NSGA-II_crowding_distance: 0.420554654941096', 'NSGA-II_rank: 7', 'change: 0.2844272211579739', 'is_elite: False']\n", + "Id: 77_69 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '76_56'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_69', 'origin': '76_77~CUW~76_56#MGNP'} Metrics: ['ELUC: -7.870341349566744', 'NSGA-II_crowding_distance: 0.33229958766535816', 'NSGA-II_rank: 3', 'change: 0.120837702478542', 'is_elite: False']\n", + "Id: 77_92 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '75_27'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_92', 'origin': '76_44~CUW~75_27#MGNP'} Metrics: ['ELUC: -7.908505757482655', 'NSGA-II_crowding_distance: 0.21695662035839586', 'NSGA-II_rank: 2', 'change: 0.11054388625720399', 'is_elite: False']\n", + "Id: 77_99 Identity: {'ancestor_count': 74, 'ancestor_ids': ['76_56', '76_56'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_99', 'origin': '76_56~CUW~76_56#MGNP'} Metrics: ['ELUC: -8.006834110335719', 'NSGA-II_crowding_distance: 0.07483150083271198', 'NSGA-II_rank: 2', 'change: 0.1153256676245465', 'is_elite: False']\n", + "Id: 77_57 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '76_92'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_57', 'origin': '76_44~CUW~76_92#MGNP'} Metrics: ['ELUC: -8.159665067081825', 'NSGA-II_crowding_distance: 0.1911392990101159', 'NSGA-II_rank: 1', 'change: 0.10783985787472226', 'is_elite: True']\n", + "Id: 77_81 Identity: {'ancestor_count': 75, 'ancestor_ids': ['1_1', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_81', 'origin': '1_1~CUW~76_77#MGNP'} Metrics: ['ELUC: -8.332128549313506', 'NSGA-II_crowding_distance: 0.13740296660944917', 'NSGA-II_rank: 2', 'change: 0.12146849122750318', 'is_elite: False']\n", + "Id: 76_56 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_62', '75_24'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_56', 'origin': '75_62~CUW~75_24#MGNP'} Metrics: ['ELUC: -8.430452407801242', 'NSGA-II_crowding_distance: 0.07220614044261314', 'NSGA-II_rank: 1', 'change: 0.11632477022572306', 'is_elite: False']\n", + "Id: 77_65 Identity: {'ancestor_count': 75, 'ancestor_ids': ['1_1', '76_26'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_65', 'origin': '1_1~CUW~76_26#MGNP'} Metrics: ['ELUC: -8.492690647417769', 'NSGA-II_crowding_distance: 0.49281045024860837', 'NSGA-II_rank: 4', 'change: 0.13498883154287492', 'is_elite: False']\n", + "Id: 77_25 Identity: {'ancestor_count': 74, 'ancestor_ids': ['71_50', '76_56'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_25', 'origin': '71_50~CUW~76_56#MGNP'} Metrics: ['ELUC: -8.55148337049773', 'NSGA-II_crowding_distance: 0.05295248485775632', 'NSGA-II_rank: 1', 'change: 0.12273528366890146', 'is_elite: False']\n", + "Id: 77_19 Identity: {'ancestor_count': 73, 'ancestor_ids': ['2_49', '75_81'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_19', 'origin': '2_49~CUW~75_81#MGNP'} Metrics: ['ELUC: -8.616940934685168', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.30064318364635156', 'is_elite: False']\n", + "Id: 77_30 Identity: {'ancestor_count': 74, 'ancestor_ids': ['76_56', '76_14'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_30', 'origin': '76_56~CUW~76_14#MGNP'} Metrics: ['ELUC: -8.954870732783904', 'NSGA-II_crowding_distance: 0.03159836687956169', 'NSGA-II_rank: 1', 'change: 0.12322507104412199', 'is_elite: False']\n", + "Id: 77_13 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_56', '76_44'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_13', 'origin': '76_56~CUW~76_44#MGNP'} Metrics: ['ELUC: -9.062228213913482', 'NSGA-II_crowding_distance: 0.10189750882052415', 'NSGA-II_rank: 1', 'change: 0.12349603476843769', 'is_elite: False']\n", + "Id: 77_34 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_14', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_34', 'origin': '76_14~CUW~76_77#MGNP'} Metrics: ['ELUC: -9.280799227309998', 'NSGA-II_crowding_distance: 0.10448471516566109', 'NSGA-II_rank: 2', 'change: 0.12856610104576066', 'is_elite: False']\n", + "Id: 77_89 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_56', '76_26'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_89', 'origin': '76_56~CUW~76_26#MGNP'} Metrics: ['ELUC: -9.494711028629226', 'NSGA-II_crowding_distance: 0.06285072256461254', 'NSGA-II_rank: 2', 'change: 0.12887281223654634', 'is_elite: False']\n", + "Id: 77_76 Identity: {'ancestor_count': 75, 'ancestor_ids': ['75_45', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_76', 'origin': '75_45~CUW~76_77#MGNP'} Metrics: ['ELUC: -9.581620318184457', 'NSGA-II_crowding_distance: 0.9449426718982157', 'NSGA-II_rank: 5', 'change: 0.23237890745640832', 'is_elite: False']\n", + "Id: 77_15 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '2_49'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_15', 'origin': '76_77~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.688607410750869', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2720895896016699', 'is_elite: False']\n", + "Id: 77_31 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_99', '76_74'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_31', 'origin': '76_99~CUW~76_74#MGNP'} Metrics: ['ELUC: -9.715691294005435', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.25494575719909857', 'is_elite: False']\n", + "Id: 77_100 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_100', '76_26'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_100', 'origin': '76_100~CUW~76_26#MGNP'} Metrics: ['ELUC: -9.897593565574457', 'NSGA-II_crowding_distance: 0.8872366535220385', 'NSGA-II_rank: 4', 'change: 0.1671095788067172', 'is_elite: False']\n", + "Id: 77_37 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '76_92'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_37', 'origin': '76_77~CUW~76_92#MGNP'} Metrics: ['ELUC: -9.916515700690915', 'NSGA-II_crowding_distance: 0.9907169508029925', 'NSGA-II_rank: 3', 'change: 0.13443339187592696', 'is_elite: False']\n", + "Id: 77_87 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_14', '76_74'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_87', 'origin': '76_14~CUW~76_74#MGNP'} Metrics: ['ELUC: -9.991533863643818', 'NSGA-II_crowding_distance: 0.09486931883571152', 'NSGA-II_rank: 2', 'change: 0.13286325491682388', 'is_elite: False']\n", + "Id: 77_83 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_61', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_83', 'origin': '76_61~CUW~76_77#MGNP'} Metrics: ['ELUC: -10.527710780807437', 'NSGA-II_crowding_distance: 0.12452329036280713', 'NSGA-II_rank: 1', 'change: 0.1269374365125923', 'is_elite: False']\n", + "Id: 76_77 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_30', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_77', 'origin': '75_30~CUW~74_33#MGNP'} Metrics: ['ELUC: -10.69275202479392', 'NSGA-II_crowding_distance: 0.4179237125930947', 'NSGA-II_rank: 2', 'change: 0.13363787981721081', 'is_elite: False']\n", + "Id: 77_32 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_32', 'origin': '76_77~CUW~76_77#MGNP'} Metrics: ['ELUC: -10.752236721636885', 'NSGA-II_crowding_distance: 0.06896864441929734', 'NSGA-II_rank: 1', 'change: 0.13197104435073442', 'is_elite: False']\n", + "Id: 77_93 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '76_56'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_93', 'origin': '76_77~CUW~76_56#MGNP'} Metrics: ['ELUC: -11.114690782214405', 'NSGA-II_crowding_distance: 0.30689103595249945', 'NSGA-II_rank: 1', 'change: 0.1375549114855765', 'is_elite: True']\n", + "Id: 77_77 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '2_49'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_77', 'origin': '76_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.483522028359896', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2856317391058036', 'is_elite: False']\n", + "Id: 77_61 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_14', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_61', 'origin': '76_14~CUW~76_77#MGNP'} Metrics: ['ELUC: -11.837737167027354', 'NSGA-II_crowding_distance: 0.6724900106351169', 'NSGA-II_rank: 2', 'change: 0.20101828088983156', 'is_elite: False']\n", + "Id: 77_12 Identity: {'ancestor_count': 75, 'ancestor_ids': ['2_49', '76_26'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_12', 'origin': '2_49~CUW~76_26#MGNP'} Metrics: ['ELUC: -12.454054658178556', 'NSGA-II_crowding_distance: 0.8727229704643701', 'NSGA-II_rank: 3', 'change: 0.2748711769545264', 'is_elite: False']\n", + "Id: 77_60 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_26', '75_27'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_60', 'origin': '76_26~CUW~75_27#MGNP'} Metrics: ['ELUC: -12.594906437860352', 'NSGA-II_crowding_distance: 0.3784494039195557', 'NSGA-II_rank: 1', 'change: 0.19226981728387954', 'is_elite: True']\n", + "Id: 77_22 Identity: {'ancestor_count': 71, 'ancestor_ids': ['2_49', '76_92'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_22', 'origin': '2_49~CUW~76_92#MGNP'} Metrics: ['ELUC: -12.704920510618651', 'NSGA-II_crowding_distance: 0.13674549567019162', 'NSGA-II_rank: 3', 'change: 0.28978111861997985', 'is_elite: False']\n", + "Id: 77_47 Identity: {'ancestor_count': 74, 'ancestor_ids': ['2_49', '76_56'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_47', 'origin': '2_49~CUW~76_56#MGNP'} Metrics: ['ELUC: -13.434632941112008', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2906575545198763', 'is_elite: False']\n", + "Id: 77_17 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_100', '76_26'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_17', 'origin': '76_100~CUW~76_26#MGNP'} Metrics: ['ELUC: -13.676955906591639', 'NSGA-II_crowding_distance: 0.19054895730517063', 'NSGA-II_rank: 1', 'change: 0.206993350864447', 'is_elite: True']\n", + "Id: 77_24 Identity: {'ancestor_count': 75, 'ancestor_ids': ['75_27', '76_44'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_24', 'origin': '75_27~CUW~76_44#MGNP'} Metrics: ['ELUC: -14.292047631682678', 'NSGA-II_crowding_distance: 0.4370350290888397', 'NSGA-II_rank: 2', 'change: 0.234668801527431', 'is_elite: False']\n", + "Id: 77_49 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '76_26'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_49', 'origin': '76_77~CUW~76_26#MGNP'} Metrics: ['ELUC: -14.629956293124291', 'NSGA-II_crowding_distance: 0.10107948188159459', 'NSGA-II_rank: 1', 'change: 0.21458995645996787', 'is_elite: False']\n", + "Id: 77_63 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '76_14'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_63', 'origin': '76_77~CUW~76_14#MGNP'} Metrics: ['ELUC: -14.636579278075432', 'NSGA-II_crowding_distance: 0.05805145002315306', 'NSGA-II_rank: 1', 'change: 0.22086811129912154', 'is_elite: False']\n", + "Id: 77_67 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_92', '76_26'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_67', 'origin': '76_92~CUW~76_26#MGNP'} Metrics: ['ELUC: -14.647850120569371', 'NSGA-II_crowding_distance: 0.07201190010971067', 'NSGA-II_rank: 1', 'change: 0.23160755166785685', 'is_elite: False']\n", + "Id: 76_26 Identity: {'ancestor_count': 74, 'ancestor_ids': ['75_30', '75_68'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_26', 'origin': '75_30~CUW~75_68#MGNP'} Metrics: ['ELUC: -14.945560972483408', 'NSGA-II_crowding_distance: 0.11137579224847247', 'NSGA-II_rank: 1', 'change: 0.23711134288917363', 'is_elite: False']\n", + "Id: 77_33 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_26', '76_37'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_33', 'origin': '76_26~CUW~76_37#MGNP'} Metrics: ['ELUC: -15.34123157252147', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.250671833364656', 'is_elite: False']\n", + "Id: 76_14 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_68', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_14', 'origin': '75_68~CUW~74_33#MGNP'} Metrics: ['ELUC: -15.734787458826037', 'NSGA-II_crowding_distance: 0.37171483006344286', 'NSGA-II_rank: 1', 'change: 0.24639394440606752', 'is_elite: True']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 76_99 Identity: {'ancestor_count': 74, 'ancestor_ids': ['2_49', '75_27'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_99', 'origin': '2_49~CUW~75_27#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 77_16 Identity: {'ancestor_count': 75, 'ancestor_ids': ['2_49', '76_37'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_16', 'origin': '2_49~CUW~76_37#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 77_55 Identity: {'ancestor_count': 75, 'ancestor_ids': ['2_49', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_55', 'origin': '2_49~CUW~76_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 77.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 78...:\n", + "PopulationResponse:\n", + " Generation: 78\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/78/20240220-050426\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 78 and asking ESP for generation 79...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 78 data persisted.\n", + "Evaluated candidates:\n", + "Id: 78_11 Identity: {'ancestor_count': 76, 'ancestor_ids': ['1_1', '77_55'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_11', 'origin': '1_1~CUW~77_55#MGNP'} Metrics: ['ELUC: 23.74920611059065', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30378727679852957', 'is_elite: False']\n", + "Id: 78_95 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '2_49'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_95', 'origin': '77_28~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.36886722444189', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26690829969140556', 'is_elite: False']\n", + "Id: 78_14 Identity: {'ancestor_count': 74, 'ancestor_ids': ['77_75', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_14', 'origin': '77_75~CUW~76_14#MGNP'} Metrics: ['ELUC: 3.7005612270089214', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.095799452085682', 'is_elite: False']\n", + "Id: 78_39 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_83', '77_44'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_39', 'origin': '77_83~CUW~77_44#MGNP'} Metrics: ['ELUC: 3.491863501777962', 'NSGA-II_crowding_distance: 1.0219797021805073', 'NSGA-II_rank: 7', 'change: 0.09672188567973478', 'is_elite: False']\n", + "Id: 78_44 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_44', 'origin': '1_1~CUW~77_75#MGNP'} Metrics: ['ELUC: 1.026087750373508', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03493266264089093', 'is_elite: False']\n", + "Id: 78_81 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_58', '1_1'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_81', 'origin': '77_58~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.7306106236340956', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.06785450064647788', 'is_elite: False']\n", + "Id: 78_18 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_18', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.4665762095738603', 'NSGA-II_crowding_distance: 0.13787694600365305', 'NSGA-II_rank: 2', 'change: 0.040644594034134285', 'is_elite: False']\n", + "Id: 78_80 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '1_1'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_80', 'origin': '77_60~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.10665084312812691', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06658590185712555', 'is_elite: False']\n", + "Id: 78_91 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_75', '77_35'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_91', 'origin': '77_75~CUW~77_35#MGNP'} Metrics: ['ELUC: 0.06736167019625165', 'NSGA-II_crowding_distance: 0.11489412101759464', 'NSGA-II_rank: 5', 'change: 0.07114019667222124', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 78_25 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_83', '77_35'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_25', 'origin': '77_83~CUW~77_35#MGNP'} Metrics: ['ELUC: -0.08107652510948354', 'NSGA-II_crowding_distance: 0.3830673382419101', 'NSGA-II_rank: 5', 'change: 0.09100258378514553', 'is_elite: False']\n", + "Id: 78_23 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_44', '77_49'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_23', 'origin': '77_44~CUW~77_49#MGNP'} Metrics: ['ELUC: -0.08961210237632601', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.0581055520078493', 'is_elite: False']\n", + "Id: 78_21 Identity: {'ancestor_count': 76, 'ancestor_ids': ['1_1', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_21', 'origin': '1_1~CUW~77_57#MGNP'} Metrics: ['ELUC: -0.10589061684254314', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.052283308666581624', 'is_elite: False']\n", + "Id: 78_31 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '1_1'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_31', 'origin': '77_60~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.4216430853821251', 'NSGA-II_crowding_distance: 0.19006369420840036', 'NSGA-II_rank: 2', 'change: 0.05105497177347186', 'is_elite: False']\n", + "Id: 78_26 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_26', 'origin': '1_1~CUW~77_75#MGNP'} Metrics: ['ELUC: -0.4578627608522755', 'NSGA-II_crowding_distance: 0.24706534182907985', 'NSGA-II_rank: 1', 'change: 0.043817094454783156', 'is_elite: True']\n", + "Id: 78_16 Identity: {'ancestor_count': 76, 'ancestor_ids': ['2_49', '77_60'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_16', 'origin': '2_49~CUW~77_60#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 1.9791587125213694', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 78_54 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_75', '77_83'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_54', 'origin': '77_75~CUW~77_83#MGNP'} Metrics: ['ELUC: -0.6417994405471957', 'NSGA-II_crowding_distance: 0.1738727122349346', 'NSGA-II_rank: 3', 'change: 0.06749240423122481', 'is_elite: False']\n", + "Id: 78_59 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_35', '77_44'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_59', 'origin': '77_35~CUW~77_44#MGNP'} Metrics: ['ELUC: -1.0641446308191789', 'NSGA-II_crowding_distance: 0.4787946028490119', 'NSGA-II_rank: 4', 'change: 0.0836911116779294', 'is_elite: False']\n", + "Id: 77_75 Identity: {'ancestor_count': 71, 'ancestor_ids': ['76_92', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_75', 'origin': '76_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2098870963273631', 'NSGA-II_crowding_distance: 0.22882242576840703', 'NSGA-II_rank: 1', 'change: 0.05808474610340236', 'is_elite: True']\n", + "Id: 78_77 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_44', '77_60'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_77', 'origin': '77_44~CUW~77_60#MGNP'} Metrics: ['ELUC: -1.4087649580056296', 'NSGA-II_crowding_distance: 0.4557481817176873', 'NSGA-II_rank: 6', 'change: 0.1031945800587326', 'is_elite: False']\n", + "Id: 78_61 Identity: {'ancestor_count': 74, 'ancestor_ids': ['77_44', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_61', 'origin': '77_44~CUW~76_14#MGNP'} Metrics: ['ELUC: -1.4931472040203178', 'NSGA-II_crowding_distance: 0.1937670058672516', 'NSGA-II_rank: 3', 'change: 0.06921400287287248', 'is_elite: False']\n", + "Id: 78_30 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '1_1'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_30', 'origin': '77_28~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6610925039395468', 'NSGA-II_crowding_distance: 0.2064560931212509', 'NSGA-II_rank: 2', 'change: 0.060969467515490164', 'is_elite: False']\n", + "Id: 78_20 Identity: {'ancestor_count': 74, 'ancestor_ids': ['1_1', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_20', 'origin': '1_1~CUW~76_14#MGNP'} Metrics: ['ELUC: -2.115790069644963', 'NSGA-II_crowding_distance: 0.3339183747204395', 'NSGA-II_rank: 3', 'change: 0.08762089069326899', 'is_elite: False']\n", + "Id: 78_94 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_94', 'origin': '76_44~CUW~77_75#MGNP'} Metrics: ['ELUC: -2.378468011744331', 'NSGA-II_crowding_distance: 0.18080836297533454', 'NSGA-II_rank: 2', 'change: 0.07823387265050426', 'is_elite: False']\n", + "Id: 78_53 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_53', 'origin': '77_60~CUW~77_75#MGNP'} Metrics: ['ELUC: -2.5728946771436196', 'NSGA-II_crowding_distance: 0.11735576955283611', 'NSGA-II_rank: 6', 'change: 0.10335738833692887', 'is_elite: False']\n", + "Id: 78_13 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_44', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_13', 'origin': '77_44~CUW~77_57#MGNP'} Metrics: ['ELUC: -2.6136519193285372', 'NSGA-II_crowding_distance: 0.16715766304810628', 'NSGA-II_rank: 6', 'change: 0.1047859734473205', 'is_elite: False']\n", + "Id: 78_65 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_83', '77_28'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_65', 'origin': '77_83~CUW~77_28#MGNP'} Metrics: ['ELUC: -3.4354688939315356', 'NSGA-II_crowding_distance: 0.8136034714852355', 'NSGA-II_rank: 6', 'change: 0.1238197434215436', 'is_elite: False']\n", + "Id: 77_28 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_28', 'origin': '76_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.515599218727335', 'NSGA-II_crowding_distance: 0.24798637450944694', 'NSGA-II_rank: 1', 'change: 0.060201876866619694', 'is_elite: True']\n", + "Id: 78_62 Identity: {'ancestor_count': 76, 'ancestor_ids': ['1_1', '77_17'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_62', 'origin': '1_1~CUW~77_17#MGNP'} Metrics: ['ELUC: -3.5349899873947503', 'NSGA-II_crowding_distance: 0.33123789340905346', 'NSGA-II_rank: 5', 'change: 0.0971601602447592', 'is_elite: False']\n", + "Id: 78_89 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '77_44'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_89', 'origin': '77_28~CUW~77_44#MGNP'} Metrics: ['ELUC: -3.688035273930034', 'NSGA-II_crowding_distance: 0.20076585918108142', 'NSGA-II_rank: 2', 'change: 0.08026310097552815', 'is_elite: False']\n", + "Id: 78_73 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_75', '77_93'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_73', 'origin': '77_75~CUW~77_93#MGNP'} Metrics: ['ELUC: -3.84740464036654', 'NSGA-II_crowding_distance: 0.08140465783378169', 'NSGA-II_rank: 5', 'change: 0.10138080326254897', 'is_elite: False']\n", + "Id: 78_29 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '77_58'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_29', 'origin': '77_60~CUW~77_58#MGNP'} Metrics: ['ELUC: -4.2180617320302245', 'NSGA-II_crowding_distance: 0.11205567318218562', 'NSGA-II_rank: 5', 'change: 0.10422395969844486', 'is_elite: False']\n", + "Id: 78_38 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '2_49'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_38', 'origin': '77_17~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.414588131566742', 'NSGA-II_crowding_distance: 0.889948175158102', 'NSGA-II_rank: 6', 'change: 0.25548539970177714', 'is_elite: False']\n", + "Id: 78_60 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '1_1'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_60', 'origin': '77_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.55757574126721', 'NSGA-II_crowding_distance: 1.1155031878576727', 'NSGA-II_rank: 5', 'change: 0.11538605061362854', 'is_elite: False']\n", + "Id: 78_96 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '77_28'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_96', 'origin': '77_17~CUW~77_28#MGNP'} Metrics: ['ELUC: -4.677806209371008', 'NSGA-II_crowding_distance: 0.5873353339498818', 'NSGA-II_rank: 4', 'change: 0.09362601722725823', 'is_elite: False']\n", + "Id: 78_99 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_99', 'origin': '77_28~CUW~77_57#MGNP'} Metrics: ['ELUC: -4.7489399673087975', 'NSGA-II_crowding_distance: 0.1474998956134959', 'NSGA-II_rank: 1', 'change: 0.07201953588229346', 'is_elite: False']\n", + "Id: 78_55 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '77_28'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_55', 'origin': '77_60~CUW~77_28#MGNP'} Metrics: ['ELUC: -4.763795518488162', 'NSGA-II_crowding_distance: 0.2806582313460432', 'NSGA-II_rank: 3', 'change: 0.09111006868739399', 'is_elite: False']\n", + "Id: 78_43 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_43', 'origin': '77_28~CUW~76_14#MGNP'} Metrics: ['ELUC: -5.188468193653618', 'NSGA-II_crowding_distance: 0.31610533507830674', 'NSGA-II_rank: 3', 'change: 0.10035659622919973', 'is_elite: False']\n", + "Id: 78_70 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '77_35'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_70', 'origin': '77_60~CUW~77_35#MGNP'} Metrics: ['ELUC: -5.259966954884127', 'NSGA-II_crowding_distance: 0.32156370340982143', 'NSGA-II_rank: 2', 'change: 0.09057601894822005', 'is_elite: False']\n", + "Id: 78_41 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '77_35'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_41', 'origin': '77_28~CUW~77_35#MGNP'} Metrics: ['ELUC: -5.360465383692117', 'NSGA-II_crowding_distance: 0.18099020977297467', 'NSGA-II_rank: 1', 'change: 0.07290461124212681', 'is_elite: False']\n", + "Id: 78_82 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_13', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_82', 'origin': '77_13~CUW~77_57#MGNP'} Metrics: ['ELUC: -6.4534283416238845', 'NSGA-II_crowding_distance: 0.1992268964467443', 'NSGA-II_rank: 1', 'change: 0.09709728801757793', 'is_elite: False']\n", + "Id: 78_98 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '1_1'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_98', 'origin': '77_55~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.828882047610419', 'NSGA-II_crowding_distance: 0.635565746832592', 'NSGA-II_rank: 6', 'change: 0.2583175414390486', 'is_elite: False']\n", + "Id: 78_84 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_35', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_84', 'origin': '77_35~CUW~77_57#MGNP'} Metrics: ['ELUC: -7.279753584621076', 'NSGA-II_crowding_distance: 0.09309331163029068', 'NSGA-II_rank: 1', 'change: 0.09977856501282742', 'is_elite: False']\n", + "Id: 78_45 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_93', '77_58'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_45', 'origin': '77_93~CUW~77_58#MGNP'} Metrics: ['ELUC: -7.3468555548856065', 'NSGA-II_crowding_distance: 0.3172282393687321', 'NSGA-II_rank: 4', 'change: 0.11430923148651373', 'is_elite: False']\n", + "Id: 78_85 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '77_13'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_85', 'origin': '77_60~CUW~77_13#MGNP'} Metrics: ['ELUC: -7.527080820631599', 'NSGA-II_crowding_distance: 0.26203491354898', 'NSGA-II_rank: 4', 'change: 0.12093473606219562', 'is_elite: False']\n", + "Id: 78_49 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_57', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_49', 'origin': '77_57~CUW~77_57#MGNP'} Metrics: ['ELUC: -7.632259294496869', 'NSGA-II_crowding_distance: 0.05583662920771543', 'NSGA-II_rank: 1', 'change: 0.10486913301717529', 'is_elite: False']\n", + "Id: 78_52 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_57', '77_60'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_52', 'origin': '77_57~CUW~77_60#MGNP'} Metrics: ['ELUC: -7.7087932329920585', 'NSGA-II_crowding_distance: 0.21211658300801972', 'NSGA-II_rank: 2', 'change: 0.10858948152023565', 'is_elite: False']\n", + "Id: 78_66 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_66', 'origin': '77_17~CUW~77_57#MGNP'} Metrics: ['ELUC: -7.7649442431525415', 'NSGA-II_crowding_distance: 0.5297953157531569', 'NSGA-II_rank: 3', 'change: 0.11350195364902467', 'is_elite: False']\n", + "Id: 78_50 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_83', '76_44'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_50', 'origin': '77_83~CUW~76_44#MGNP'} Metrics: ['ELUC: -7.8430685740924835', 'NSGA-II_crowding_distance: 0.07670580451114066', 'NSGA-II_rank: 2', 'change: 0.11025678800727727', 'is_elite: False']\n", + "Id: 78_15 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_57', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_15', 'origin': '77_57~CUW~77_57#MGNP'} Metrics: ['ELUC: -7.850723420592749', 'NSGA-II_crowding_distance: 0.03995259288338572', 'NSGA-II_rank: 1', 'change: 0.10674943674312626', 'is_elite: False']\n", + "Id: 78_90 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_58', '77_93'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_90', 'origin': '77_58~CUW~77_93#MGNP'} Metrics: ['ELUC: -8.137775654000533', 'NSGA-II_crowding_distance: 0.25985356713905206', 'NSGA-II_rank: 2', 'change: 0.12297799947463671', 'is_elite: False']\n", + "Id: 77_57 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '76_92'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_57', 'origin': '76_44~CUW~76_92#MGNP'} Metrics: ['ELUC: -8.159665067081825', 'NSGA-II_crowding_distance: 0.07598485796308316', 'NSGA-II_rank: 1', 'change: 0.10783985787472226', 'is_elite: False']\n", + "Id: 78_76 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_58', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_76', 'origin': '77_58~CUW~77_57#MGNP'} Metrics: ['ELUC: -8.760801542085819', 'NSGA-II_crowding_distance: 0.17003620877128445', 'NSGA-II_rank: 1', 'change: 0.11397731881054604', 'is_elite: False']\n", + "Id: 78_48 Identity: {'ancestor_count': 76, 'ancestor_ids': ['2_49', '77_83'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_48', 'origin': '2_49~CUW~77_83#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 78_42 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '1_1'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_42', 'origin': '77_60~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.047610326335668', 'NSGA-II_crowding_distance: 0.3651788588459597', 'NSGA-II_rank: 4', 'change: 0.14978948483596816', 'is_elite: False']\n", + "Id: 78_63 Identity: {'ancestor_count': 76, 'ancestor_ids': ['76_100', '77_83'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_63', 'origin': '76_100~CUW~77_83#MGNP'} Metrics: ['ELUC: -9.432670932556782', 'NSGA-II_crowding_distance: 0.21289732916718027', 'NSGA-II_rank: 1', 'change: 0.13697157137193455', 'is_elite: False']\n", + "Id: 78_37 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_93', '2_49'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_37', 'origin': '77_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.448774924072058', 'NSGA-II_crowding_distance: 0.4871459800761043', 'NSGA-II_rank: 6', 'change: 0.2958886106752707', 'is_elite: False']\n", + "Id: 78_46 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '77_28'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_46', 'origin': '77_17~CUW~77_28#MGNP'} Metrics: ['ELUC: -9.641156602741319', 'NSGA-II_crowding_distance: 0.5728085618688961', 'NSGA-II_rank: 4', 'change: 0.1754516735482575', 'is_elite: False']\n", + "Id: 78_57 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_49', '77_93'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_57', 'origin': '77_49~CUW~77_93#MGNP'} Metrics: ['ELUC: -10.002620580665136', 'NSGA-II_crowding_distance: 0.5540068526495767', 'NSGA-II_rank: 3', 'change: 0.14166419848732872', 'is_elite: False']\n", + "Id: 78_88 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '76_100'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_88', 'origin': '77_55~CUW~76_100#MGNP'} Metrics: ['ELUC: -10.172520465650617', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3002620502043748', 'is_elite: False']\n", + "Id: 78_67 Identity: {'ancestor_count': 76, 'ancestor_ids': ['76_14', '77_93'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_67', 'origin': '76_14~CUW~77_93#MGNP'} Metrics: ['ELUC: -10.603004008792336', 'NSGA-II_crowding_distance: 0.3931178157610225', 'NSGA-II_rank: 2', 'change: 0.14018968802851645', 'is_elite: False']\n", + "Id: 78_17 Identity: {'ancestor_count': 76, 'ancestor_ids': ['76_100', '77_17'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_17', 'origin': '76_100~CUW~77_17#MGNP'} Metrics: ['ELUC: -11.066279200588896', 'NSGA-II_crowding_distance: 0.40491432335661354', 'NSGA-II_rank: 3', 'change: 0.18703873651620942', 'is_elite: False']\n", + "Id: 77_93 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_77', '76_56'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_93', 'origin': '76_77~CUW~76_56#MGNP'} Metrics: ['ELUC: -11.114690782214405', 'NSGA-II_crowding_distance: 0.12421788957089584', 'NSGA-II_rank: 1', 'change: 0.1375549114855765', 'is_elite: False']\n", + "Id: 78_75 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_93', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_75', 'origin': '77_93~CUW~76_14#MGNP'} Metrics: ['ELUC: -11.288652234588918', 'NSGA-II_crowding_distance: 0.08006175250965787', 'NSGA-II_rank: 1', 'change: 0.14253884669707662', 'is_elite: False']\n", + "Id: 78_36 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_93', '77_93'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_36', 'origin': '77_93~CUW~77_93#MGNP'} Metrics: ['ELUC: -11.75366564936565', 'NSGA-II_crowding_distance: 0.09189357142873167', 'NSGA-II_rank: 1', 'change: 0.15059995380102686', 'is_elite: False']\n", + "Id: 78_32 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '77_58'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_32', 'origin': '77_60~CUW~77_58#MGNP'} Metrics: ['ELUC: -11.797456739811699', 'NSGA-II_crowding_distance: 0.1166114951825151', 'NSGA-II_rank: 1', 'change: 0.16132327125471804', 'is_elite: False']\n", + "Id: 78_87 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_35', '77_17'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_87', 'origin': '77_35~CUW~77_17#MGNP'} Metrics: ['ELUC: -11.991019242387242', 'NSGA-II_crowding_distance: 1.2281686694213974', 'NSGA-II_rank: 5', 'change: 0.23055790492570954', 'is_elite: False']\n", + "Id: 78_58 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_58', 'origin': '77_17~CUW~77_75#MGNP'} Metrics: ['ELUC: -12.11740781214391', 'NSGA-II_crowding_distance: 0.29101475093101664', 'NSGA-II_rank: 2', 'change: 0.17107928941388506', 'is_elite: False']\n", + "Id: 78_92 Identity: {'ancestor_count': 76, 'ancestor_ids': ['1_1', '77_55'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_92', 'origin': '1_1~CUW~77_55#MGNP'} Metrics: ['ELUC: -12.194589515583877', 'NSGA-II_crowding_distance: 0.2684269407627971', 'NSGA-II_rank: 5', 'change: 0.27161834788961103', 'is_elite: False']\n", + "Id: 77_60 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_26', '75_27'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_60', 'origin': '76_26~CUW~75_27#MGNP'} Metrics: ['ELUC: -12.594906437860352', 'NSGA-II_crowding_distance: 0.2744731416178122', 'NSGA-II_rank: 3', 'change: 0.19226981728387954', 'is_elite: False']\n", + "Id: 78_78 Identity: {'ancestor_count': 76, 'ancestor_ids': ['76_100', '77_60'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_78', 'origin': '76_100~CUW~77_60#MGNP'} Metrics: ['ELUC: -12.622362721734525', 'NSGA-II_crowding_distance: 0.1900334628446394', 'NSGA-II_rank: 2', 'change: 0.18913763013631035', 'is_elite: False']\n", + "Id: 78_24 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_60'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_24', 'origin': '77_55~CUW~77_60#MGNP'} Metrics: ['ELUC: -12.686428703709138', 'NSGA-II_crowding_distance: 0.2136436429697688', 'NSGA-II_rank: 5', 'change: 0.2828234664741798', 'is_elite: False']\n", + "Id: 78_72 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_57', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_72', 'origin': '77_57~CUW~76_14#MGNP'} Metrics: ['ELUC: -12.932405294953451', 'NSGA-II_crowding_distance: 0.2563707473769376', 'NSGA-II_rank: 1', 'change: 0.16539065016790402', 'is_elite: True']\n", + "Id: 78_64 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_60'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_64', 'origin': '77_55~CUW~77_60#MGNP'} Metrics: ['ELUC: -12.947533529512492', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.30950534655156126', 'is_elite: False']\n", + "Id: 78_22 Identity: {'ancestor_count': 76, 'ancestor_ids': ['76_14', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_22', 'origin': '76_14~CUW~77_57#MGNP'} Metrics: ['ELUC: -13.099927698020593', 'NSGA-II_crowding_distance: 0.8387982989362961', 'NSGA-II_rank: 4', 'change: 0.2207280942633234', 'is_elite: False']\n", + "Id: 78_28 Identity: {'ancestor_count': 76, 'ancestor_ids': ['2_49', '77_83'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_28', 'origin': '2_49~CUW~77_83#MGNP'} Metrics: ['ELUC: -13.419907073097795', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.3219988660001994', 'is_elite: False']\n", + "Id: 78_40 Identity: {'ancestor_count': 76, 'ancestor_ids': ['76_14', '77_93'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_40', 'origin': '76_14~CUW~77_93#MGNP'} Metrics: ['ELUC: -13.5693690782279', 'NSGA-II_crowding_distance: 0.12323236512305447', 'NSGA-II_rank: 2', 'change: 0.20112329250033323', 'is_elite: False']\n", + "Id: 78_51 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '77_17'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_51', 'origin': '77_17~CUW~77_17#MGNP'} Metrics: ['ELUC: -13.578459932138497', 'NSGA-II_crowding_distance: 0.4871321191098919', 'NSGA-II_rank: 3', 'change: 0.2081223076626603', 'is_elite: False']\n", + "Id: 78_83 Identity: {'ancestor_count': 76, 'ancestor_ids': ['2_49', '77_83'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_83', 'origin': '2_49~CUW~77_83#MGNP'} Metrics: ['ELUC: -13.64557673018429', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2893608481330644', 'is_elite: False']\n", + "Id: 77_17 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_100', '76_26'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_17', 'origin': '76_100~CUW~76_26#MGNP'} Metrics: ['ELUC: -13.676955906591639', 'NSGA-II_crowding_distance: 0.0719747071995652', 'NSGA-II_rank: 2', 'change: 0.206993350864447', 'is_elite: False']\n", + "Id: 78_86 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_13', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_86', 'origin': '77_13~CUW~76_14#MGNP'} Metrics: ['ELUC: -13.921274957541907', 'NSGA-II_crowding_distance: 0.35016668065312906', 'NSGA-II_rank: 2', 'change: 0.21535302019892238', 'is_elite: False']\n", + "Id: 78_12 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_12', 'origin': '77_17~CUW~76_14#MGNP'} Metrics: ['ELUC: -14.184229337400312', 'NSGA-II_crowding_distance: 0.2525729878718641', 'NSGA-II_rank: 1', 'change: 0.19731432238145805', 'is_elite: True']\n", + "Id: 78_27 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_49', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_27', 'origin': '77_49~CUW~77_57#MGNP'} Metrics: ['ELUC: -14.242260196685494', 'NSGA-II_crowding_distance: 0.2409470037253769', 'NSGA-II_rank: 1', 'change: 0.21852415966386776', 'is_elite: True']\n", + "Id: 78_35 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_35', 'origin': '77_55~CUW~77_75#MGNP'} Metrics: ['ELUC: -14.623244490400149', 'NSGA-II_crowding_distance: 0.5243821613279268', 'NSGA-II_rank: 2', 'change: 0.2872468009678441', 'is_elite: False']\n", + "Id: 78_93 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_83', '77_60'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_93', 'origin': '77_83~CUW~77_60#MGNP'} Metrics: ['ELUC: -15.627352479340402', 'NSGA-II_crowding_distance: 0.1782922442497223', 'NSGA-II_rank: 1', 'change: 0.2447172941951426', 'is_elite: False']\n", + "Id: 76_14 Identity: {'ancestor_count': 73, 'ancestor_ids': ['75_68', '74_33'], 'birth_generation': 76, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '76_14', 'origin': '75_68~CUW~74_33#MGNP'} Metrics: ['ELUC: -15.734787458826037', 'NSGA-II_crowding_distance: 0.020682480456881328', 'NSGA-II_rank: 1', 'change: 0.24639394440606752', 'is_elite: False']\n", + "Id: 78_68 Identity: {'ancestor_count': 76, 'ancestor_ids': ['76_14', '77_17'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_68', 'origin': '76_14~CUW~77_17#MGNP'} Metrics: ['ELUC: -15.783026313209136', 'NSGA-II_crowding_distance: 0.1611312318838588', 'NSGA-II_rank: 1', 'change: 0.24824665250700517', 'is_elite: False']\n", + "Id: 78_79 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_79', 'origin': '77_55~CUW~77_75#MGNP'} Metrics: ['ELUC: -16.21059339499776', 'NSGA-II_crowding_distance: 0.22331744508966722', 'NSGA-II_rank: 1', 'change: 0.28639733972472264', 'is_elite: True']\n", + "Id: 78_47 Identity: {'ancestor_count': 76, 'ancestor_ids': ['2_49', '77_55'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_47', 'origin': '2_49~CUW~77_55#MGNP'} Metrics: ['ELUC: -16.776051892996605', 'NSGA-II_crowding_distance: 0.12055648910804244', 'NSGA-II_rank: 1', 'change: 0.2980276512448888', 'is_elite: False']\n", + "Id: 78_69 Identity: {'ancestor_count': 76, 'ancestor_ids': ['2_49', '77_55'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_69', 'origin': '2_49~CUW~77_55#MGNP'} Metrics: ['ELUC: -17.433965507140513', 'NSGA-II_crowding_distance: 0.06253717990040278', 'NSGA-II_rank: 1', 'change: 0.3016077076505848', 'is_elite: False']\n", + "Id: 78_34 Identity: {'ancestor_count': 76, 'ancestor_ids': ['2_49', '77_93'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_34', 'origin': '2_49~CUW~77_93#MGNP'} Metrics: ['ELUC: -17.58617896968203', 'NSGA-II_crowding_distance: 0.014029415168643256', 'NSGA-II_rank: 1', 'change: 0.3029392459004282', 'is_elite: False']\n", + "Id: 78_74 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_17'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_74', 'origin': '77_55~CUW~77_17#MGNP'} Metrics: ['ELUC: -17.596862600266125', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030217627170344', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 77_55 Identity: {'ancestor_count': 75, 'ancestor_ids': ['2_49', '76_77'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_55', 'origin': '2_49~CUW~76_77#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 78_19 Identity: {'ancestor_count': 76, 'ancestor_ids': ['76_14', '77_55'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_19', 'origin': '76_14~CUW~77_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 78_33 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_33', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 78_56 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_56', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 78_71 Identity: {'ancestor_count': 76, 'ancestor_ids': ['1_1', '77_55'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_71', 'origin': '1_1~CUW~77_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 78_97 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_60', '2_49'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_97', 'origin': '77_60~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 78_100 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_55'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_100', 'origin': '77_55~CUW~77_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 78.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 79...:\n", + "PopulationResponse:\n", + " Generation: 79\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/79/20240220-051143\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 79 and asking ESP for generation 80...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 79 data persisted.\n", + "Evaluated candidates:\n", + "Id: 79_11 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_12', '2_49'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_11', 'origin': '78_12~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832139317147604', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037735054467949', 'is_elite: False']\n", + "Id: 79_35 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '78_26'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_35', 'origin': '78_79~CUW~78_26#MGNP'} Metrics: ['ELUC: 23.80610469175861', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.30342597168749064', 'is_elite: False']\n", + "Id: 79_28 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_28', 'origin': '78_72~CUW~78_100#MGNP'} Metrics: ['ELUC: 12.113058674722701', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27419765699087595', 'is_elite: False']\n", + "Id: 79_31 Identity: {'ancestor_count': 77, 'ancestor_ids': ['2_49', '78_41'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_31', 'origin': '2_49~CUW~78_41#MGNP'} Metrics: ['ELUC: 6.061095037129206', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2645628450174315', 'is_elite: False']\n", + "Id: 79_58 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_75', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_58', 'origin': '77_75~CUW~78_63#MGNP'} Metrics: ['ELUC: 2.6935623399763506', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.0966582181665213', 'is_elite: False']\n", + "Id: 79_42 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_26', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_42', 'origin': '78_26~CUW~78_63#MGNP'} Metrics: ['ELUC: 2.1828465764698675', 'NSGA-II_crowding_distance: 0.9198242150680993', 'NSGA-II_rank: 7', 'change: 0.10106810939048229', 'is_elite: False']\n", + "Id: 79_80 Identity: {'ancestor_count': 73, 'ancestor_ids': ['1_1', '78_26'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_80', 'origin': '1_1~CUW~78_26#MGNP'} Metrics: ['ELUC: 1.8798228115671813', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04652505936863787', 'is_elite: False']\n", + "Id: 79_93 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_82', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_93', 'origin': '78_82~CUW~78_100#MGNP'} Metrics: ['ELUC: 1.8620611245997227', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23707501030457', 'is_elite: False']\n", + "Id: 79_26 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '77_75'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_26', 'origin': '78_100~CUW~77_75#MGNP'} Metrics: ['ELUC: 1.4082764869828486', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.306181763332244', 'is_elite: False']\n", + "Id: 79_64 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '77_28'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_64', 'origin': '78_72~CUW~77_28#MGNP'} Metrics: ['ELUC: 1.059113135160607', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.07400106951292161', 'is_elite: False']\n", + "Id: 79_17 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_75', '78_76'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_17', 'origin': '77_75~CUW~78_76#MGNP'} Metrics: ['ELUC: 0.8617332293239146', 'NSGA-II_crowding_distance: 0.17269644023345737', 'NSGA-II_rank: 6', 'change: 0.09166881548926495', 'is_elite: False']\n", + "Id: 79_30 Identity: {'ancestor_count': 73, 'ancestor_ids': ['78_26', '78_26'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_30', 'origin': '78_26~CUW~78_26#MGNP'} Metrics: ['ELUC: 0.4106460993244449', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.041610919086494634', 'is_elite: False']\n", + "Id: 79_12 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_75', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_12', 'origin': '77_75~CUW~78_100#MGNP'} Metrics: ['ELUC: 0.19032291802015405', 'NSGA-II_crowding_distance: 1.1173573217525834', 'NSGA-II_rank: 7', 'change: 0.23489355721947625', 'is_elite: False']\n", + "Id: 79_34 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_34', 'origin': '78_72~CUW~78_63#MGNP'} Metrics: ['ELUC: 0.16869223783989304', 'NSGA-II_crowding_distance: 0.8997113915373123', 'NSGA-II_rank: 6', 'change: 0.09337482380777871', 'is_elite: False']\n", + "Id: 79_81 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_72'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_81', 'origin': '78_100~CUW~78_72#MGNP'} Metrics: ['ELUC: 0.13469419986350667', 'NSGA-II_crowding_distance: 0.8643456985131154', 'NSGA-II_rank: 8', 'change: 0.25619429632923874', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 79_16 Identity: {'ancestor_count': 73, 'ancestor_ids': ['78_26', '1_1'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_16', 'origin': '78_26~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.2537062425884639', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.06318305812293855', 'is_elite: False']\n", + "Id: 79_19 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_27', '1_1'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_19', 'origin': '78_27~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.30665734532788447', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.061796434998657855', 'is_elite: False']\n", + "Id: 79_84 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_47', '77_28'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_84', 'origin': '78_47~CUW~77_28#MGNP'} Metrics: ['ELUC: -0.4119040461693181', 'NSGA-II_crowding_distance: 0.992284451661481', 'NSGA-II_rank: 8', 'change: 0.2770107831121024', 'is_elite: False']\n", + "Id: 78_26 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_26', 'origin': '1_1~CUW~77_75#MGNP'} Metrics: ['ELUC: -0.4578627608522755', 'NSGA-II_crowding_distance: 0.2399765348526271', 'NSGA-II_rank: 1', 'change: 0.043817094454783156', 'is_elite: True']\n", + "Id: 79_13 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_13', 'origin': '78_100~CUW~78_63#MGNP'} Metrics: ['ELUC: -0.5668355961981181', 'NSGA-II_crowding_distance: 1.2856717198368188', 'NSGA-II_rank: 6', 'change: 0.23884854613953815', 'is_elite: False']\n", + "Id: 79_36 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '2_49'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_36', 'origin': '77_28~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.7818906232434093', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3291030001394465', 'is_elite: False']\n", + "Id: 79_51 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_75', '77_28'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_51', 'origin': '77_75~CUW~77_28#MGNP'} Metrics: ['ELUC: -1.1810136380301153', 'NSGA-II_crowding_distance: 0.27842892466382985', 'NSGA-II_rank: 3', 'change: 0.060908909444524185', 'is_elite: False']\n", + "Id: 77_75 Identity: {'ancestor_count': 71, 'ancestor_ids': ['76_92', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_75', 'origin': '76_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2098870963273631', 'NSGA-II_crowding_distance: 0.20583177861644658', 'NSGA-II_rank: 2', 'change: 0.05808474610340236', 'is_elite: False']\n", + "Id: 79_67 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_67', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5910723650455143', 'NSGA-II_crowding_distance: 0.1607826360405459', 'NSGA-II_rank: 1', 'change: 0.049500772600951044', 'is_elite: False']\n", + "Id: 79_21 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_76', '77_75'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_21', 'origin': '78_76~CUW~77_75#MGNP'} Metrics: ['ELUC: -1.886986619822046', 'NSGA-II_crowding_distance: 1.0668991345203356', 'NSGA-II_rank: 4', 'change: 0.09271351582034934', 'is_elite: False']\n", + "Id: 79_85 Identity: {'ancestor_count': 77, 'ancestor_ids': ['1_1', '78_99'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_85', 'origin': '1_1~CUW~78_99#MGNP'} Metrics: ['ELUC: -1.9356243964315578', 'NSGA-II_crowding_distance: 0.4533392024499958', 'NSGA-II_rank: 3', 'change: 0.06727816552633417', 'is_elite: False']\n", + "Id: 79_41 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_99', '77_75'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_41', 'origin': '78_99~CUW~77_75#MGNP'} Metrics: ['ELUC: -2.11765549458153', 'NSGA-II_crowding_distance: 0.09037619879131428', 'NSGA-II_rank: 2', 'change: 0.05871568347013106', 'is_elite: False']\n", + "Id: 79_45 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_76'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_45', 'origin': '78_100~CUW~78_76#MGNP'} Metrics: ['ELUC: -2.2629064217324824', 'NSGA-II_crowding_distance: 0.615925806871493', 'NSGA-II_rank: 7', 'change: 0.25101725014396564', 'is_elite: False']\n", + "Id: 79_78 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_41', '77_28'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_78', 'origin': '78_41~CUW~77_28#MGNP'} Metrics: ['ELUC: -2.4439153191987715', 'NSGA-II_crowding_distance: 0.05700295686059349', 'NSGA-II_rank: 2', 'change: 0.06379638537804912', 'is_elite: False']\n", + "Id: 79_96 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_27', '77_28'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_96', 'origin': '78_27~CUW~77_28#MGNP'} Metrics: ['ELUC: -2.4743653182056486', 'NSGA-II_crowding_distance: 0.18567423023672242', 'NSGA-II_rank: 2', 'change: 0.06843873464251185', 'is_elite: False']\n", + "Id: 79_55 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '78_26'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_55', 'origin': '77_28~CUW~78_26#MGNP'} Metrics: ['ELUC: -2.6132406284640677', 'NSGA-II_crowding_distance: 0.11703966338854484', 'NSGA-II_rank: 1', 'change: 0.05521362327588024', 'is_elite: False']\n", + "Id: 79_87 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_26', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_87', 'origin': '78_26~CUW~78_100#MGNP'} Metrics: ['ELUC: -3.221970177599764', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.28651130306465417', 'is_elite: False']\n", + "Id: 79_53 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '78_26'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_53', 'origin': '78_79~CUW~78_26#MGNP'} Metrics: ['ELUC: -3.275111644844417', 'NSGA-II_crowding_distance: 1.7718989205927251', 'NSGA-II_rank: 5', 'change: 0.20822135431628858', 'is_elite: False']\n", + "Id: 79_50 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_75', '77_28'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_50', 'origin': '77_75~CUW~77_28#MGNP'} Metrics: ['ELUC: -3.3116269442601296', 'NSGA-II_crowding_distance: 0.06803978972786115', 'NSGA-II_rank: 1', 'change: 0.055224458424926195', 'is_elite: False']\n", + "Id: 77_28 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_28', 'origin': '76_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.515599218727335', 'NSGA-II_crowding_distance: 0.22514215840206264', 'NSGA-II_rank: 1', 'change: 0.060201876866619694', 'is_elite: True']\n", + "Id: 79_97 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_41', '1_1'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_97', 'origin': '78_41~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.119748036519869', 'NSGA-II_crowding_distance: 0.45986136658835475', 'NSGA-II_rank: 2', 'change: 0.088006565365651', 'is_elite: False']\n", + "Id: 79_82 Identity: {'ancestor_count': 77, 'ancestor_ids': ['1_1', '78_32'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_82', 'origin': '1_1~CUW~78_32#MGNP'} Metrics: ['ELUC: -4.309751197091586', 'NSGA-II_crowding_distance: 0.7471703056563209', 'NSGA-II_rank: 3', 'change: 0.13574698041613964', 'is_elite: False']\n", + "Id: 79_89 Identity: {'ancestor_count': 73, 'ancestor_ids': ['78_26', '2_49'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_89', 'origin': '78_26~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.400568938106666', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2779176607128076', 'is_elite: False']\n", + "Id: 79_88 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '1_1'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_88', 'origin': '78_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.000724801432787', 'NSGA-II_crowding_distance: 1.1356543014868845', 'NSGA-II_rank: 8', 'change: 0.2770403289764425', 'is_elite: False']\n", + "Id: 79_44 Identity: {'ancestor_count': 77, 'ancestor_ids': ['2_49', '78_76'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_44', 'origin': '2_49~CUW~78_76#MGNP'} Metrics: ['ELUC: -5.434915181347992', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.30932889513535955', 'is_elite: False']\n", + "Id: 79_37 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_41', '78_27'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_37', 'origin': '78_41~CUW~78_27#MGNP'} Metrics: ['ELUC: -5.471572710834718', 'NSGA-II_crowding_distance: 0.32039198433117855', 'NSGA-II_rank: 1', 'change: 0.08574691577329832', 'is_elite: True']\n", + "Id: 79_77 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_63', '78_79'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_77', 'origin': '78_63~CUW~78_79#MGNP'} Metrics: ['ELUC: -6.048800045097983', 'NSGA-II_crowding_distance: 0.6639119499497604', 'NSGA-II_rank: 6', 'change: 0.24353313214079844', 'is_elite: False']\n", + "Id: 79_33 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_82', '2_49'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_33', 'origin': '78_82~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.341561544082334', 'NSGA-II_crowding_distance: 0.5016400250483466', 'NSGA-II_rank: 7', 'change: 0.2653424948806678', 'is_elite: False']\n", + "Id: 79_48 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_28', '78_93'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_48', 'origin': '77_28~CUW~78_93#MGNP'} Metrics: ['ELUC: -6.617855234163039', 'NSGA-II_crowding_distance: 0.2622094807592584', 'NSGA-II_rank: 1', 'change: 0.10315346425724053', 'is_elite: True']\n", + "Id: 79_29 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_75', '78_82'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_29', 'origin': '77_75~CUW~78_82#MGNP'} Metrics: ['ELUC: -7.083921871615853', 'NSGA-II_crowding_distance: 0.39981941491019257', 'NSGA-II_rank: 2', 'change: 0.12173724364435089', 'is_elite: False']\n", + "Id: 79_47 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '1_1'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_47', 'origin': '78_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.059252173636894', 'NSGA-II_crowding_distance: 0.20031378175853898', 'NSGA-II_rank: 1', 'change: 0.12007066340577863', 'is_elite: True']\n", + "Id: 79_25 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_41'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_25', 'origin': '78_100~CUW~78_41#MGNP'} Metrics: ['ELUC: -8.061132053849905', 'NSGA-II_crowding_distance: 0.36800328804884636', 'NSGA-II_rank: 7', 'change: 0.2696972970386556', 'is_elite: False']\n", + "Id: 79_57 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_57', 'origin': '78_79~CUW~78_63#MGNP'} Metrics: ['ELUC: -8.406155695012533', 'NSGA-II_crowding_distance: 0.541631839929724', 'NSGA-II_rank: 6', 'change: 0.24971097748790258', 'is_elite: False']\n", + "Id: 79_76 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_75', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_76', 'origin': '77_75~CUW~78_63#MGNP'} Metrics: ['ELUC: -8.910507179647604', 'NSGA-II_crowding_distance: 0.18001301955521498', 'NSGA-II_rank: 2', 'change: 0.12297901515283469', 'is_elite: False']\n", + "Id: 79_94 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_26', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_94', 'origin': '78_26~CUW~78_63#MGNP'} Metrics: ['ELUC: -8.997364013237778', 'NSGA-II_crowding_distance: 0.1808709673137895', 'NSGA-II_rank: 1', 'change: 0.12254163534674489', 'is_elite: False']\n", + "Id: 79_59 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_27', '77_75'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_59', 'origin': '78_27~CUW~77_75#MGNP'} Metrics: ['ELUC: -9.171812255150625', 'NSGA-II_crowding_distance: 1.2056564527095184', 'NSGA-II_rank: 4', 'change: 0.15241012323653466', 'is_elite: False']\n", + "Id: 79_22 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_99', '78_72'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_22', 'origin': '78_99~CUW~78_72#MGNP'} Metrics: ['ELUC: -9.357144723524979', 'NSGA-II_crowding_distance: 0.11701824750558723', 'NSGA-II_rank: 2', 'change: 0.13579553333503275', 'is_elite: False']\n", + "Id: 79_100 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '78_93'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_100', 'origin': '78_72~CUW~78_93#MGNP'} Metrics: ['ELUC: -10.05678450770523', 'NSGA-II_crowding_distance: 0.09587028776258913', 'NSGA-II_rank: 2', 'change: 0.13692901685216946', 'is_elite: False']\n", + "Id: 79_95 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_28', '78_93'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_95', 'origin': '77_28~CUW~78_93#MGNP'} Metrics: ['ELUC: -10.101148016357083', 'NSGA-II_crowding_distance: 0.5112855125917665', 'NSGA-II_rank: 3', 'change: 0.15056890395613023', 'is_elite: False']\n", + "Id: 79_73 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_76', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_73', 'origin': '78_76~CUW~78_63#MGNP'} Metrics: ['ELUC: -10.545700643844512', 'NSGA-II_crowding_distance: 0.15912334362661967', 'NSGA-II_rank: 1', 'change: 0.13184273244638609', 'is_elite: False']\n", + "Id: 79_98 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_63', '78_93'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_98', 'origin': '78_63~CUW~78_93#MGNP'} Metrics: ['ELUC: -10.746377717719524', 'NSGA-II_crowding_distance: 0.2686203421655599', 'NSGA-II_rank: 2', 'change: 0.14069036625524214', 'is_elite: False']\n", + "Id: 79_92 Identity: {'ancestor_count': 76, 'ancestor_ids': ['2_49', '77_28'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_92', 'origin': '2_49~CUW~77_28#MGNP'} Metrics: ['ELUC: -10.850642137341508', 'NSGA-II_crowding_distance: 0.2519691567580577', 'NSGA-II_rank: 7', 'change: 0.27577775632177115', 'is_elite: False']\n", + "Id: 79_61 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_82', '78_72'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_61', 'origin': '78_82~CUW~78_72#MGNP'} Metrics: ['ELUC: -11.082823142882509', 'NSGA-II_crowding_distance: 0.07396876943325148', 'NSGA-II_rank: 1', 'change: 0.134629610819906', 'is_elite: False']\n", + "Id: 79_86 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_93', '78_72'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_86', 'origin': '78_93~CUW~78_72#MGNP'} Metrics: ['ELUC: -11.154185516449411', 'NSGA-II_crowding_distance: 0.11309346104387513', 'NSGA-II_rank: 1', 'change: 0.1435871890012735', 'is_elite: False']\n", + "Id: 79_15 Identity: {'ancestor_count': 77, 'ancestor_ids': ['2_49', '78_72'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_15', 'origin': '2_49~CUW~78_72#MGNP'} Metrics: ['ELUC: -11.223423790522473', 'NSGA-II_crowding_distance: 0.09624669001156125', 'NSGA-II_rank: 7', 'change: 0.2758833711970301', 'is_elite: False']\n", + "Id: 79_43 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_26', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_43', 'origin': '78_26~CUW~78_12#MGNP'} Metrics: ['ELUC: -11.31786475062643', 'NSGA-II_crowding_distance: 0.17421005756833507', 'NSGA-II_rank: 1', 'change: 0.1643854507210059', 'is_elite: False']\n", + "Id: 79_40 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_28', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_40', 'origin': '77_28~CUW~78_12#MGNP'} Metrics: ['ELUC: -11.524389204843809', 'NSGA-II_crowding_distance: 0.28690874279176104', 'NSGA-II_rank: 3', 'change: 0.17108432072071164', 'is_elite: False']\n", + "Id: 79_79 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_27', '78_63'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_79', 'origin': '78_27~CUW~78_63#MGNP'} Metrics: ['ELUC: -11.537605599687872', 'NSGA-II_crowding_distance: 0.6437896506192301', 'NSGA-II_rank: 4', 'change: 0.2013387545748847', 'is_elite: False']\n", + "Id: 79_68 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_27'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_68', 'origin': '78_100~CUW~78_27#MGNP'} Metrics: ['ELUC: -11.775951379001446', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2817560090264863', 'is_elite: False']\n", + "Id: 79_20 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_72'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_20', 'origin': '78_100~CUW~78_72#MGNP'} Metrics: ['ELUC: -11.884417580975148', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.26045981535041646', 'is_elite: False']\n", + "Id: 79_69 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_12', '78_99'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_69', 'origin': '78_12~CUW~78_99#MGNP'} Metrics: ['ELUC: -12.399315821631129', 'NSGA-II_crowding_distance: 0.2216840746171185', 'NSGA-II_rank: 3', 'change: 0.1936984635882598', 'is_elite: False']\n", + "Id: 79_39 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_75', '78_79'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_39', 'origin': '77_75~CUW~78_79#MGNP'} Metrics: ['ELUC: -12.780810688169051', 'NSGA-II_crowding_distance: 1.1068574081245104', 'NSGA-II_rank: 5', 'change: 0.24183942485080703', 'is_elite: False']\n", + "Id: 79_72 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_72', 'origin': '78_72~CUW~78_12#MGNP'} Metrics: ['ELUC: -12.815398800948296', 'NSGA-II_crowding_distance: 0.40734805584667966', 'NSGA-II_rank: 2', 'change: 0.1671040929571505', 'is_elite: False']\n", + "Id: 78_72 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_57', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_72', 'origin': '77_57~CUW~76_14#MGNP'} Metrics: ['ELUC: -12.932405294953451', 'NSGA-II_crowding_distance: 0.13917265490798023', 'NSGA-II_rank: 1', 'change: 0.16539065016790402', 'is_elite: False']\n", + "Id: 79_14 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_12', '78_72'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_14', 'origin': '78_12~CUW~78_72#MGNP'} Metrics: ['ELUC: -13.340802568055903', 'NSGA-II_crowding_distance: 0.11049396813446646', 'NSGA-II_rank: 1', 'change: 0.17158159122948716', 'is_elite: False']\n", + "Id: 79_38 Identity: {'ancestor_count': 77, 'ancestor_ids': ['2_49', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_38', 'origin': '2_49~CUW~78_12#MGNP'} Metrics: ['ELUC: -13.362072907333955', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28205983596986756', 'is_elite: False']\n", + "Id: 79_83 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_27', '78_82'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_83', 'origin': '78_27~CUW~78_82#MGNP'} Metrics: ['ELUC: -13.585008416140933', 'NSGA-II_crowding_distance: 0.5387448071041414', 'NSGA-II_rank: 4', 'change: 0.22295071163417687', 'is_elite: False']\n", + "Id: 79_60 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_93', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_60', 'origin': '77_93~CUW~78_12#MGNP'} Metrics: ['ELUC: -13.615282164717536', 'NSGA-II_crowding_distance: 0.3657404311101826', 'NSGA-II_rank: 3', 'change: 0.20021338866178073', 'is_elite: False']\n", + "Id: 79_99 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_93', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_99', 'origin': '77_93~CUW~78_12#MGNP'} Metrics: ['ELUC: -13.616904220134813', 'NSGA-II_crowding_distance: 0.11491991853994149', 'NSGA-II_rank: 1', 'change: 0.18674343013096276', 'is_elite: False']\n", + "Id: 79_49 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_93', '2_49'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_49', 'origin': '78_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.628768967055315', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28751105337813654', 'is_elite: False']\n", + "Id: 79_32 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_12', '2_49'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_32', 'origin': '78_12~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.681497419010242', 'NSGA-II_crowding_distance: 0.37989085627206975', 'NSGA-II_rank: 3', 'change: 0.2706085393664488', 'is_elite: False']\n", + "Id: 79_65 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_12', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_65', 'origin': '78_12~CUW~78_12#MGNP'} Metrics: ['ELUC: -14.023167854190673', 'NSGA-II_crowding_distance: 0.06769464792069192', 'NSGA-II_rank: 1', 'change: 0.19429118467059842', 'is_elite: False']\n", + "Id: 79_23 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_26', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_23', 'origin': '78_26~CUW~78_12#MGNP'} Metrics: ['ELUC: -14.093714022169545', 'NSGA-II_crowding_distance: 0.5527490886742216', 'NSGA-II_rank: 2', 'change: 0.19858426820966515', 'is_elite: False']\n", + "Id: 78_12 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_17', '76_14'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_12', 'origin': '77_17~CUW~76_14#MGNP'} Metrics: ['ELUC: -14.184229337400312', 'NSGA-II_crowding_distance: 0.09367669975412207', 'NSGA-II_rank: 1', 'change: 0.19731432238145805', 'is_elite: False']\n", + "Id: 78_27 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_49', '77_57'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_27', 'origin': '77_49~CUW~77_57#MGNP'} Metrics: ['ELUC: -14.242260196685494', 'NSGA-II_crowding_distance: 0.07718019831267328', 'NSGA-II_rank: 1', 'change: 0.21852415966386776', 'is_elite: False']\n", + "Id: 79_74 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_27', '78_27'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_74', 'origin': '78_27~CUW~78_27#MGNP'} Metrics: ['ELUC: -14.263547648596088', 'NSGA-II_crowding_distance: 0.057082306217836935', 'NSGA-II_rank: 1', 'change: 0.2189971173644866', 'is_elite: False']\n", + "Id: 79_18 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_27', '77_28'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_18', 'origin': '78_27~CUW~77_28#MGNP'} Metrics: ['ELUC: -14.455425113301958', 'NSGA-II_crowding_distance: 0.11807607908695263', 'NSGA-II_rank: 1', 'change: 0.23193877339872004', 'is_elite: False']\n", + "Id: 79_75 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_75', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -14.461963950031906', 'NSGA-II_crowding_distance: 0.3217515957779056', 'NSGA-II_rank: 3', 'change: 0.28655669198200173', 'is_elite: False']\n", + "Id: 79_63 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_63', 'origin': '78_79~CUW~78_12#MGNP'} Metrics: ['ELUC: -14.943905789257686', 'NSGA-II_crowding_distance: 0.5940725347701212', 'NSGA-II_rank: 2', 'change: 0.28070053658311694', 'is_elite: False']\n", + "Id: 79_71 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_93', '78_12'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_71', 'origin': '78_93~CUW~78_12#MGNP'} Metrics: ['ELUC: -15.378154633617399', 'NSGA-II_crowding_distance: 0.1049894597385657', 'NSGA-II_rank: 1', 'change: 0.23531316394271373', 'is_elite: False']\n", + "Id: 79_46 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_93', '78_27'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_46', 'origin': '78_93~CUW~78_27#MGNP'} Metrics: ['ELUC: -15.662605280923191', 'NSGA-II_crowding_distance: 0.21855157055066088', 'NSGA-II_rank: 1', 'change: 0.24277906897011056', 'is_elite: True']\n", + "Id: 78_79 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_79', 'origin': '77_55~CUW~77_75#MGNP'} Metrics: ['ELUC: -16.21059339499776', 'NSGA-II_crowding_distance: 0.2541021743841507', 'NSGA-II_rank: 1', 'change: 0.28639733972472264', 'is_elite: True']\n", + "Id: 79_62 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '78_27'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_62', 'origin': '78_79~CUW~78_27#MGNP'} Metrics: ['ELUC: -17.232181301209376', 'NSGA-II_crowding_distance: 0.1345679588247155', 'NSGA-II_rank: 1', 'change: 0.29196130622290045', 'is_elite: False']\n", + "Id: 79_90 Identity: {'ancestor_count': 77, 'ancestor_ids': ['2_49', '78_82'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_90', 'origin': '2_49~CUW~78_82#MGNP'} Metrics: ['ELUC: -17.422991683511373', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3034779699606275', 'is_elite: False']\n", + "Id: 79_91 Identity: {'ancestor_count': 77, 'ancestor_ids': ['1_1', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_91', 'origin': '1_1~CUW~78_100#MGNP'} Metrics: ['ELUC: -17.597148620946363', 'NSGA-II_crowding_distance: 0.05783544006971339', 'NSGA-II_rank: 1', 'change: 0.30301915023057635', 'is_elite: False']\n", + "Id: 79_56 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_56', 'origin': '78_72~CUW~78_100#MGNP'} Metrics: ['ELUC: -17.597279947015164', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302214505575', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 78_100 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_55'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_100', 'origin': '77_55~CUW~77_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 79_24 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '2_49'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_24', 'origin': '78_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 79_27 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_27', 'origin': '78_79~CUW~78_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 79_52 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_76', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_52', 'origin': '78_76~CUW~78_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 79_54 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_12', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_54', 'origin': '78_12~CUW~78_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 79_66 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_100'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_66', 'origin': '78_100~CUW~78_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 79_70 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_41'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_70', 'origin': '78_100~CUW~78_41#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 79.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 80...:\n", + "PopulationResponse:\n", + " Generation: 80\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/80/20240220-051859\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 80 and asking ESP for generation 81...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 80 data persisted.\n", + "Evaluated candidates:\n", + "Id: 80_19 Identity: {'ancestor_count': 78, 'ancestor_ids': ['2_49', '79_62'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_19', 'origin': '2_49~CUW~79_62#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 80_27 Identity: {'ancestor_count': 78, 'ancestor_ids': ['2_49', '79_47'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_27', 'origin': '2_49~CUW~79_47#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 80_24 Identity: {'ancestor_count': 78, 'ancestor_ids': ['2_49', '79_37'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_24', 'origin': '2_49~CUW~79_37#MGNP'} Metrics: ['ELUC: 23.219043645001584', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2996595176604623', 'is_elite: False']\n", + "Id: 80_32 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_70', '79_47'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_32', 'origin': '79_70~CUW~79_47#MGNP'} Metrics: ['ELUC: 11.978395020287955', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.22481561998670208', 'is_elite: False']\n", + "Id: 80_68 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_46', '79_67'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_68', 'origin': '79_46~CUW~79_67#MGNP'} Metrics: ['ELUC: 2.5667747316795793', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.10151840209639028', 'is_elite: False']\n", + "Id: 80_70 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_70', 'origin': '79_37~CUW~2_49#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 80_31 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_70', '77_28'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_31', 'origin': '79_70~CUW~77_28#MGNP'} Metrics: ['ELUC: 2.0510615600242157', 'NSGA-II_crowding_distance: 1.6140324072308905', 'NSGA-II_rank: 8', 'change: 0.21188431287109558', 'is_elite: False']\n", + "Id: 80_64 Identity: {'ancestor_count': 77, 'ancestor_ids': ['79_67', '78_72'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_64', 'origin': '79_67~CUW~78_72#MGNP'} Metrics: ['ELUC: 1.974660339797733', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.08537392997890805', 'is_elite: False']\n", + "Id: 80_53 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '78_26'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_53', 'origin': '79_37~CUW~78_26#MGNP'} Metrics: ['ELUC: 1.2521545417822872', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0693900082951211', 'is_elite: False']\n", + "Id: 80_57 Identity: {'ancestor_count': 78, 'ancestor_ids': ['1_1', '79_94'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_57', 'origin': '1_1~CUW~79_94#MGNP'} Metrics: ['ELUC: 1.185028876605543', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.07077785054518433', 'is_elite: False']\n", + "Id: 80_97 Identity: {'ancestor_count': 78, 'ancestor_ids': ['78_26', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_97', 'origin': '78_26~CUW~79_48#MGNP'} Metrics: ['ELUC: 1.1036526072415753', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07036223769126308', 'is_elite: False']\n", + "Id: 80_12 Identity: {'ancestor_count': 78, 'ancestor_ids': ['77_28', '79_43'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_12', 'origin': '77_28~CUW~79_43#MGNP'} Metrics: ['ELUC: 0.27334226052991006', 'NSGA-II_crowding_distance: 0.2637041624604255', 'NSGA-II_rank: 5', 'change: 0.07079101594828749', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 78_26 Identity: {'ancestor_count': 72, 'ancestor_ids': ['1_1', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_26', 'origin': '1_1~CUW~77_75#MGNP'} Metrics: ['ELUC: -0.4578627608522755', 'NSGA-II_crowding_distance: 0.18346466311753143', 'NSGA-II_rank: 1', 'change: 0.043817094454783156', 'is_elite: False']\n", + "Id: 80_98 Identity: {'ancestor_count': 78, 'ancestor_ids': ['78_26', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_98', 'origin': '78_26~CUW~79_46#MGNP'} Metrics: ['ELUC: -0.49062873906550863', 'NSGA-II_crowding_distance: 0.39580887356153704', 'NSGA-II_rank: 7', 'change: 0.09792053639192799', 'is_elite: False']\n", + "Id: 80_25 Identity: {'ancestor_count': 73, 'ancestor_ids': ['79_67', '78_26'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_25', 'origin': '79_67~CUW~78_26#MGNP'} Metrics: ['ELUC: -0.5972510356594682', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04657792729198894', 'is_elite: False']\n", + "Id: 80_95 Identity: {'ancestor_count': 73, 'ancestor_ids': ['78_26', '78_26'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_95', 'origin': '78_26~CUW~78_26#MGNP'} Metrics: ['ELUC: -0.9094454041955143', 'NSGA-II_crowding_distance: 0.09085191754376715', 'NSGA-II_rank: 1', 'change: 0.04420630905883744', 'is_elite: False']\n", + "Id: 80_46 Identity: {'ancestor_count': 73, 'ancestor_ids': ['78_26', '1_1'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_46', 'origin': '78_26~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.952719087233226', 'NSGA-II_crowding_distance: 0.11726707323657223', 'NSGA-II_rank: 2', 'change: 0.052270981299424445', 'is_elite: False']\n", + "Id: 80_47 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '1_1'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_47', 'origin': '78_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9574516347653939', 'NSGA-II_crowding_distance: 0.2488784065565376', 'NSGA-II_rank: 2', 'change: 0.06582986711205491', 'is_elite: False']\n", + "Id: 80_35 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_35', 'origin': '79_37~CUW~79_48#MGNP'} Metrics: ['ELUC: -1.0294370958018542', 'NSGA-II_crowding_distance: 0.36951182611986744', 'NSGA-II_rank: 7', 'change: 0.11500341792772911', 'is_elite: False']\n", + "Id: 80_67 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_67', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_67', 'origin': '79_67~CUW~79_48#MGNP'} Metrics: ['ELUC: -1.1239480799945119', 'NSGA-II_crowding_distance: 0.7556247014409342', 'NSGA-II_rank: 6', 'change: 0.08251479878196635', 'is_elite: False']\n", + "Id: 80_44 Identity: {'ancestor_count': 2, 'ancestor_ids': ['79_67', '1_1'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_44', 'origin': '79_67~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5931281571618026', 'NSGA-II_crowding_distance: 0.20183411250994554', 'NSGA-II_rank: 1', 'change: 0.051659478330220256', 'is_elite: False']\n", + "Id: 80_85 Identity: {'ancestor_count': 78, 'ancestor_ids': ['1_1', '79_37'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_85', 'origin': '1_1~CUW~79_37#MGNP'} Metrics: ['ELUC: -2.113433630762688', 'NSGA-II_crowding_distance: 0.28672626006791424', 'NSGA-II_rank: 5', 'change: 0.07137286705954812', 'is_elite: False']\n", + "Id: 80_81 Identity: {'ancestor_count': 78, 'ancestor_ids': ['78_72', '79_73'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_81', 'origin': '78_72~CUW~79_73#MGNP'} Metrics: ['ELUC: -2.1594310059836754', 'NSGA-II_crowding_distance: 0.3405267626219759', 'NSGA-II_rank: 5', 'change: 0.08981431658931559', 'is_elite: False']\n", + "Id: 80_59 Identity: {'ancestor_count': 73, 'ancestor_ids': ['78_26', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_59', 'origin': '78_26~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.467378947193517', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3406213402701923', 'is_elite: False']\n", + "Id: 80_42 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_42', 'origin': '77_28~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.554900596281222', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2567734447740218', 'is_elite: False']\n", + "Id: 80_41 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '77_28'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_41', 'origin': '79_37~CUW~77_28#MGNP'} Metrics: ['ELUC: -2.6271505585321413', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07022776696036916', 'is_elite: False']\n", + "Id: 80_91 Identity: {'ancestor_count': 78, 'ancestor_ids': ['1_1', '79_18'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_91', 'origin': '1_1~CUW~79_18#MGNP'} Metrics: ['ELUC: -2.784263606563307', 'NSGA-II_crowding_distance: 0.9492377076274898', 'NSGA-II_rank: 7', 'change: 0.13509924461157283', 'is_elite: False']\n", + "Id: 80_94 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '79_67'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_94', 'origin': '79_37~CUW~79_67#MGNP'} Metrics: ['ELUC: -2.834576837980577', 'NSGA-II_crowding_distance: 0.30950074447600934', 'NSGA-II_rank: 3', 'change: 0.0694628090433846', 'is_elite: False']\n", + "Id: 80_82 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_70', '79_43'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_82', 'origin': '79_70~CUW~79_43#MGNP'} Metrics: ['ELUC: -2.93497681595788', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2469722100749698', 'is_elite: False']\n", + "Id: 80_14 Identity: {'ancestor_count': 76, 'ancestor_ids': ['79_67', '77_28'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_14', 'origin': '79_67~CUW~77_28#MGNP'} Metrics: ['ELUC: -3.2533421282342427', 'NSGA-II_crowding_distance: 0.29761801248514586', 'NSGA-II_rank: 3', 'change: 0.07727364254438716', 'is_elite: False']\n", + "Id: 80_75 Identity: {'ancestor_count': 78, 'ancestor_ids': ['78_26', '79_47'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_75', 'origin': '78_26~CUW~79_47#MGNP'} Metrics: ['ELUC: -3.4388440065317916', 'NSGA-II_crowding_distance: 0.39730116097280255', 'NSGA-II_rank: 2', 'change: 0.06944678550572661', 'is_elite: False']\n", + "Id: 77_28 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_28', 'origin': '76_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.515599218727335', 'NSGA-II_crowding_distance: 0.3318916431455927', 'NSGA-II_rank: 1', 'change: 0.060201876866619694', 'is_elite: True']\n", + "Id: 80_52 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_43', '79_55'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_52', 'origin': '79_43~CUW~79_55#MGNP'} Metrics: ['ELUC: -3.680578568871714', 'NSGA-II_crowding_distance: 0.33246637880787167', 'NSGA-II_rank: 5', 'change: 0.11621369271431344', 'is_elite: False']\n", + "Id: 80_63 Identity: {'ancestor_count': 78, 'ancestor_ids': ['77_28', '79_70'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_63', 'origin': '77_28~CUW~79_70#MGNP'} Metrics: ['ELUC: -3.7560750738703215', 'NSGA-II_crowding_distance: 1.2059869739805786', 'NSGA-II_rank: 8', 'change: 0.2415798904549453', 'is_elite: False']\n", + "Id: 80_86 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_47', '79_94'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_86', 'origin': '79_47~CUW~79_94#MGNP'} Metrics: ['ELUC: -4.154572737136498', 'NSGA-II_crowding_distance: 1.2336282426114416', 'NSGA-II_rank: 6', 'change: 0.1326602760781464', 'is_elite: False']\n", + "Id: 80_66 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_47', '79_37'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_66', 'origin': '79_47~CUW~79_37#MGNP'} Metrics: ['ELUC: -4.508374807556486', 'NSGA-II_crowding_distance: 0.21782010072241648', 'NSGA-II_rank: 5', 'change: 0.11981363038852717', 'is_elite: False']\n", + "Id: 80_84 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_70', '79_43'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_84', 'origin': '79_70~CUW~79_43#MGNP'} Metrics: ['ELUC: -4.6822683087668056', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27304611377254767', 'is_elite: False']\n", + "Id: 80_74 Identity: {'ancestor_count': 78, 'ancestor_ids': ['77_28', '79_43'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_74', 'origin': '77_28~CUW~79_43#MGNP'} Metrics: ['ELUC: -4.893776284476499', 'NSGA-II_crowding_distance: 0.3501214943865462', 'NSGA-II_rank: 3', 'change: 0.10956451518052951', 'is_elite: False']\n", + "Id: 80_83 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_67', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_83', 'origin': '79_67~CUW~79_48#MGNP'} Metrics: ['ELUC: -5.003251569266321', 'NSGA-II_crowding_distance: 0.5840171126617212', 'NSGA-II_rank: 4', 'change: 0.1155154284471704', 'is_elite: False']\n", + "Id: 79_37 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_41', '78_27'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_37', 'origin': '78_41~CUW~78_27#MGNP'} Metrics: ['ELUC: -5.471572710834718', 'NSGA-II_crowding_distance: 0.30389528601744586', 'NSGA-II_rank: 2', 'change: 0.08574691577329832', 'is_elite: False']\n", + "Id: 80_16 Identity: {'ancestor_count': 78, 'ancestor_ids': ['78_26', '79_73'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_16', 'origin': '78_26~CUW~79_73#MGNP'} Metrics: ['ELUC: -5.630892630511665', 'NSGA-II_crowding_distance: 0.3306611169196159', 'NSGA-II_rank: 5', 'change: 0.12894575354183238', 'is_elite: False']\n", + "Id: 80_45 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_94', '79_67'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_45', 'origin': '79_94~CUW~79_67#MGNP'} Metrics: ['ELUC: -5.715331176131343', 'NSGA-II_crowding_distance: 0.20345930083265718', 'NSGA-II_rank: 2', 'change: 0.10086318241494624', 'is_elite: False']\n", + "Id: 80_71 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_99', '1_1'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_71', 'origin': '79_99~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.766994319520505', 'NSGA-II_crowding_distance: 0.3512797818652184', 'NSGA-II_rank: 4', 'change: 0.11922402961779535', 'is_elite: False']\n", + "Id: 80_33 Identity: {'ancestor_count': 78, 'ancestor_ids': ['77_28', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_33', 'origin': '77_28~CUW~79_48#MGNP'} Metrics: ['ELUC: -5.82777994911403', 'NSGA-II_crowding_distance: 0.32039198433117855', 'NSGA-II_rank: 1', 'change: 0.0788252023385081', 'is_elite: True']\n", + "Id: 80_87 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_94', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_87', 'origin': '79_94~CUW~79_48#MGNP'} Metrics: ['ELUC: -6.457229069310995', 'NSGA-II_crowding_distance: 0.2259657556858337', 'NSGA-II_rank: 3', 'change: 0.11327125121166227', 'is_elite: False']\n", + "Id: 80_36 Identity: {'ancestor_count': 77, 'ancestor_ids': ['1_1', '78_79'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_36', 'origin': '1_1~CUW~78_79#MGNP'} Metrics: ['ELUC: -6.610200378162518', 'NSGA-II_crowding_distance: 0.7955883222280626', 'NSGA-II_rank: 7', 'change: 0.2163121979554144', 'is_elite: False']\n", + "Id: 79_48 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_28', '78_93'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_48', 'origin': '77_28~CUW~78_93#MGNP'} Metrics: ['ELUC: -6.617855234163039', 'NSGA-II_crowding_distance: 0.18822660331603952', 'NSGA-II_rank: 1', 'change: 0.10315346425724053', 'is_elite: False']\n", + "Id: 80_48 Identity: {'ancestor_count': 78, 'ancestor_ids': ['1_1', '79_70'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_48', 'origin': '1_1~CUW~79_70#MGNP'} Metrics: ['ELUC: -6.697359808019825', 'NSGA-II_crowding_distance: 0.23659363661379612', 'NSGA-II_rank: 7', 'change: 0.23424932541752533', 'is_elite: False']\n", + "Id: 80_89 Identity: {'ancestor_count': 78, 'ancestor_ids': ['1_1', '79_47'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_89', 'origin': '1_1~CUW~79_47#MGNP'} Metrics: ['ELUC: -6.75957632445668', 'NSGA-II_crowding_distance: 0.24924433487158687', 'NSGA-II_rank: 2', 'change: 0.1100283098376918', 'is_elite: False']\n", + "Id: 80_60 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_60', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.781143794210554', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.250894823375709', 'is_elite: False']\n", + "Id: 80_62 Identity: {'ancestor_count': 78, 'ancestor_ids': ['78_26', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_62', 'origin': '78_26~CUW~79_46#MGNP'} Metrics: ['ELUC: -7.128001325047879', 'NSGA-II_crowding_distance: 0.5880210567528621', 'NSGA-II_rank: 5', 'change: 0.14488044767670033', 'is_elite: False']\n", + "Id: 80_79 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_79', 'origin': '79_37~CUW~79_48#MGNP'} Metrics: ['ELUC: -7.298655039080971', 'NSGA-II_crowding_distance: 0.15639700543052265', 'NSGA-II_rank: 3', 'change: 0.1279745350459185', 'is_elite: False']\n", + "Id: 80_69 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_28', '78_72'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_69', 'origin': '77_28~CUW~78_72#MGNP'} Metrics: ['ELUC: -7.433214723563747', 'NSGA-II_crowding_distance: 0.30306400067010225', 'NSGA-II_rank: 4', 'change: 0.1331973500844338', 'is_elite: False']\n", + "Id: 80_40 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_18', '79_37'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_40', 'origin': '79_18~CUW~79_37#MGNP'} Metrics: ['ELUC: -7.542398415600555', 'NSGA-II_crowding_distance: 0.18551404349583833', 'NSGA-II_rank: 1', 'change: 0.10589022225355628', 'is_elite: False']\n", + "Id: 80_39 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_28', '78_79'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_39', 'origin': '77_28~CUW~78_79#MGNP'} Metrics: ['ELUC: -7.638058004678185', 'NSGA-II_crowding_distance: 0.2914814330353853', 'NSGA-II_rank: 7', 'change: 0.2483281459354706', 'is_elite: False']\n", + "Id: 80_72 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '79_47'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_72', 'origin': '79_37~CUW~79_47#MGNP'} Metrics: ['ELUC: -7.86993547105243', 'NSGA-II_crowding_distance: 0.4502436110611362', 'NSGA-II_rank: 4', 'change: 0.13433724715412423', 'is_elite: False']\n", + "Id: 80_76 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_43', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_76', 'origin': '79_43~CUW~79_48#MGNP'} Metrics: ['ELUC: -7.913607994846999', 'NSGA-II_crowding_distance: 0.32433233921081456', 'NSGA-II_rank: 3', 'change: 0.12899031917150197', 'is_elite: False']\n", + "Id: 79_47 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_72', '1_1'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_47', 'origin': '78_72~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.059252173636894', 'NSGA-II_crowding_distance: 0.15830105633329183', 'NSGA-II_rank: 2', 'change: 0.12007066340577863', 'is_elite: False']\n", + "Id: 80_29 Identity: {'ancestor_count': 78, 'ancestor_ids': ['2_49', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_29', 'origin': '2_49~CUW~79_46#MGNP'} Metrics: ['ELUC: -8.148317706659213', 'NSGA-II_crowding_distance: 0.18201813271875594', 'NSGA-II_rank: 7', 'change: 0.27025269771732363', 'is_elite: False']\n", + "Id: 80_38 Identity: {'ancestor_count': 78, 'ancestor_ids': ['2_49', '79_70'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_38', 'origin': '2_49~CUW~79_70#MGNP'} Metrics: ['ELUC: -8.154141043502943', 'NSGA-II_crowding_distance: 0.2730201868808977', 'NSGA-II_rank: 7', 'change: 0.27807623953508676', 'is_elite: False']\n", + "Id: 80_100 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_94', '79_37'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_100', 'origin': '79_94~CUW~79_37#MGNP'} Metrics: ['ELUC: -8.169070777635236', 'NSGA-II_crowding_distance: 0.06594112955944358', 'NSGA-II_rank: 2', 'change: 0.12331671497329905', 'is_elite: False']\n", + "Id: 80_99 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_48', '78_72'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_99', 'origin': '79_48~CUW~78_72#MGNP'} Metrics: ['ELUC: -8.498375245932907', 'NSGA-II_crowding_distance: 0.3576632809564865', 'NSGA-II_rank: 2', 'change: 0.1276420144260963', 'is_elite: False']\n", + "Id: 80_28 Identity: {'ancestor_count': 77, 'ancestor_ids': ['79_55', '78_79'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_28', 'origin': '79_55~CUW~78_79#MGNP'} Metrics: ['ELUC: -8.793611021395092', 'NSGA-II_crowding_distance: 1.2443752985590657', 'NSGA-II_rank: 6', 'change: 0.2038850448991916', 'is_elite: False']\n", + "Id: 80_49 Identity: {'ancestor_count': 77, 'ancestor_ids': ['77_28', '78_79'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_49', 'origin': '77_28~CUW~78_79#MGNP'} Metrics: ['ELUC: -8.911131603580747', 'NSGA-II_crowding_distance: 0.7107975408964138', 'NSGA-II_rank: 5', 'change: 0.1967160968484104', 'is_elite: False']\n", + "Id: 80_23 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_26', '78_79'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_23', 'origin': '78_26~CUW~78_79#MGNP'} Metrics: ['ELUC: -8.912384502838158', 'NSGA-II_crowding_distance: 0.5899279174423202', 'NSGA-II_rank: 5', 'change: 0.26349813731666305', 'is_elite: False']\n", + "Id: 80_78 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_94', '79_47'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_78', 'origin': '79_94~CUW~79_47#MGNP'} Metrics: ['ELUC: -8.998950997494239', 'NSGA-II_crowding_distance: 0.22509645016817104', 'NSGA-II_rank: 1', 'change: 0.11809879165871524', 'is_elite: False']\n", + "Id: 80_43 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_99', '1_1'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_43', 'origin': '79_99~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.031287298727342', 'NSGA-II_crowding_distance: 0.7607086579057569', 'NSGA-II_rank: 4', 'change: 0.18888232045036357', 'is_elite: False']\n", + "Id: 80_18 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '1_1'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_18', 'origin': '78_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.135705716034295', 'NSGA-II_crowding_distance: 0.7156675976551792', 'NSGA-II_rank: 4', 'change: 0.2596510644746884', 'is_elite: False']\n", + "Id: 80_55 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_55', 'origin': '79_37~CUW~79_48#MGNP'} Metrics: ['ELUC: -9.152056538639496', 'NSGA-II_crowding_distance: 0.2472617364817366', 'NSGA-II_rank: 1', 'change: 0.14573759217532567', 'is_elite: True']\n", + "Id: 80_54 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_46', '77_28'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_54', 'origin': '79_46~CUW~77_28#MGNP'} Metrics: ['ELUC: -9.387129693418652', 'NSGA-II_crowding_distance: 0.4366647485272729', 'NSGA-II_rank: 3', 'change: 0.17390113181428507', 'is_elite: False']\n", + "Id: 80_56 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_70', '78_72'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_56', 'origin': '79_70~CUW~78_72#MGNP'} Metrics: ['ELUC: -9.633176975179534', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.30163208045253553', 'is_elite: False']\n", + "Id: 80_34 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '77_28'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_34', 'origin': '78_79~CUW~77_28#MGNP'} Metrics: ['ELUC: -10.099704968251759', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.28986609663988594', 'is_elite: False']\n", + "Id: 80_26 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_73', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_26', 'origin': '79_73~CUW~79_46#MGNP'} Metrics: ['ELUC: -10.445671665251552', 'NSGA-II_crowding_distance: 0.17337353798153965', 'NSGA-II_rank: 3', 'change: 0.19482557128612946', 'is_elite: False']\n", + "Id: 80_80 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_73', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_80', 'origin': '79_73~CUW~79_46#MGNP'} Metrics: ['ELUC: -10.74219647881553', 'NSGA-II_crowding_distance: 0.3656755754653438', 'NSGA-II_rank: 3', 'change: 0.1950372755281149', 'is_elite: False']\n", + "Id: 80_88 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_43', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_88', 'origin': '79_43~CUW~79_46#MGNP'} Metrics: ['ELUC: -10.917891013070024', 'NSGA-II_crowding_distance: 0.5334288741052396', 'NSGA-II_rank: 2', 'change: 0.15933479497366038', 'is_elite: False']\n", + "Id: 80_21 Identity: {'ancestor_count': 78, 'ancestor_ids': ['2_49', '79_70'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_21', 'origin': '2_49~CUW~79_70#MGNP'} Metrics: ['ELUC: -11.32369636567985', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2794861892601111', 'is_elite: False']\n", + "Id: 80_17 Identity: {'ancestor_count': 78, 'ancestor_ids': ['78_72', '79_43'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_17', 'origin': '78_72~CUW~79_43#MGNP'} Metrics: ['ELUC: -11.379559533478732', 'NSGA-II_crowding_distance: 0.2877203017319725', 'NSGA-II_rank: 1', 'change: 0.1514765229593359', 'is_elite: True']\n", + "Id: 80_51 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_94', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_51', 'origin': '79_94~CUW~79_46#MGNP'} Metrics: ['ELUC: -11.83478264161479', 'NSGA-II_crowding_distance: 0.5336650671075267', 'NSGA-II_rank: 2', 'change: 0.19185966921458514', 'is_elite: False']\n", + "Id: 80_73 Identity: {'ancestor_count': 78, 'ancestor_ids': ['2_49', '79_18'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_73', 'origin': '2_49~CUW~79_18#MGNP'} Metrics: ['ELUC: -11.856200793065607', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.271193540588255', 'is_elite: False']\n", + "Id: 80_61 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_47', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_61', 'origin': '79_47~CUW~79_46#MGNP'} Metrics: ['ELUC: -12.243893944888661', 'NSGA-II_crowding_distance: 0.47406432760814865', 'NSGA-II_rank: 1', 'change: 0.17911748459585827', 'is_elite: True']\n", + "Id: 80_13 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_62', '1_1'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_13', 'origin': '79_62~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.75993776225887', 'NSGA-II_crowding_distance: 0.49026726867605075', 'NSGA-II_rank: 3', 'change: 0.24718488687838858', 'is_elite: False']\n", + "Id: 80_90 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_70', '79_67'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_90', 'origin': '79_70~CUW~79_67#MGNP'} Metrics: ['ELUC: -12.872767532376097', 'NSGA-II_crowding_distance: 0.4685337745453605', 'NSGA-II_rank: 2', 'change: 0.24260537946727134', 'is_elite: False']\n", + "Id: 80_37 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_62', '79_70'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_37', 'origin': '79_62~CUW~79_70#MGNP'} Metrics: ['ELUC: -13.774169864418793', 'NSGA-II_crowding_distance: 0.2690257050128281', 'NSGA-II_rank: 3', 'change: 0.26624911491107084', 'is_elite: False']\n", + "Id: 80_11 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_70', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_11', 'origin': '79_70~CUW~79_48#MGNP'} Metrics: ['ELUC: -14.178987819369995', 'NSGA-II_crowding_distance: 0.23799342670391194', 'NSGA-II_rank: 3', 'change: 0.28976159165820653', 'is_elite: False']\n", + "Id: 80_30 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_48', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_30', 'origin': '79_48~CUW~79_46#MGNP'} Metrics: ['ELUC: -14.790112289449574', 'NSGA-II_crowding_distance: 0.4077991197815229', 'NSGA-II_rank: 1', 'change: 0.23504862220522685', 'is_elite: True']\n", + "Id: 80_15 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '79_18'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_15', 'origin': '79_37~CUW~79_18#MGNP'} Metrics: ['ELUC: -15.036136331407066', 'NSGA-II_crowding_distance: 0.2323430605606631', 'NSGA-II_rank: 2', 'change: 0.2445391575058725', 'is_elite: False']\n", + "Id: 80_58 Identity: {'ancestor_count': 78, 'ancestor_ids': ['2_49', '79_62'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_58', 'origin': '2_49~CUW~79_62#MGNP'} Metrics: ['ELUC: -15.08574116322538', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30311047006517694', 'is_elite: False']\n", + "Id: 80_20 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_18', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_20', 'origin': '79_18~CUW~79_46#MGNP'} Metrics: ['ELUC: -15.603536108545018', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.25300259151924587', 'is_elite: False']\n", + "Id: 79_46 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_93', '78_27'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_46', 'origin': '78_93~CUW~78_27#MGNP'} Metrics: ['ELUC: -15.662605280923191', 'NSGA-II_crowding_distance: 0.25288322817893505', 'NSGA-II_rank: 1', 'change: 0.24277906897011056', 'is_elite: True']\n", + "Id: 78_79 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_55', '77_75'], 'birth_generation': 78, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '78_79', 'origin': '77_55~CUW~77_75#MGNP'} Metrics: ['ELUC: -16.21059339499776', 'NSGA-II_crowding_distance: 0.21027189455184656', 'NSGA-II_rank: 1', 'change: 0.28639733972472264', 'is_elite: False']\n", + "Id: 80_77 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_62', '79_70'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_77', 'origin': '79_62~CUW~79_70#MGNP'} Metrics: ['ELUC: -16.55931030718559', 'NSGA-II_crowding_distance: 0.05745051427845374', 'NSGA-II_rank: 1', 'change: 0.2903021556320019', 'is_elite: False']\n", + "Id: 80_93 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_18', '79_70'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_93', 'origin': '79_18~CUW~79_70#MGNP'} Metrics: ['ELUC: -16.71790534354053', 'NSGA-II_crowding_distance: 0.1011242479810043', 'NSGA-II_rank: 1', 'change: 0.2949300527606708', 'is_elite: False']\n", + "Id: 80_22 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_22', 'origin': '78_79~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.58906053483023', 'NSGA-II_crowding_distance: 0.07710112097931367', 'NSGA-II_rank: 1', 'change: 0.3030001989132084', 'is_elite: False']\n", + "Id: 80_50 Identity: {'ancestor_count': 77, 'ancestor_ids': ['79_55', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_50', 'origin': '79_55~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.5969364138529', 'NSGA-II_crowding_distance: 0.000541471921013265', 'NSGA-II_rank: 1', 'change: 0.3030178808617514', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 79_70 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_100', '78_41'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_70', 'origin': '78_100~CUW~78_41#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 80_65 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_65', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 80_92 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_70', '79_70'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_92', 'origin': '79_70~CUW~79_70#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 80_96 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_96', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 80.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 81...:\n", + "PopulationResponse:\n", + " Generation: 81\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/81/20240220-052615\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 81 and asking ESP for generation 82...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 81 data persisted.\n", + "Evaluated candidates:\n", + "Id: 81_36 Identity: {'ancestor_count': 3, 'ancestor_ids': ['80_96', '80_44'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_36', 'origin': '80_96~CUW~80_44#MGNP'} Metrics: ['ELUC: 20.508894382219847', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.29004310647081527', 'is_elite: False']\n", + "Id: 81_61 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_61', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: 8.052130092108714', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.25792025974515304', 'is_elite: False']\n", + "Id: 81_65 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_78', '80_93'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_65', 'origin': '80_78~CUW~80_93#MGNP'} Metrics: ['ELUC: 5.372661906588276', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.21990904438054235', 'is_elite: False']\n", + "Id: 81_77 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_30'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_77', 'origin': '1_1~CUW~80_30#MGNP'} Metrics: ['ELUC: 4.480718044362467', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07256174933362436', 'is_elite: False']\n", + "Id: 81_19 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '1_1'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_19', 'origin': '80_61~CUW~1_1#MGNP'} Metrics: ['ELUC: 3.882020030387998', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11539357607991427', 'is_elite: False']\n", + "Id: 81_14 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_17', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_14', 'origin': '80_17~CUW~80_96#MGNP'} Metrics: ['ELUC: 1.8198057903803377', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.33068235670981105', 'is_elite: False']\n", + "Id: 81_62 Identity: {'ancestor_count': 74, 'ancestor_ids': ['80_95', '1_1'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_62', 'origin': '80_95~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.1331109955193275', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03938166192001844', 'is_elite: False']\n", + "Id: 81_93 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_40'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_93', 'origin': '1_1~CUW~80_40#MGNP'} Metrics: ['ELUC: 1.0603288128542259', 'NSGA-II_crowding_distance: 0.6467271729959942', 'NSGA-II_rank: 5', 'change: 0.07834699640398131', 'is_elite: False']\n", + "Id: 81_34 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_78'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_34', 'origin': '1_1~CUW~80_78#MGNP'} Metrics: ['ELUC: 0.8286372097720623', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06325916870989212', 'is_elite: False']\n", + "Id: 81_78 Identity: {'ancestor_count': 73, 'ancestor_ids': ['1_1', '78_26'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_78', 'origin': '1_1~CUW~78_26#MGNP'} Metrics: ['ELUC: 0.7268913387256583', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03316356895032533', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 81_83 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '80_44'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_83', 'origin': '1_1~CUW~80_44#MGNP'} Metrics: ['ELUC: -0.17533652053397208', 'NSGA-II_crowding_distance: 0.13395041152234058', 'NSGA-II_rank: 3', 'change: 0.05286867367542159', 'is_elite: False']\n", + "Id: 81_99 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_99', 'origin': '80_30~CUW~77_28#MGNP'} Metrics: ['ELUC: -0.18367581639887126', 'NSGA-II_crowding_distance: 0.2783583058893939', 'NSGA-II_rank: 3', 'change: 0.055904896324820846', 'is_elite: False']\n", + "Id: 81_12 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_96', '80_17'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_12', 'origin': '80_96~CUW~80_17#MGNP'} Metrics: ['ELUC: -0.5312748495248805', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23842341148438495', 'is_elite: False']\n", + "Id: 81_72 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_96', '80_55'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_72', 'origin': '80_96~CUW~80_55#MGNP'} Metrics: ['ELUC: -0.6020493386379148', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2381572253006621', 'is_elite: False']\n", + "Id: 81_67 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '1_1'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_67', 'origin': '80_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9788627192273901', 'NSGA-II_crowding_distance: 0.1521426862100738', 'NSGA-II_rank: 2', 'change: 0.04038170149287962', 'is_elite: False']\n", + "Id: 81_51 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '78_26'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_51', 'origin': '77_28~CUW~78_26#MGNP'} Metrics: ['ELUC: -1.01616521621348', 'NSGA-II_crowding_distance: 0.1578329212342475', 'NSGA-II_rank: 2', 'change: 0.047725592210315394', 'is_elite: False']\n", + "Id: 81_11 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_17', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_11', 'origin': '80_17~CUW~80_96#MGNP'} Metrics: ['ELUC: -1.1994239765016586', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.21868827314289427', 'is_elite: False']\n", + "Id: 81_96 Identity: {'ancestor_count': 76, 'ancestor_ids': ['77_28', '2_49'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_96', 'origin': '77_28~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.034623227819866', 'NSGA-II_crowding_distance: 0.8746937762381337', 'NSGA-II_rank: 7', 'change: 0.2617966569425906', 'is_elite: False']\n", + "Id: 81_81 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_40', '1_1'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_81', 'origin': '80_40~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0400692419325464', 'NSGA-II_crowding_distance: 0.4179062877756232', 'NSGA-II_rank: 4', 'change: 0.10271919341296079', 'is_elite: False']\n", + "Id: 81_29 Identity: {'ancestor_count': 3, 'ancestor_ids': ['80_44', '1_1'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_29', 'origin': '80_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.079239788663608', 'NSGA-II_crowding_distance: 0.18596668043521203', 'NSGA-II_rank: 2', 'change: 0.06606662104958103', 'is_elite: False']\n", + "Id: 81_95 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_78'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_95', 'origin': '1_1~CUW~80_78#MGNP'} Metrics: ['ELUC: -2.083618656113992', 'NSGA-II_crowding_distance: 0.283156107327437', 'NSGA-II_rank: 1', 'change: 0.03614901748277748', 'is_elite: True']\n", + "Id: 81_48 Identity: {'ancestor_count': 73, 'ancestor_ids': ['78_26', '80_44'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_48', 'origin': '78_26~CUW~80_44#MGNP'} Metrics: ['ELUC: -2.266459336253464', 'NSGA-II_crowding_distance: 0.13844388569598018', 'NSGA-II_rank: 1', 'change: 0.050923069709636386', 'is_elite: False']\n", + "Id: 81_23 Identity: {'ancestor_count': 77, 'ancestor_ids': ['1_1', '78_79'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_23', 'origin': '1_1~CUW~78_79#MGNP'} Metrics: ['ELUC: -2.3330326192860777', 'NSGA-II_crowding_distance: 1.4749510237904708', 'NSGA-II_rank: 6', 'change: 0.19319932248927957', 'is_elite: False']\n", + "Id: 81_97 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '78_26'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_97', 'origin': '80_30~CUW~78_26#MGNP'} Metrics: ['ELUC: -2.33826424004989', 'NSGA-II_crowding_distance: 0.15974498651647256', 'NSGA-II_rank: 4', 'change: 0.11087456749280887', 'is_elite: False']\n", + "Id: 81_35 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_35', 'origin': '80_55~CUW~77_28#MGNP'} Metrics: ['ELUC: -2.4461217287781487', 'NSGA-II_crowding_distance: 0.07273492617342174', 'NSGA-II_rank: 2', 'change: 0.07599480305008362', 'is_elite: False']\n", + "Id: 81_13 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_95', '80_30'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_13', 'origin': '80_95~CUW~80_30#MGNP'} Metrics: ['ELUC: -2.5223785462884165', 'NSGA-II_crowding_distance: 0.35108632318491884', 'NSGA-II_rank: 3', 'change: 0.09291717628810958', 'is_elite: False']\n", + "Id: 81_26 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_26', 'origin': '80_30~CUW~77_28#MGNP'} Metrics: ['ELUC: -2.6221626323138567', 'NSGA-II_crowding_distance: 0.10393364223973789', 'NSGA-II_rank: 2', 'change: 0.07736768455069123', 'is_elite: False']\n", + "Id: 81_92 Identity: {'ancestor_count': 79, 'ancestor_ids': ['78_26', '80_17'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_92', 'origin': '78_26~CUW~80_17#MGNP'} Metrics: ['ELUC: -2.7280542696004226', 'NSGA-II_crowding_distance: 0.8312634508223629', 'NSGA-II_rank: 5', 'change: 0.12137015548405027', 'is_elite: False']\n", + "Id: 81_86 Identity: {'ancestor_count': 79, 'ancestor_ids': ['2_49', '80_78'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_86', 'origin': '2_49~CUW~80_78#MGNP'} Metrics: ['ELUC: -3.2082343264187743', 'NSGA-II_crowding_distance: 0.6005292101115827', 'NSGA-II_rank: 7', 'change: 0.26422824193993993', 'is_elite: False']\n", + "Id: 81_44 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '78_26'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_44', 'origin': '80_55~CUW~78_26#MGNP'} Metrics: ['ELUC: -3.271012337098035', 'NSGA-II_crowding_distance: 0.3669224528257282', 'NSGA-II_rank: 4', 'change: 0.12059550610307446', 'is_elite: False']\n", + "Id: 81_53 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_33'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_53', 'origin': '1_1~CUW~80_33#MGNP'} Metrics: ['ELUC: -3.326945247608536', 'NSGA-II_crowding_distance: 0.10214266830003998', 'NSGA-II_rank: 1', 'change: 0.056357952254699355', 'is_elite: False']\n", + "Id: 77_28 Identity: {'ancestor_count': 75, 'ancestor_ids': ['76_44', '1_1'], 'birth_generation': 77, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '77_28', 'origin': '76_44~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.515599218727335', 'NSGA-II_crowding_distance: 0.14968541725429615', 'NSGA-II_rank: 1', 'change: 0.060201876866619694', 'is_elite: False']\n", + "Id: 81_82 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_93', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_82', 'origin': '80_93~CUW~80_61#MGNP'} Metrics: ['ELUC: -3.8167710297340363', 'NSGA-II_crowding_distance: 0.6622492111673075', 'NSGA-II_rank: 5', 'change: 0.1943168337501205', 'is_elite: False']\n", + "Id: 81_55 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_55', 'origin': '80_33~CUW~77_28#MGNP'} Metrics: ['ELUC: -3.869097155820678', 'NSGA-II_crowding_distance: 0.15497788864185236', 'NSGA-II_rank: 2', 'change: 0.0824721058148266', 'is_elite: False']\n", + "Id: 81_47 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_44'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_47', 'origin': '80_30~CUW~80_44#MGNP'} Metrics: ['ELUC: -3.896904543647357', 'NSGA-II_crowding_distance: 0.15441789713556373', 'NSGA-II_rank: 3', 'change: 0.09537001425678422', 'is_elite: False']\n", + "Id: 81_85 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_85', 'origin': '80_61~CUW~77_28#MGNP'} Metrics: ['ELUC: -4.00570131538566', 'NSGA-II_crowding_distance: 0.27704692900790123', 'NSGA-II_rank: 3', 'change: 0.11247376878522251', 'is_elite: False']\n", + "Id: 81_73 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_30'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_73', 'origin': '1_1~CUW~80_30#MGNP'} Metrics: ['ELUC: -4.3735495527158905', 'NSGA-II_crowding_distance: 0.13746200750356818', 'NSGA-II_rank: 2', 'change: 0.09256199197594074', 'is_elite: False']\n", + "Id: 81_42 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '80_33'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_42', 'origin': '80_33~CUW~80_33#MGNP'} Metrics: ['ELUC: -4.967752663815606', 'NSGA-II_crowding_distance: 0.1939211349209528', 'NSGA-II_rank: 1', 'change: 0.0731757374328627', 'is_elite: False']\n", + "Id: 81_39 Identity: {'ancestor_count': 79, 'ancestor_ids': ['77_28', '80_78'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_39', 'origin': '77_28~CUW~80_78#MGNP'} Metrics: ['ELUC: -5.535668758061823', 'NSGA-II_crowding_distance: 0.19162230313885503', 'NSGA-II_rank: 2', 'change: 0.09425854136786221', 'is_elite: False']\n", + "Id: 80_33 Identity: {'ancestor_count': 78, 'ancestor_ids': ['77_28', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_33', 'origin': '77_28~CUW~79_48#MGNP'} Metrics: ['ELUC: -5.82777994911403', 'NSGA-II_crowding_distance: 0.3076198900138667', 'NSGA-II_rank: 1', 'change: 0.0788252023385081', 'is_elite: True']\n", + "Id: 81_66 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_78', '80_93'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_66', 'origin': '80_78~CUW~80_93#MGNP'} Metrics: ['ELUC: -6.035179129272586', 'NSGA-II_crowding_distance: 0.8845315426530405', 'NSGA-II_rank: 6', 'change: 0.26267345093072403', 'is_elite: False']\n", + "Id: 81_74 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_74', 'origin': '80_61~CUW~80_96#MGNP'} Metrics: ['ELUC: -6.342958794940151', 'NSGA-II_crowding_distance: 1.1253062237618663', 'NSGA-II_rank: 7', 'change: 0.26843824439861774', 'is_elite: False']\n", + "Id: 81_25 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_25', 'origin': '80_61~CUW~77_28#MGNP'} Metrics: ['ELUC: -6.344383965376598', 'NSGA-II_crowding_distance: 0.18947497232090682', 'NSGA-II_rank: 2', 'change: 0.11425803963409092', 'is_elite: False']\n", + "Id: 81_57 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_93'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_57', 'origin': '1_1~CUW~80_93#MGNP'} Metrics: ['ELUC: -6.570580162185145', 'NSGA-II_crowding_distance: 0.684355224774057', 'NSGA-II_rank: 5', 'change: 0.21428177101209836', 'is_elite: False']\n", + "Id: 81_49 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_55'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_49', 'origin': '80_30~CUW~80_55#MGNP'} Metrics: ['ELUC: -6.771169947953497', 'NSGA-II_crowding_distance: 0.4731347932406941', 'NSGA-II_rank: 4', 'change: 0.12637076271855507', 'is_elite: False']\n", + "Id: 81_28 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_28', 'origin': '80_61~CUW~77_28#MGNP'} Metrics: ['ELUC: -6.973595949343149', 'NSGA-II_crowding_distance: 0.22102236398323552', 'NSGA-II_rank: 3', 'change: 0.12436262370328972', 'is_elite: False']\n", + "Id: 81_54 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '1_1'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_54', 'origin': '80_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.134418936782306', 'NSGA-II_crowding_distance: 0.0805590032723572', 'NSGA-II_rank: 3', 'change: 0.12571205929045517', 'is_elite: False']\n", + "Id: 81_59 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_59', 'origin': '80_30~CUW~80_61#MGNP'} Metrics: ['ELUC: -7.374452280047497', 'NSGA-II_crowding_distance: 0.09248035936123707', 'NSGA-II_rank: 3', 'change: 0.1400374212042719', 'is_elite: False']\n", + "Id: 81_88 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_88', 'origin': '80_55~CUW~77_28#MGNP'} Metrics: ['ELUC: -7.5291867362634814', 'NSGA-II_crowding_distance: 0.12192988404234109', 'NSGA-II_rank: 2', 'change: 0.11504244597734412', 'is_elite: False']\n", + "Id: 81_64 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_44', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_64', 'origin': '80_44~CUW~80_61#MGNP'} Metrics: ['ELUC: -7.558947211835571', 'NSGA-II_crowding_distance: 0.10631474335389172', 'NSGA-II_rank: 2', 'change: 0.12865335911079387', 'is_elite: False']\n", + "Id: 81_58 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '80_33'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_58', 'origin': '80_55~CUW~80_33#MGNP'} Metrics: ['ELUC: -7.676392394668442', 'NSGA-II_crowding_distance: 0.11876906758473674', 'NSGA-II_rank: 3', 'change: 0.1425063770002658', 'is_elite: False']\n", + "Id: 81_70 Identity: {'ancestor_count': 79, 'ancestor_ids': ['79_46', '80_55'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_70', 'origin': '79_46~CUW~80_55#MGNP'} Metrics: ['ELUC: -7.944500436954415', 'NSGA-II_crowding_distance: 0.20359828094181592', 'NSGA-II_rank: 2', 'change: 0.1372135862736436', 'is_elite: False']\n", + "Id: 81_20 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_33'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_20', 'origin': '80_30~CUW~80_33#MGNP'} Metrics: ['ELUC: -8.244788742135801', 'NSGA-II_crowding_distance: 0.3600822316090363', 'NSGA-II_rank: 1', 'change: 0.10935034498458633', 'is_elite: True']\n", + "Id: 81_37 Identity: {'ancestor_count': 79, 'ancestor_ids': ['79_46', '80_33'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_37', 'origin': '79_46~CUW~80_33#MGNP'} Metrics: ['ELUC: -8.413571824878002', 'NSGA-II_crowding_distance: 0.24239223378001062', 'NSGA-II_rank: 4', 'change: 0.14970957384747036', 'is_elite: False']\n", + "Id: 81_60 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_44', '80_17'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_60', 'origin': '80_44~CUW~80_17#MGNP'} Metrics: ['ELUC: -8.52259400943482', 'NSGA-II_crowding_distance: 0.06255337152444299', 'NSGA-II_rank: 4', 'change: 0.15534870850803165', 'is_elite: False']\n", + "Id: 81_94 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_94', 'origin': '80_33~CUW~80_61#MGNP'} Metrics: ['ELUC: -8.697546859839363', 'NSGA-II_crowding_distance: 0.27943335401855185', 'NSGA-II_rank: 1', 'change: 0.13756488674738657', 'is_elite: True']\n", + "Id: 81_76 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '80_17'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_76', 'origin': '80_61~CUW~80_17#MGNP'} Metrics: ['ELUC: -8.763468290406124', 'NSGA-II_crowding_distance: 0.7010156354289957', 'NSGA-II_rank: 4', 'change: 0.15881334148039544', 'is_elite: False']\n", + "Id: 81_50 Identity: {'ancestor_count': 78, 'ancestor_ids': ['80_96', '79_48'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_50', 'origin': '80_96~CUW~79_48#MGNP'} Metrics: ['ELUC: -8.96498349517388', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.29459603213256835', 'is_elite: False']\n", + "Id: 80_55 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_37', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_55', 'origin': '79_37~CUW~79_48#MGNP'} Metrics: ['ELUC: -9.152056538639496', 'NSGA-II_crowding_distance: 0.32910902128117836', 'NSGA-II_rank: 3', 'change: 0.14573759217532567', 'is_elite: False']\n", + "Id: 81_98 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '2_49'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_98', 'origin': '80_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.554830524604153', 'NSGA-II_crowding_distance: 0.525048976209529', 'NSGA-II_rank: 6', 'change: 0.26749858949796285', 'is_elite: False']\n", + "Id: 81_100 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_100', 'origin': '1_1~CUW~80_96#MGNP'} Metrics: ['ELUC: -9.689237873181037', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2900586304388839', 'is_elite: False']\n", + "Id: 81_17 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '79_46'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_17', 'origin': '80_61~CUW~79_46#MGNP'} Metrics: ['ELUC: -10.375939215825168', 'NSGA-II_crowding_distance: 0.2457507223571218', 'NSGA-II_rank: 2', 'change: 0.14090123827888076', 'is_elite: False']\n", + "Id: 81_79 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_79', '77_28'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_79', 'origin': '78_79~CUW~77_28#MGNP'} Metrics: ['ELUC: -10.848670014716003', 'NSGA-II_crowding_distance: 0.5768301410829839', 'NSGA-II_rank: 5', 'change: 0.25319817815177276', 'is_elite: False']\n", + "Id: 81_21 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_17', '80_40'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_21', 'origin': '80_17~CUW~80_40#MGNP'} Metrics: ['ELUC: -11.326205215281089', 'NSGA-II_crowding_distance: 0.42093263265211994', 'NSGA-II_rank: 3', 'change: 0.1770212230577147', 'is_elite: False']\n", + "Id: 80_17 Identity: {'ancestor_count': 78, 'ancestor_ids': ['78_72', '79_43'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_17', 'origin': '78_72~CUW~79_43#MGNP'} Metrics: ['ELUC: -11.379559533478732', 'NSGA-II_crowding_distance: 0.2477544985185483', 'NSGA-II_rank: 2', 'change: 0.1514765229593359', 'is_elite: False']\n", + "Id: 81_16 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_16', 'origin': '1_1~CUW~80_96#MGNP'} Metrics: ['ELUC: -11.419439640354582', 'NSGA-II_crowding_distance: 0.15811563716576785', 'NSGA-II_rank: 5', 'change: 0.2769904153975834', 'is_elite: False']\n", + "Id: 81_46 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_17', '80_55'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_46', 'origin': '80_17~CUW~80_55#MGNP'} Metrics: ['ELUC: -11.468734660651027', 'NSGA-II_crowding_distance: 0.2945242744311524', 'NSGA-II_rank: 1', 'change: 0.13801567472251197', 'is_elite: True']\n", + "Id: 81_45 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_45', 'origin': '80_33~CUW~80_96#MGNP'} Metrics: ['ELUC: -11.495089542298167', 'NSGA-II_crowding_distance: 0.11419347475371441', 'NSGA-II_rank: 5', 'change: 0.27866866109358224', 'is_elite: False']\n", + "Id: 81_75 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_96', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_75', 'origin': '80_96~CUW~80_61#MGNP'} Metrics: ['ELUC: -11.915437512505585', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.28924095045667897', 'is_elite: False']\n", + "Id: 81_15 Identity: {'ancestor_count': 78, 'ancestor_ids': ['77_28', '79_46'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_15', 'origin': '77_28~CUW~79_46#MGNP'} Metrics: ['ELUC: -12.102684472893138', 'NSGA-II_crowding_distance: 0.3877457785169783', 'NSGA-II_rank: 3', 'change: 0.21508058450468442', 'is_elite: False']\n", + "Id: 80_61 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_47', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_61', 'origin': '79_47~CUW~79_46#MGNP'} Metrics: ['ELUC: -12.243893944888661', 'NSGA-II_crowding_distance: 0.46121740082790885', 'NSGA-II_rank: 2', 'change: 0.17911748459585827', 'is_elite: False']\n", + "Id: 81_22 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '80_17'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_22', 'origin': '80_55~CUW~80_17#MGNP'} Metrics: ['ELUC: -12.502269198677512', 'NSGA-II_crowding_distance: 0.3624802347816174', 'NSGA-II_rank: 1', 'change: 0.16087705599631114', 'is_elite: True']\n", + "Id: 81_31 Identity: {'ancestor_count': 79, 'ancestor_ids': ['2_49', '80_17'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_31', 'origin': '2_49~CUW~80_17#MGNP'} Metrics: ['ELUC: -12.887505288302979', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28324073866821003', 'is_elite: False']\n", + "Id: 81_87 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_93'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_87', 'origin': '80_30~CUW~80_93#MGNP'} Metrics: ['ELUC: -13.57479420996435', 'NSGA-II_crowding_distance: 0.9416622860659298', 'NSGA-II_rank: 4', 'change: 0.2393626789161233', 'is_elite: False']\n", + "Id: 81_43 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_43', 'origin': '80_30~CUW~80_61#MGNP'} Metrics: ['ELUC: -13.773676108294445', 'NSGA-II_crowding_distance: 0.32021227612348263', 'NSGA-II_rank: 1', 'change: 0.20705613200662631', 'is_elite: True']\n", + "Id: 81_33 Identity: {'ancestor_count': 78, 'ancestor_ids': ['80_22', '1_1'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_33', 'origin': '80_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.905030930436395', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2978604160722468', 'is_elite: False']\n", + "Id: 81_89 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_30'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_89', 'origin': '80_30~CUW~80_30#MGNP'} Metrics: ['ELUC: -14.594405423236797', 'NSGA-II_crowding_distance: 0.22197683647412758', 'NSGA-II_rank: 3', 'change: 0.23282485881932077', 'is_elite: False']\n", + "Id: 80_30 Identity: {'ancestor_count': 78, 'ancestor_ids': ['79_48', '79_46'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_30', 'origin': '79_48~CUW~79_46#MGNP'} Metrics: ['ELUC: -14.790112289449574', 'NSGA-II_crowding_distance: 0.3612043680782951', 'NSGA-II_rank: 3', 'change: 0.23504862220522685', 'is_elite: False']\n", + "Id: 81_80 Identity: {'ancestor_count': 78, 'ancestor_ids': ['1_1', '79_46'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_80', 'origin': '1_1~CUW~79_46#MGNP'} Metrics: ['ELUC: -14.857495018864272', 'NSGA-II_crowding_distance: 0.46140638117172617', 'NSGA-II_rank: 2', 'change: 0.22261102008753633', 'is_elite: False']\n", + "Id: 81_91 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '79_46'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_91', 'origin': '80_55~CUW~79_46#MGNP'} Metrics: ['ELUC: -14.860784225793289', 'NSGA-II_crowding_distance: 0.16987001709419447', 'NSGA-II_rank: 1', 'change: 0.2163965362315079', 'is_elite: False']\n", + "Id: 81_69 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_17', '80_30'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_69', 'origin': '80_17~CUW~80_30#MGNP'} Metrics: ['ELUC: -15.323694515792564', 'NSGA-II_crowding_distance: 0.13402369283403462', 'NSGA-II_rank: 1', 'change: 0.23143726940659123', 'is_elite: False']\n", + "Id: 79_46 Identity: {'ancestor_count': 77, 'ancestor_ids': ['78_93', '78_27'], 'birth_generation': 79, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '79_46', 'origin': '78_93~CUW~78_27#MGNP'} Metrics: ['ELUC: -15.662605280923191', 'NSGA-II_crowding_distance: 0.08539308871162522', 'NSGA-II_rank: 1', 'change: 0.24277906897011056', 'is_elite: False']\n", + "Id: 81_90 Identity: {'ancestor_count': 79, 'ancestor_ids': ['79_46', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_90', 'origin': '79_46~CUW~80_61#MGNP'} Metrics: ['ELUC: -15.802313018667324', 'NSGA-II_crowding_distance: 0.39410699158068757', 'NSGA-II_rank: 2', 'change: 0.24909969528589587', 'is_elite: False']\n", + "Id: 81_84 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '79_46'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_84', 'origin': '80_55~CUW~79_46#MGNP'} Metrics: ['ELUC: -15.824080411206477', 'NSGA-II_crowding_distance: 0.09155948276247244', 'NSGA-II_rank: 1', 'change: 0.24842496119158394', 'is_elite: False']\n", + "Id: 81_41 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_61', '80_30'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_41', 'origin': '80_61~CUW~80_30#MGNP'} Metrics: ['ELUC: -16.216589441935806', 'NSGA-II_crowding_distance: 0.08010067509149134', 'NSGA-II_rank: 1', 'change: 0.26069709623344534', 'is_elite: False']\n", + "Id: 81_52 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_93', '80_55'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_52', 'origin': '80_93~CUW~80_55#MGNP'} Metrics: ['ELUC: -16.297321329840063', 'NSGA-II_crowding_distance: 0.05585327032625141', 'NSGA-II_rank: 1', 'change: 0.2642941733182567', 'is_elite: False']\n", + "Id: 81_68 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_68', 'origin': '80_30~CUW~80_61#MGNP'} Metrics: ['ELUC: -16.553386271420873', 'NSGA-II_crowding_distance: 0.16249498293220982', 'NSGA-II_rank: 1', 'change: 0.2716469213873246', 'is_elite: False']\n", + "Id: 81_63 Identity: {'ancestor_count': 79, 'ancestor_ids': ['2_49', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_63', 'origin': '2_49~CUW~80_61#MGNP'} Metrics: ['ELUC: -16.615652283217372', 'NSGA-II_crowding_distance: 0.39567879630149794', 'NSGA-II_rank: 3', 'change: 0.2998211413053213', 'is_elite: False']\n", + "Id: 81_71 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_96', '80_93'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_71', 'origin': '80_96~CUW~80_93#MGNP'} Metrics: ['ELUC: -16.835865292540788', 'NSGA-II_crowding_distance: 0.265602135512727', 'NSGA-II_rank: 2', 'change: 0.29824160069198913', 'is_elite: False']\n", + "Id: 81_32 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_96', '80_40'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_32', 'origin': '80_96~CUW~80_40#MGNP'} Metrics: ['ELUC: -17.105023652228102', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30696107542723017', 'is_elite: False']\n", + "Id: 81_40 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_40', 'origin': '80_55~CUW~80_96#MGNP'} Metrics: ['ELUC: -17.134699311652206', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30008324375967804', 'is_elite: False']\n", + "Id: 81_30 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_78', '2_49'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_30', 'origin': '80_78~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.210563579211676', 'NSGA-II_crowding_distance: 0.16418844877130354', 'NSGA-II_rank: 1', 'change: 0.2972810525188868', 'is_elite: False']\n", + "Id: 81_56 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_56', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59484823548728', 'NSGA-II_crowding_distance: 0.04122216171653059', 'NSGA-II_rank: 1', 'change: 0.3029631649828288', 'is_elite: False']\n", + "Id: 81_27 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_27', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59723023197059', 'NSGA-II_crowding_distance: 0.00033641259383675366', 'NSGA-II_rank: 1', 'change: 0.3030189746578248', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 80_96 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_96', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 81_18 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_18', 'origin': '2_49~CUW~80_96#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 81_24 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_17', '2_49'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_24', 'origin': '80_17~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 81_38 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_38', 'origin': '80_33~CUW~80_96#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 81.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 82...:\n", + "PopulationResponse:\n", + " Generation: 82\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/82/20240220-053330\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 82 and asking ESP for generation 83...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 82 data persisted.\n", + "Evaluated candidates:\n", + "Id: 82_99 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '1_1'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_99', 'origin': '81_38~CUW~1_1#MGNP'} Metrics: ['ELUC: 21.44314559111994', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.28887746602181236', 'is_elite: False']\n", + "Id: 82_63 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_42', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_63', 'origin': '81_42~CUW~81_38#MGNP'} Metrics: ['ELUC: 9.811261931380631', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.23894357339702352', 'is_elite: False']\n", + "Id: 82_58 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_42', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_58', 'origin': '81_42~CUW~81_38#MGNP'} Metrics: ['ELUC: 2.2747568184122082', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.22426427829319373', 'is_elite: False']\n", + "Id: 82_29 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '81_95'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_29', 'origin': '81_22~CUW~81_95#MGNP'} Metrics: ['ELUC: 0.07550519970419821', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.10505746306356409', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 82_92 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_53'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_92', 'origin': '81_38~CUW~81_53#MGNP'} Metrics: ['ELUC: -0.1594680801871305', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3050647246276793', 'is_elite: False']\n", + "Id: 82_17 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_17', 'origin': '81_38~CUW~81_22#MGNP'} Metrics: ['ELUC: -0.5501747215875261', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.22343648879964317', 'is_elite: False']\n", + "Id: 82_40 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_40', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 82_62 Identity: {'ancestor_count': 79, 'ancestor_ids': ['2_49', '80_33'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_62', 'origin': '2_49~CUW~80_33#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 82_77 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_95'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_77', 'origin': '1_1~CUW~81_95#MGNP'} Metrics: ['ELUC: -0.9717186783171426', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.038791654603082586', 'is_elite: False']\n", + "Id: 82_69 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_95'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_69', 'origin': '1_1~CUW~81_95#MGNP'} Metrics: ['ELUC: -1.050695653970631', 'NSGA-II_crowding_distance: 0.036681791025811844', 'NSGA-II_rank: 2', 'change: 0.03968511191560676', 'is_elite: False']\n", + "Id: 82_45 Identity: {'ancestor_count': 74, 'ancestor_ids': ['1_1', '81_48'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_45', 'origin': '1_1~CUW~81_48#MGNP'} Metrics: ['ELUC: -1.2635566698147127', 'NSGA-II_crowding_distance: 0.23781672765405393', 'NSGA-II_rank: 2', 'change: 0.043310327229354184', 'is_elite: False']\n", + "Id: 82_20 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_20', 'origin': '81_20~CUW~81_38#MGNP'} Metrics: ['ELUC: -1.2928971724302778', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2290562174784037', 'is_elite: False']\n", + "Id: 81_95 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_78'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_95', 'origin': '1_1~CUW~80_78#MGNP'} Metrics: ['ELUC: -2.083618656113992', 'NSGA-II_crowding_distance: 0.270392362165912', 'NSGA-II_rank: 1', 'change: 0.03614901748277748', 'is_elite: True']\n", + "Id: 82_65 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '1_1'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_65', 'origin': '81_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0939519141466545', 'NSGA-II_crowding_distance: 0.1539317925662405', 'NSGA-II_rank: 1', 'change: 0.05004215671589595', 'is_elite: False']\n", + "Id: 82_42 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_91'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_42', 'origin': '1_1~CUW~81_91#MGNP'} Metrics: ['ELUC: -2.6411026523421244', 'NSGA-II_crowding_distance: 1.0308045691907495', 'NSGA-II_rank: 7', 'change: 0.1464081301318765', 'is_elite: False']\n", + "Id: 82_15 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_43', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_15', 'origin': '81_43~CUW~81_38#MGNP'} Metrics: ['ELUC: -2.9009073383645982', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.21641016098832452', 'is_elite: False']\n", + "Id: 82_41 Identity: {'ancestor_count': 80, 'ancestor_ids': ['80_33', '81_43'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_41', 'origin': '80_33~CUW~81_43#MGNP'} Metrics: ['ELUC: -2.9663132159644325', 'NSGA-II_crowding_distance: 0.2781470698089903', 'NSGA-II_rank: 2', 'change: 0.06860456342741356', 'is_elite: False']\n", + "Id: 82_54 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_54', 'origin': '81_95~CUW~81_20#MGNP'} Metrics: ['ELUC: -3.014510645228866', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.0785641558771764', 'is_elite: False']\n", + "Id: 82_71 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_95'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_71', 'origin': '81_20~CUW~81_95#MGNP'} Metrics: ['ELUC: -3.498019665494213', 'NSGA-II_crowding_distance: 0.15092584609666812', 'NSGA-II_rank: 1', 'change: 0.05807601291591252', 'is_elite: False']\n", + "Id: 82_27 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_53', '81_43'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_27', 'origin': '81_53~CUW~81_43#MGNP'} Metrics: ['ELUC: -3.5019291044847143', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07156482575306147', 'is_elite: False']\n", + "Id: 82_16 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '1_1'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_16', 'origin': '81_20~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.622895557647704', 'NSGA-II_crowding_distance: 0.13094247437348436', 'NSGA-II_rank: 3', 'change: 0.07877643731248428', 'is_elite: False']\n", + "Id: 82_81 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_81', 'origin': '81_22~CUW~81_38#MGNP'} Metrics: ['ELUC: -3.7086670558950434', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.32560755794290014', 'is_elite: False']\n", + "Id: 82_53 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_53', 'origin': '81_95~CUW~81_20#MGNP'} Metrics: ['ELUC: -3.7442359417430673', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10338682880905255', 'is_elite: False']\n", + "Id: 82_89 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_42'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_89', 'origin': '1_1~CUW~81_42#MGNP'} Metrics: ['ELUC: -3.8644898837175226', 'NSGA-II_crowding_distance: 0.18331537318501506', 'NSGA-II_rank: 2', 'change: 0.07137959084773812', 'is_elite: False']\n", + "Id: 82_13 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '1_1'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_13', 'origin': '80_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.894236719537647', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08383078095273983', 'is_elite: False']\n", + "Id: 82_95 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_33'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_95', 'origin': '1_1~CUW~80_33#MGNP'} Metrics: ['ELUC: -4.262119776456695', 'NSGA-II_crowding_distance: 0.06940163177172316', 'NSGA-II_rank: 1', 'change: 0.05828058893099188', 'is_elite: False']\n", + "Id: 82_72 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_42', '81_95'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_72', 'origin': '81_42~CUW~81_95#MGNP'} Metrics: ['ELUC: -4.277574215207477', 'NSGA-II_crowding_distance: 0.15790170228584965', 'NSGA-II_rank: 1', 'change: 0.06555463223542563', 'is_elite: False']\n", + "Id: 82_26 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_42', '81_94'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_26', 'origin': '81_42~CUW~81_94#MGNP'} Metrics: ['ELUC: -4.299449224860528', 'NSGA-II_crowding_distance: 0.25001990874762425', 'NSGA-II_rank: 4', 'change: 0.08336249589447138', 'is_elite: False']\n", + "Id: 82_24 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_69', '1_1'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_24', 'origin': '81_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.467660984890014', 'NSGA-II_crowding_distance: 1.311846704945129', 'NSGA-II_rank: 5', 'change: 0.13935873187507689', 'is_elite: False']\n", + "Id: 82_74 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '81_48'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_74', 'origin': '80_33~CUW~81_48#MGNP'} Metrics: ['ELUC: -4.580785984302141', 'NSGA-II_crowding_distance: 0.17212583341725615', 'NSGA-II_rank: 3', 'change: 0.08204673250442437', 'is_elite: False']\n", + "Id: 82_46 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_46', 'origin': '1_1~CUW~81_38#MGNP'} Metrics: ['ELUC: -4.793166804611166', 'NSGA-II_crowding_distance: 1.1059765308884821', 'NSGA-II_rank: 7', 'change: 0.20390364046532494', 'is_elite: False']\n", + "Id: 82_90 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '80_33'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_90', 'origin': '80_33~CUW~80_33#MGNP'} Metrics: ['ELUC: -4.982533127223017', 'NSGA-II_crowding_distance: 0.3156296811670701', 'NSGA-II_rank: 4', 'change: 0.09523006421445193', 'is_elite: False']\n", + "Id: 82_61 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_61', 'origin': '81_20~CUW~81_46#MGNP'} Metrics: ['ELUC: -5.149522901248343', 'NSGA-II_crowding_distance: 0.3469764154258759', 'NSGA-II_rank: 3', 'change: 0.090639322478145', 'is_elite: False']\n", + "Id: 82_79 Identity: {'ancestor_count': 80, 'ancestor_ids': ['80_33', '81_94'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_79', 'origin': '80_33~CUW~81_94#MGNP'} Metrics: ['ELUC: -5.181139143403142', 'NSGA-II_crowding_distance: 0.16890251010499488', 'NSGA-II_rank: 2', 'change: 0.07911106339283823', 'is_elite: False']\n", + "Id: 82_91 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_94', '81_91'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_91', 'origin': '81_94~CUW~81_91#MGNP'} Metrics: ['ELUC: -5.431111757077129', 'NSGA-II_crowding_distance: 0.4123358607489285', 'NSGA-II_rank: 4', 'change: 0.1292828388847243', 'is_elite: False']\n", + "Id: 82_38 Identity: {'ancestor_count': 80, 'ancestor_ids': ['80_33', '81_42'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_38', 'origin': '80_33~CUW~81_42#MGNP'} Metrics: ['ELUC: -5.662310450961492', 'NSGA-II_crowding_distance: 0.0625123739454751', 'NSGA-II_rank: 2', 'change: 0.08493733908581916', 'is_elite: False']\n", + "Id: 82_98 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_42', '80_33'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_98', 'origin': '81_42~CUW~80_33#MGNP'} Metrics: ['ELUC: -5.784784151308138', 'NSGA-II_crowding_distance: 0.23624440539894315', 'NSGA-II_rank: 2', 'change: 0.08511464590507284', 'is_elite: False']\n", + "Id: 80_33 Identity: {'ancestor_count': 78, 'ancestor_ids': ['77_28', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_33', 'origin': '77_28~CUW~79_48#MGNP'} Metrics: ['ELUC: -5.82777994911403', 'NSGA-II_crowding_distance: 0.37241576862617937', 'NSGA-II_rank: 1', 'change: 0.0788252023385081', 'is_elite: True']\n", + "Id: 82_59 Identity: {'ancestor_count': 80, 'ancestor_ids': ['77_28', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_59', 'origin': '77_28~CUW~81_22#MGNP'} Metrics: ['ELUC: -7.0731471234639915', 'NSGA-II_crowding_distance: 0.37676121740517426', 'NSGA-II_rank: 3', 'change: 0.11629483399736074', 'is_elite: False']\n", + "Id: 82_12 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '2_49'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_12', 'origin': '81_20~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.0936032734203645', 'NSGA-II_crowding_distance: 0.9691954308092505', 'NSGA-II_rank: 7', 'change: 0.26860302912243667', 'is_elite: False']\n", + "Id: 82_33 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_43', '77_28'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_33', 'origin': '81_43~CUW~77_28#MGNP'} Metrics: ['ELUC: -7.461515884811016', 'NSGA-II_crowding_distance: 0.27852795278703', 'NSGA-II_rank: 4', 'change: 0.1368170165623359', 'is_elite: False']\n", + "Id: 82_22 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '1_1'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_22', 'origin': '81_22~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.464661031798729', 'NSGA-II_crowding_distance: 0.2755511189837968', 'NSGA-II_rank: 2', 'change: 0.11527166217367237', 'is_elite: False']\n", + "Id: 82_51 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_42', '81_94'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_51', 'origin': '81_42~CUW~81_94#MGNP'} Metrics: ['ELUC: -7.701523882499481', 'NSGA-II_crowding_distance: 0.4309088120141729', 'NSGA-II_rank: 3', 'change: 0.13055300372142298', 'is_elite: False']\n", + "Id: 82_55 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_91', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_55', 'origin': '81_91~CUW~81_46#MGNP'} Metrics: ['ELUC: -7.890450726412458', 'NSGA-II_crowding_distance: 0.2576945313192121', 'NSGA-II_rank: 4', 'change: 0.14293987645877917', 'is_elite: False']\n", + "Id: 82_19 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_42', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_19', 'origin': '81_42~CUW~81_46#MGNP'} Metrics: ['ELUC: -7.906700641808768', 'NSGA-II_crowding_distance: 0.1677694213291448', 'NSGA-II_rank: 2', 'change: 0.12018172943024077', 'is_elite: False']\n", + "Id: 81_20 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_33'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_20', 'origin': '80_30~CUW~80_33#MGNP'} Metrics: ['ELUC: -8.244788742135801', 'NSGA-II_crowding_distance: 0.2758907948145419', 'NSGA-II_rank: 1', 'change: 0.10935034498458633', 'is_elite: True']\n", + "Id: 82_47 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_91', '81_43'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_47', 'origin': '81_91~CUW~81_43#MGNP'} Metrics: ['ELUC: -8.475083994997862', 'NSGA-II_crowding_distance: 1.8138777224579767', 'NSGA-II_rank: 6', 'change: 0.16073304672323008', 'is_elite: False']\n", + "Id: 82_80 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_94', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_80', 'origin': '81_94~CUW~81_20#MGNP'} Metrics: ['ELUC: -8.580198061715128', 'NSGA-II_crowding_distance: 0.078690862444983', 'NSGA-II_rank: 1', 'change: 0.11443548353417866', 'is_elite: False']\n", + "Id: 82_56 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '80_33'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_56', 'origin': '81_20~CUW~80_33#MGNP'} Metrics: ['ELUC: -8.586691768910654', 'NSGA-II_crowding_distance: 0.12963186761833875', 'NSGA-II_rank: 1', 'change: 0.1270277449350571', 'is_elite: False']\n", + "Id: 81_94 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_94', 'origin': '80_33~CUW~80_61#MGNP'} Metrics: ['ELUC: -8.697546859839363', 'NSGA-II_crowding_distance: 0.2985639971745961', 'NSGA-II_rank: 2', 'change: 0.13756488674738657', 'is_elite: False']\n", + "Id: 82_39 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_39', 'origin': '2_49~CUW~81_46#MGNP'} Metrics: ['ELUC: -8.753461138478592', 'NSGA-II_crowding_distance: 0.8702053408638564', 'NSGA-II_rank: 6', 'change: 0.28431191991511945', 'is_elite: False']\n", + "Id: 82_32 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_32', 'origin': '81_38~CUW~81_22#MGNP'} Metrics: ['ELUC: -9.037555420628912', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.30278905804150136', 'is_elite: False']\n", + "Id: 82_52 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_52', 'origin': '2_49~CUW~81_20#MGNP'} Metrics: ['ELUC: -9.229627457827492', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29979747467054657', 'is_elite: False']\n", + "Id: 82_60 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_60', 'origin': '2_49~CUW~81_22#MGNP'} Metrics: ['ELUC: -9.408880543110024', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29801757212883645', 'is_elite: False']\n", + "Id: 82_57 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_57', 'origin': '81_20~CUW~81_46#MGNP'} Metrics: ['ELUC: -9.722820978484933', 'NSGA-II_crowding_distance: 0.20561491258323494', 'NSGA-II_rank: 1', 'change: 0.1337240808867949', 'is_elite: True']\n", + "Id: 82_35 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_94', '81_94'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_35', 'origin': '81_94~CUW~81_94#MGNP'} Metrics: ['ELUC: -9.999719820894411', 'NSGA-II_crowding_distance: 0.32756297114641864', 'NSGA-II_rank: 4', 'change: 0.1446187159058053', 'is_elite: False']\n", + "Id: 82_49 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_84', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_49', 'origin': '81_84~CUW~81_20#MGNP'} Metrics: ['ELUC: -10.921851517898018', 'NSGA-II_crowding_distance: 1.0079225145230892', 'NSGA-II_rank: 5', 'change: 0.15905693861512893', 'is_elite: False']\n", + "Id: 82_11 Identity: {'ancestor_count': 80, 'ancestor_ids': ['80_33', '81_43'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_11', 'origin': '80_33~CUW~81_43#MGNP'} Metrics: ['ELUC: -10.946844195768175', 'NSGA-II_crowding_distance: 0.6881532950548711', 'NSGA-II_rank: 5', 'change: 0.16681523307977766', 'is_elite: False']\n", + "Id: 82_76 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '81_48'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_76', 'origin': '81_22~CUW~81_48#MGNP'} Metrics: ['ELUC: -11.058677334780038', 'NSGA-II_crowding_distance: 0.7727003143074567', 'NSGA-II_rank: 4', 'change: 0.1539264897495081', 'is_elite: False']\n", + "Id: 82_88 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_46', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_88', 'origin': '81_46~CUW~81_20#MGNP'} Metrics: ['ELUC: -11.271370085222372', 'NSGA-II_crowding_distance: 0.46334967500297797', 'NSGA-II_rank: 3', 'change: 0.13934452307281547', 'is_elite: False']\n", + "Id: 82_37 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_37', 'origin': '2_49~CUW~81_46#MGNP'} Metrics: ['ELUC: -11.291851375255936', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2917166315809333', 'is_elite: False']\n", + "Id: 81_46 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_17', '80_55'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_46', 'origin': '80_17~CUW~80_55#MGNP'} Metrics: ['ELUC: -11.468734660651027', 'NSGA-II_crowding_distance: 0.3056960781463699', 'NSGA-II_rank: 2', 'change: 0.13801567472251197', 'is_elite: False']\n", + "Id: 82_83 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '80_33'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_83', 'origin': '81_22~CUW~80_33#MGNP'} Metrics: ['ELUC: -11.603967787837547', 'NSGA-II_crowding_distance: 0.15513921625404967', 'NSGA-II_rank: 1', 'change: 0.13717454872398224', 'is_elite: False']\n", + "Id: 82_73 Identity: {'ancestor_count': 80, 'ancestor_ids': ['80_33', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_73', 'origin': '80_33~CUW~81_22#MGNP'} Metrics: ['ELUC: -11.616694648843243', 'NSGA-II_crowding_distance: 0.1144161190041759', 'NSGA-II_rank: 1', 'change: 0.14787454582532605', 'is_elite: False']\n", + "Id: 82_78 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_94', '81_43'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_78', 'origin': '81_94~CUW~81_43#MGNP'} Metrics: ['ELUC: -11.794812158821244', 'NSGA-II_crowding_distance: 0.5006534400668654', 'NSGA-II_rank: 3', 'change: 0.16277450135318955', 'is_elite: False']\n", + "Id: 82_50 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_50', 'origin': '81_20~CUW~81_38#MGNP'} Metrics: ['ELUC: -11.95908208298172', 'NSGA-II_crowding_distance: 0.9438096946414389', 'NSGA-II_rank: 4', 'change: 0.2719550053061517', 'is_elite: False']\n", + "Id: 82_30 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_30', 'origin': '81_22~CUW~81_22#MGNP'} Metrics: ['ELUC: -12.147417067433581', 'NSGA-II_crowding_distance: 0.21731764352562288', 'NSGA-II_rank: 2', 'change: 0.15897392748156472', 'is_elite: False']\n", + "Id: 82_86 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_86', 'origin': '81_22~CUW~81_46#MGNP'} Metrics: ['ELUC: -12.428927871814855', 'NSGA-II_crowding_distance: 0.09394462735325843', 'NSGA-II_rank: 1', 'change: 0.15731394194859114', 'is_elite: False']\n", + "Id: 82_85 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_43', '81_94'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_85', 'origin': '81_43~CUW~81_94#MGNP'} Metrics: ['ELUC: -12.44787872711227', 'NSGA-II_crowding_distance: 0.29594339443754025', 'NSGA-II_rank: 2', 'change: 0.17675672310202462', 'is_elite: False']\n", + "Id: 81_22 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_55', '80_17'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_22', 'origin': '80_55~CUW~80_17#MGNP'} Metrics: ['ELUC: -12.502269198677512', 'NSGA-II_crowding_distance: 0.03690426324944365', 'NSGA-II_rank: 1', 'change: 0.16087705599631114', 'is_elite: False']\n", + "Id: 82_75 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_75', 'origin': '81_22~CUW~81_22#MGNP'} Metrics: ['ELUC: -12.67230945782176', 'NSGA-II_crowding_distance: 0.08208370836478704', 'NSGA-II_rank: 1', 'change: 0.16419509115065697', 'is_elite: False']\n", + "Id: 82_70 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_70', 'origin': '81_22~CUW~81_22#MGNP'} Metrics: ['ELUC: -13.127514133052676', 'NSGA-II_crowding_distance: 0.17467053184597428', 'NSGA-II_rank: 1', 'change: 0.17475840606871143', 'is_elite: False']\n", + "Id: 82_48 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_68', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_48', 'origin': '81_68~CUW~81_20#MGNP'} Metrics: ['ELUC: -13.659062180847519', 'NSGA-II_crowding_distance: 0.7655182580681236', 'NSGA-II_rank: 3', 'change: 0.21010903480083837', 'is_elite: False']\n", + "Id: 81_43 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_61'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_43', 'origin': '80_30~CUW~80_61#MGNP'} Metrics: ['ELUC: -13.773676108294445', 'NSGA-II_crowding_distance: 0.25399387111930566', 'NSGA-II_rank: 2', 'change: 0.20705613200662631', 'is_elite: False']\n", + "Id: 82_25 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_43', '81_91'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_25', 'origin': '81_43~CUW~81_91#MGNP'} Metrics: ['ELUC: -13.818258950987415', 'NSGA-II_crowding_distance: 0.18298967818709316', 'NSGA-II_rank: 1', 'change: 0.19686576916733678', 'is_elite: False']\n", + "Id: 82_94 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_43', '81_94'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_94', 'origin': '81_43~CUW~81_94#MGNP'} Metrics: ['ELUC: -14.30413254917916', 'NSGA-II_crowding_distance: 0.3551254729920663', 'NSGA-II_rank: 2', 'change: 0.2106714047030797', 'is_elite: False']\n", + "Id: 82_82 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_22', '81_68'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_82', 'origin': '81_22~CUW~81_68#MGNP'} Metrics: ['ELUC: -14.483788807093575', 'NSGA-II_crowding_distance: 0.07714426011492645', 'NSGA-II_rank: 1', 'change: 0.20634204882127763', 'is_elite: False']\n", + "Id: 82_93 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_91', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_93', 'origin': '81_91~CUW~81_46#MGNP'} Metrics: ['ELUC: -14.5026411679168', 'NSGA-II_crowding_distance: 0.18507974035907465', 'NSGA-II_rank: 1', 'change: 0.20826972005152736', 'is_elite: True']\n", + "Id: 82_14 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_14', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -14.510253939213813', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2899956535510726', 'is_elite: False']\n", + "Id: 82_97 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_43', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_97', 'origin': '81_43~CUW~81_38#MGNP'} Metrics: ['ELUC: -14.651568596670252', 'NSGA-II_crowding_distance: 0.5621670547275626', 'NSGA-II_rank: 3', 'change: 0.2850034694311682', 'is_elite: False']\n", + "Id: 82_36 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_36', 'origin': '2_49~CUW~81_22#MGNP'} Metrics: ['ELUC: -14.721860121070682', 'NSGA-II_crowding_distance: 0.30129198768091825', 'NSGA-II_rank: 1', 'change: 0.2575255751622122', 'is_elite: True']\n", + "Id: 82_43 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_91'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_43', 'origin': '81_38~CUW~81_91#MGNP'} Metrics: ['ELUC: -14.982931721996842', 'NSGA-II_crowding_distance: 0.4623185762674685', 'NSGA-II_rank: 2', 'change: 0.2766029565837616', 'is_elite: False']\n", + "Id: 82_18 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_30', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_18', 'origin': '81_30~CUW~81_20#MGNP'} Metrics: ['ELUC: -16.062302497144543', 'NSGA-II_crowding_distance: 0.16368365326104972', 'NSGA-II_rank: 3', 'change: 0.29447556938441605', 'is_elite: False']\n", + "Id: 82_96 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_91'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_96', 'origin': '2_49~CUW~81_91#MGNP'} Metrics: ['ELUC: -16.08738768262354', 'NSGA-II_crowding_distance: 0.028351803392038907', 'NSGA-II_rank: 3', 'change: 0.2965659525736888', 'is_elite: False']\n", + "Id: 82_31 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_20'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_31', 'origin': '2_49~CUW~81_20#MGNP'} Metrics: ['ELUC: -16.272877173253512', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.29715175974582353', 'is_elite: False']\n", + "Id: 82_28 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_91', '81_68'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_28', 'origin': '81_91~CUW~81_68#MGNP'} Metrics: ['ELUC: -16.375799621200837', 'NSGA-II_crowding_distance: 0.1757705021325619', 'NSGA-II_rank: 1', 'change: 0.2663804584951691', 'is_elite: False']\n", + "Id: 82_84 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_84', 'origin': '81_38~CUW~81_38#MGNP'} Metrics: ['ELUC: -16.643819402031255', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.28899095133006925', 'is_elite: False']\n", + "Id: 82_23 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_23', 'origin': '81_95~CUW~81_38#MGNP'} Metrics: ['ELUC: -16.70621669696751', 'NSGA-II_crowding_distance: 0.19124765161502233', 'NSGA-II_rank: 1', 'change: 0.27629643323483516', 'is_elite: True']\n", + "Id: 82_87 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '1_1'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_87', 'origin': '81_38~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.590630095535765', 'NSGA-II_crowding_distance: 0.1402429971786581', 'NSGA-II_rank: 1', 'change: 0.30282844814207566', 'is_elite: False']\n", + "Id: 82_34 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_42'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_34', 'origin': '2_49~CUW~81_42#MGNP'} Metrics: ['ELUC: -17.59726586935643', 'NSGA-II_crowding_distance: 0.0010278180362945312', 'NSGA-II_rank: 1', 'change: 0.30302043914165366', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 81_38 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '80_96'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_38', 'origin': '80_33~CUW~80_96#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 82_21 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_42'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_21', 'origin': '81_38~CUW~81_42#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 82_44 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_44', 'origin': '81_38~CUW~81_38#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 82_64 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_64', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 82_66 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_43'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_66', 'origin': '2_49~CUW~81_43#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 82_67 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_94', '2_49'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_67', 'origin': '81_94~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 82_68 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_91'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_68', 'origin': '81_38~CUW~81_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 82_100 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_42'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_100', 'origin': '81_38~CUW~81_42#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 82.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 83...:\n", + "PopulationResponse:\n", + " Generation: 83\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/83/20240220-054044\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 83 and asking ESP for generation 84...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 83 data persisted.\n", + "Evaluated candidates:\n", + "Id: 83_98 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_36'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_98', 'origin': '1_1~CUW~82_36#MGNP'} Metrics: ['ELUC: 23.831629257683026', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 14', 'change: 0.3037721564390044', 'is_elite: False']\n", + "Id: 83_18 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_36', '80_33'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_18', 'origin': '82_36~CUW~80_33#MGNP'} Metrics: ['ELUC: 21.466043661897537', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.2982056886646357', 'is_elite: False']\n", + "Id: 83_100 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_93'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_100', 'origin': '2_49~CUW~82_93#MGNP'} Metrics: ['ELUC: 21.436372151142105', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.29515608653789077', 'is_elite: False']\n", + "Id: 83_66 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_66', 'origin': '1_1~CUW~82_100#MGNP'} Metrics: ['ELUC: 20.520048216708677', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2761206010089571', 'is_elite: False']\n", + "Id: 83_16 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_36', '1_1'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_16', 'origin': '82_36~CUW~1_1#MGNP'} Metrics: ['ELUC: 15.324631286654279', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27226774581240787', 'is_elite: False']\n", + "Id: 83_47 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_36'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_47', 'origin': '1_1~CUW~82_36#MGNP'} Metrics: ['ELUC: 12.336061916788987', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2574784749417047', 'is_elite: False']\n", + "Id: 83_81 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_81', 'origin': '1_1~CUW~82_100#MGNP'} Metrics: ['ELUC: 10.18241945855655', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.22917015370322769', 'is_elite: False']\n", + "Id: 83_61 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_36'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_61', 'origin': '1_1~CUW~82_36#MGNP'} Metrics: ['ELUC: 6.1873613302691695', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24449444773246948', 'is_elite: False']\n", + "Id: 83_49 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '1_1'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_49', 'origin': '82_100~CUW~1_1#MGNP'} Metrics: ['ELUC: 5.456254491442891', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.17714199594884308', 'is_elite: False']\n", + "Id: 83_57 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_57', 'origin': '1_1~CUW~82_100#MGNP'} Metrics: ['ELUC: 4.664463037467959', 'NSGA-II_crowding_distance: 1.298851181859082', 'NSGA-II_rank: 6', 'change: 0.23473352381805004', 'is_elite: False']\n", + "Id: 83_42 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '80_33'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_42', 'origin': '82_23~CUW~80_33#MGNP'} Metrics: ['ELUC: 4.260644652043384', 'NSGA-II_crowding_distance: 1.035361051057007', 'NSGA-II_rank: 9', 'change: 0.25776863612174783', 'is_elite: False']\n", + "Id: 83_14 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_70'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_14', 'origin': '2_49~CUW~82_70#MGNP'} Metrics: ['ELUC: 3.9861463945049938', 'NSGA-II_crowding_distance: 0.7292552930567576', 'NSGA-II_rank: 8', 'change: 0.25669677796433016', 'is_elite: False']\n", + "Id: 83_78 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_78', 'origin': '2_49~CUW~81_20#MGNP'} Metrics: ['ELUC: 3.6417414348388744', 'NSGA-II_crowding_distance: 1.3577039845688512', 'NSGA-II_rank: 9', 'change: 0.26920195210081566', 'is_elite: False']\n", + "Id: 83_64 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_83'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_64', 'origin': '2_49~CUW~82_83#MGNP'} Metrics: ['ELUC: 2.5022781169274566', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.35171157226652205', 'is_elite: False']\n", + "Id: 83_30 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '82_25'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_30', 'origin': '81_95~CUW~82_25#MGNP'} Metrics: ['ELUC: 2.3881376271928887', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09992678600295717', 'is_elite: False']\n", + "Id: 83_73 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_65'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_73', 'origin': '2_49~CUW~82_65#MGNP'} Metrics: ['ELUC: 1.4822952579300628', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.35115128475788326', 'is_elite: False']\n", + "Id: 83_43 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_95'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_43', 'origin': '2_49~CUW~81_95#MGNP'} Metrics: ['ELUC: 0.9152059666781597', 'NSGA-II_crowding_distance: 0.8193166432052911', 'NSGA-II_rank: 8', 'change: 0.26350775838242974', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 83_58 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_70', '2_49'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_58', 'origin': '82_70~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.4101787426225313', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2906657250562577', 'is_elite: False']\n", + "Id: 83_26 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_26', 'origin': '2_49~CUW~82_100#MGNP'} Metrics: ['ELUC: -0.5869594705120654', 'NSGA-II_crowding_distance: 1.0755349759736004', 'NSGA-II_rank: 7', 'change: 0.2388462785643108', 'is_elite: False']\n", + "Id: 83_32 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_20', '82_65'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_32', 'origin': '81_20~CUW~82_65#MGNP'} Metrics: ['ELUC: -0.6240834880352454', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07979394211318457', 'is_elite: False']\n", + "Id: 83_52 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_70', '1_1'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_52', 'origin': '82_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8102712594572427', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0685224992527519', 'is_elite: False']\n", + "Id: 83_72 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_28'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_72', 'origin': '1_1~CUW~82_28#MGNP'} Metrics: ['ELUC: -1.1507045228461534', 'NSGA-II_crowding_distance: 1.3653625784871073', 'NSGA-II_rank: 5', 'change: 0.10023659074987645', 'is_elite: False']\n", + "Id: 83_45 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_95'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_45', 'origin': '1_1~CUW~81_95#MGNP'} Metrics: ['ELUC: -1.564881991002863', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04202795607498007', 'is_elite: False']\n", + "Id: 83_46 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_46', 'origin': '1_1~CUW~81_20#MGNP'} Metrics: ['ELUC: -1.5996585374552155', 'NSGA-II_crowding_distance: 1.0082242588110317', 'NSGA-II_rank: 4', 'change: 0.0879302151438897', 'is_elite: False']\n", + "Id: 83_82 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_57'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_82', 'origin': '1_1~CUW~82_57#MGNP'} Metrics: ['ELUC: -1.773872812058671', 'NSGA-II_crowding_distance: 0.2029480662093393', 'NSGA-II_rank: 2', 'change: 0.05422421742054491', 'is_elite: False']\n", + "Id: 81_95 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_78'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_95', 'origin': '1_1~CUW~80_78#MGNP'} Metrics: ['ELUC: -2.083618656113992', 'NSGA-II_crowding_distance: 0.330462451261892', 'NSGA-II_rank: 1', 'change: 0.03614901748277748', 'is_elite: True']\n", + "Id: 83_40 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_93'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_40', 'origin': '1_1~CUW~82_93#MGNP'} Metrics: ['ELUC: -2.1469737807135645', 'NSGA-II_crowding_distance: 0.45305660631872585', 'NSGA-II_rank: 3', 'change: 0.07434206881907131', 'is_elite: False']\n", + "Id: 83_33 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_95'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_33', 'origin': '1_1~CUW~81_95#MGNP'} Metrics: ['ELUC: -3.0047112435963292', 'NSGA-II_crowding_distance: 0.15704085664890188', 'NSGA-II_rank: 1', 'change: 0.052509866115028433', 'is_elite: False']\n", + "Id: 83_51 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_70'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_51', 'origin': '2_49~CUW~82_70#MGNP'} Metrics: ['ELUC: -3.1389376789561', 'NSGA-II_crowding_distance: 1.2707447069432423', 'NSGA-II_rank: 8', 'change: 0.26898868724634634', 'is_elite: False']\n", + "Id: 83_11 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_57', '80_33'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_11', 'origin': '82_57~CUW~80_33#MGNP'} Metrics: ['ELUC: -3.1684432429973164', 'NSGA-II_crowding_distance: 0.278003985056578', 'NSGA-II_rank: 2', 'change: 0.06888669326170577', 'is_elite: False']\n", + "Id: 83_60 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_95'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_60', 'origin': '81_20~CUW~81_95#MGNP'} Metrics: ['ELUC: -3.299726627503179', 'NSGA-II_crowding_distance: 0.16876644875909938', 'NSGA-II_rank: 1', 'change: 0.062368782312980375', 'is_elite: False']\n", + "Id: 83_75 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_57', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_75', 'origin': '82_57~CUW~82_100#MGNP'} Metrics: ['ELUC: -4.271597932153872', 'NSGA-II_crowding_distance: 1.3442222258116572', 'NSGA-II_rank: 4', 'change: 0.20471604019159118', 'is_elite: False']\n", + "Id: 83_86 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_71', '82_72'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_86', 'origin': '82_71~CUW~82_72#MGNP'} Metrics: ['ELUC: -4.450452689508567', 'NSGA-II_crowding_distance: 0.24920479278095098', 'NSGA-II_rank: 2', 'change: 0.08320197675834147', 'is_elite: False']\n", + "Id: 83_71 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_25'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_71', 'origin': '82_23~CUW~82_25#MGNP'} Metrics: ['ELUC: -4.497061753420407', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.32512350381900107', 'is_elite: False']\n", + "Id: 83_91 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_72', '80_33'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_91', 'origin': '82_72~CUW~80_33#MGNP'} Metrics: ['ELUC: -4.688136890616877', 'NSGA-II_crowding_distance: 0.19893665343864442', 'NSGA-II_rank: 1', 'change: 0.07429776135099717', 'is_elite: False']\n", + "Id: 83_74 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_74', 'origin': '81_95~CUW~81_20#MGNP'} Metrics: ['ELUC: -5.470990591923912', 'NSGA-II_crowding_distance: 0.764096681712877', 'NSGA-II_rank: 3', 'change: 0.10872451973295258', 'is_elite: False']\n", + "Id: 83_37 Identity: {'ancestor_count': 81, 'ancestor_ids': ['80_33', '82_72'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_37', 'origin': '80_33~CUW~82_72#MGNP'} Metrics: ['ELUC: -5.641494144110916', 'NSGA-II_crowding_distance: 0.2454308010946934', 'NSGA-II_rank: 2', 'change: 0.09366198249163105', 'is_elite: False']\n", + "Id: 80_33 Identity: {'ancestor_count': 78, 'ancestor_ids': ['77_28', '79_48'], 'birth_generation': 80, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '80_33', 'origin': '77_28~CUW~79_48#MGNP'} Metrics: ['ELUC: -5.82777994911403', 'NSGA-II_crowding_distance: 0.12474047084165978', 'NSGA-II_rank: 1', 'change: 0.0788252023385081', 'is_elite: False']\n", + "Id: 83_24 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '80_33'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_24', 'origin': '82_100~CUW~80_33#MGNP'} Metrics: ['ELUC: -6.20204416642625', 'NSGA-II_crowding_distance: 1.1748503389673233', 'NSGA-II_rank: 5', 'change: 0.22719832655710503', 'is_elite: False']\n", + "Id: 83_92 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_33', '80_33'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_92', 'origin': '80_33~CUW~80_33#MGNP'} Metrics: ['ELUC: -6.235842589714124', 'NSGA-II_crowding_distance: 0.1455855668056781', 'NSGA-II_rank: 1', 'change: 0.08525249526371523', 'is_elite: False']\n", + "Id: 83_76 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '82_23'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_76', 'origin': '81_95~CUW~82_23#MGNP'} Metrics: ['ELUC: -6.702239354323529', 'NSGA-II_crowding_distance: 1.0897815414073533', 'NSGA-II_rank: 7', 'change: 0.23912998731013252', 'is_elite: False']\n", + "Id: 83_83 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '80_33'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_83', 'origin': '82_23~CUW~80_33#MGNP'} Metrics: ['ELUC: -6.707535679789295', 'NSGA-II_crowding_distance: 0.045721220282583616', 'NSGA-II_rank: 5', 'change: 0.22786681040913864', 'is_elite: False']\n", + "Id: 83_22 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '82_83'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_22', 'origin': '82_100~CUW~82_83#MGNP'} Metrics: ['ELUC: -6.796795715621283', 'NSGA-II_crowding_distance: 0.15352032033945168', 'NSGA-II_rank: 5', 'change: 0.22842778046044385', 'is_elite: False']\n", + "Id: 83_65 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_83'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_65', 'origin': '1_1~CUW~82_83#MGNP'} Metrics: ['ELUC: -7.058760391359609', 'NSGA-II_crowding_distance: 0.234272378765228', 'NSGA-II_rank: 2', 'change: 0.10479033396489135', 'is_elite: False']\n", + "Id: 83_34 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_57', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_34', 'origin': '82_57~CUW~81_20#MGNP'} Metrics: ['ELUC: -7.186151330285866', 'NSGA-II_crowding_distance: 0.1412472634434135', 'NSGA-II_rank: 1', 'change: 0.09921271006279303', 'is_elite: False']\n", + "Id: 83_36 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_57', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_36', 'origin': '82_57~CUW~81_20#MGNP'} Metrics: ['ELUC: -7.385322685166651', 'NSGA-II_crowding_distance: 0.22516776833499041', 'NSGA-II_rank: 2', 'change: 0.12641210142386533', 'is_elite: False']\n", + "Id: 83_17 Identity: {'ancestor_count': 80, 'ancestor_ids': ['80_33', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_17', 'origin': '80_33~CUW~81_20#MGNP'} Metrics: ['ELUC: -7.730152843417588', 'NSGA-II_crowding_distance: 0.09418611607091865', 'NSGA-II_rank: 1', 'change: 0.1020386253876616', 'is_elite: False']\n", + "Id: 83_63 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '81_95'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_63', 'origin': '82_100~CUW~81_95#MGNP'} Metrics: ['ELUC: -8.1155839509697', 'NSGA-II_crowding_distance: 1.0162940845837571', 'NSGA-II_rank: 6', 'change: 0.23756857224391684', 'is_elite: False']\n", + "Id: 81_20 Identity: {'ancestor_count': 79, 'ancestor_ids': ['80_30', '80_33'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_20', 'origin': '80_30~CUW~80_33#MGNP'} Metrics: ['ELUC: -8.244788742135801', 'NSGA-II_crowding_distance: 0.1681642185577034', 'NSGA-II_rank: 1', 'change: 0.10935034498458633', 'is_elite: False']\n", + "Id: 83_54 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '1_1'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_54', 'origin': '82_100~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.45254999642175', 'NSGA-II_crowding_distance: 0.4531853636825389', 'NSGA-II_rank: 5', 'change: 0.2344834935260925', 'is_elite: False']\n", + "Id: 83_88 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_95'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_88', 'origin': '2_49~CUW~81_95#MGNP'} Metrics: ['ELUC: -8.755823696156675', 'NSGA-II_crowding_distance: 0.8134837895602722', 'NSGA-II_rank: 7', 'change: 0.26508920278945863', 'is_elite: False']\n", + "Id: 83_93 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '82_28'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_93', 'origin': '82_100~CUW~82_28#MGNP'} Metrics: ['ELUC: -8.986200608714434', 'NSGA-II_crowding_distance: 0.04882294214677154', 'NSGA-II_rank: 7', 'change: 0.2656099333479294', 'is_elite: False']\n", + "Id: 83_87 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_87', 'origin': '81_95~CUW~82_100#MGNP'} Metrics: ['ELUC: -9.007194594138749', 'NSGA-II_crowding_distance: 0.11098123446612732', 'NSGA-II_rank: 7', 'change: 0.2664719539280747', 'is_elite: False']\n", + "Id: 83_96 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_56', '82_57'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_96', 'origin': '82_56~CUW~82_57#MGNP'} Metrics: ['ELUC: -9.133723135942498', 'NSGA-II_crowding_distance: 0.17980980745903538', 'NSGA-II_rank: 2', 'change: 0.12977342994658161', 'is_elite: False']\n", + "Id: 83_38 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_20', '82_57'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_38', 'origin': '81_20~CUW~82_57#MGNP'} Metrics: ['ELUC: -9.21687512508649', 'NSGA-II_crowding_distance: 0.16575097955628387', 'NSGA-II_rank: 1', 'change: 0.12698494528027998', 'is_elite: False']\n", + "Id: 83_79 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '82_70'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_79', 'origin': '82_100~CUW~82_70#MGNP'} Metrics: ['ELUC: -9.280318667306588', 'NSGA-II_crowding_distance: 0.5870650038003273', 'NSGA-II_rank: 4', 'change: 0.21735338503319054', 'is_elite: False']\n", + "Id: 83_39 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_71', '82_28'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_39', 'origin': '82_71~CUW~82_28#MGNP'} Metrics: ['ELUC: -9.460007562120316', 'NSGA-II_crowding_distance: 0.4671235208824043', 'NSGA-II_rank: 3', 'change: 0.1498897424448401', 'is_elite: False']\n", + "Id: 83_95 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '82_23'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_95', 'origin': '82_100~CUW~82_23#MGNP'} Metrics: ['ELUC: -9.619133437451847', 'NSGA-II_crowding_distance: 0.2354379075605157', 'NSGA-II_rank: 4', 'change: 0.23497365218476227', 'is_elite: False']\n", + "Id: 83_23 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_57', '82_25'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_23', 'origin': '82_57~CUW~82_25#MGNP'} Metrics: ['ELUC: -9.670484107065015', 'NSGA-II_crowding_distance: 0.5107883586975493', 'NSGA-II_rank: 3', 'change: 0.15874786607944222', 'is_elite: False']\n", + "Id: 83_13 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_20', '82_25'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_13', 'origin': '81_20~CUW~82_25#MGNP'} Metrics: ['ELUC: -9.682819704028054', 'NSGA-II_crowding_distance: 0.5976791701453907', 'NSGA-II_rank: 2', 'change: 0.13593487235988533', 'is_elite: False']\n", + "Id: 82_57 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_57', 'origin': '81_20~CUW~81_46#MGNP'} Metrics: ['ELUC: -9.722820978484933', 'NSGA-II_crowding_distance: 0.23930921663295587', 'NSGA-II_rank: 1', 'change: 0.1337240808867949', 'is_elite: True']\n", + "Id: 83_94 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_56', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_94', 'origin': '82_56~CUW~82_100#MGNP'} Metrics: ['ELUC: -10.2740789520783', 'NSGA-II_crowding_distance: 0.32988717980220766', 'NSGA-II_rank: 6', 'change: 0.2534237457930143', 'is_elite: False']\n", + "Id: 83_44 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_72', '82_23'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_44', 'origin': '82_72~CUW~82_23#MGNP'} Metrics: ['ELUC: -10.504438787532141', 'NSGA-II_crowding_distance: 0.32715586732615937', 'NSGA-II_rank: 4', 'change: 0.24161788517221597', 'is_elite: False']\n", + "Id: 83_90 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '1_1'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_90', 'origin': '82_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.64190710778361', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.26679406891660834', 'is_elite: False']\n", + "Id: 83_85 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '82_57'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_85', 'origin': '82_100~CUW~82_57#MGNP'} Metrics: ['ELUC: -10.85666206652979', 'NSGA-II_crowding_distance: 0.32540056483402074', 'NSGA-II_rank: 6', 'change: 0.2575890005925584', 'is_elite: False']\n", + "Id: 83_67 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_70', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_67', 'origin': '82_70~CUW~81_20#MGNP'} Metrics: ['ELUC: -11.411812349162933', 'NSGA-II_crowding_distance: 0.2215615202587884', 'NSGA-II_rank: 1', 'change: 0.16114072126592383', 'is_elite: True']\n", + "Id: 83_19 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '82_36'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_19', 'origin': '1_1~CUW~82_36#MGNP'} Metrics: ['ELUC: -11.599362718998005', 'NSGA-II_crowding_distance: 0.4446811220443554', 'NSGA-II_rank: 5', 'change: 0.25140259129995784', 'is_elite: False']\n", + "Id: 83_20 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_20', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.665269964384867', 'NSGA-II_crowding_distance: 0.3712616383387104', 'NSGA-II_rank: 6', 'change: 0.281860737367492', 'is_elite: False']\n", + "Id: 83_25 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_83', '82_70'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_25', 'origin': '82_83~CUW~82_70#MGNP'} Metrics: ['ELUC: -11.886470640391225', 'NSGA-II_crowding_distance: 0.280337262071811', 'NSGA-II_rank: 1', 'change: 0.16311529936478042', 'is_elite: True']\n", + "Id: 83_84 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_25'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_84', 'origin': '2_49~CUW~82_25#MGNP'} Metrics: ['ELUC: -12.021005972153496', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2928333440905174', 'is_elite: False']\n", + "Id: 83_68 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_56', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_68', 'origin': '82_56~CUW~82_100#MGNP'} Metrics: ['ELUC: -13.206293828574452', 'NSGA-II_crowding_distance: 0.29799082877925576', 'NSGA-II_rank: 4', 'change: 0.24383480512892486', 'is_elite: False']\n", + "Id: 83_89 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_36', '82_36'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_89', 'origin': '82_36~CUW~82_36#MGNP'} Metrics: ['ELUC: -13.343276231365877', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.25526672710615084', 'is_elite: False']\n", + "Id: 83_27 Identity: {'ancestor_count': 81, 'ancestor_ids': ['80_33', '82_28'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_27', 'origin': '80_33~CUW~82_28#MGNP'} Metrics: ['ELUC: -13.355638767878398', 'NSGA-II_crowding_distance: 0.5975400400941177', 'NSGA-II_rank: 3', 'change: 0.21444229861205172', 'is_elite: False']\n", + "Id: 83_97 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '81_95'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_97', 'origin': '82_23~CUW~81_95#MGNP'} Metrics: ['ELUC: -13.644119050104253', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.25137185080729124', 'is_elite: False']\n", + "Id: 83_28 Identity: {'ancestor_count': 81, 'ancestor_ids': ['80_33', '82_28'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_28', 'origin': '80_33~CUW~82_28#MGNP'} Metrics: ['ELUC: -13.744955451020894', 'NSGA-II_crowding_distance: 0.5788491802166742', 'NSGA-II_rank: 2', 'change: 0.21068291729636437', 'is_elite: False']\n", + "Id: 83_99 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_56', '82_28'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_99', 'origin': '82_56~CUW~82_28#MGNP'} Metrics: ['ELUC: -14.037646458736727', 'NSGA-II_crowding_distance: 0.2784208495143754', 'NSGA-II_rank: 1', 'change: 0.20022589873934377', 'is_elite: True']\n", + "Id: 83_21 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_57'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_21', 'origin': '82_23~CUW~82_57#MGNP'} Metrics: ['ELUC: -14.186524418164648', 'NSGA-II_crowding_distance: 0.40147730103654167', 'NSGA-II_rank: 3', 'change: 0.2348471558411452', 'is_elite: False']\n", + "Id: 83_35 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_20', '82_93'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_35', 'origin': '81_20~CUW~82_93#MGNP'} Metrics: ['ELUC: -14.30116474297131', 'NSGA-II_crowding_distance: 0.24042956731601683', 'NSGA-II_rank: 2', 'change: 0.21181435021297265', 'is_elite: False']\n", + "Id: 83_56 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_70', '82_25'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_56', 'origin': '82_70~CUW~82_25#MGNP'} Metrics: ['ELUC: -14.331963983502899', 'NSGA-II_crowding_distance: 0.05340521109922983', 'NSGA-II_rank: 1', 'change: 0.2046891004216039', 'is_elite: False']\n", + "Id: 82_93 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_91', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_93', 'origin': '81_91~CUW~81_46#MGNP'} Metrics: ['ELUC: -14.5026411679168', 'NSGA-II_crowding_distance: 0.1564142215610223', 'NSGA-II_rank: 1', 'change: 0.20826972005152736', 'is_elite: False']\n", + "Id: 82_36 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_22'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_36', 'origin': '2_49~CUW~81_22#MGNP'} Metrics: ['ELUC: -14.721860121070682', 'NSGA-II_crowding_distance: 0.298622735613008', 'NSGA-II_rank: 2', 'change: 0.2575255751622122', 'is_elite: False']\n", + "Id: 83_70 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_25'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_70', 'origin': '2_49~CUW~82_25#MGNP'} Metrics: ['ELUC: -14.745315735487107', 'NSGA-II_crowding_distance: 0.48227983270475216', 'NSGA-II_rank: 3', 'change: 0.28884046891773335', 'is_elite: False']\n", + "Id: 83_80 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '2_49'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_80', 'origin': '81_20~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.946393261665378', 'NSGA-II_crowding_distance: 0.24233596656217474', 'NSGA-II_rank: 2', 'change: 0.2792438878355025', 'is_elite: False']\n", + "Id: 83_59 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_25', '82_93'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_59', 'origin': '82_25~CUW~82_93#MGNP'} Metrics: ['ELUC: -15.378545380769976', 'NSGA-II_crowding_distance: 0.3533175029643705', 'NSGA-II_rank: 1', 'change: 0.2335988095120297', 'is_elite: True']\n", + "Id: 83_62 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_70'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_62', 'origin': '82_23~CUW~82_70#MGNP'} Metrics: ['ELUC: -16.421892438889333', 'NSGA-II_crowding_distance: 0.23993582425859036', 'NSGA-II_rank: 2', 'change: 0.2930931229329357', 'is_elite: False']\n", + "Id: 82_23 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_23', 'origin': '81_95~CUW~81_38#MGNP'} Metrics: ['ELUC: -16.70621669696751', 'NSGA-II_crowding_distance: 0.3498800492678866', 'NSGA-II_rank: 1', 'change: 0.27629643323483516', 'is_elite: True']\n", + "Id: 83_15 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_28', '82_36'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_15', 'origin': '82_28~CUW~82_36#MGNP'} Metrics: ['ELUC: -17.369238134923798', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3028073221963312', 'is_elite: False']\n", + "Id: 83_41 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_100', '82_57'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_41', 'origin': '82_100~CUW~82_57#MGNP'} Metrics: ['ELUC: -17.433641249295682', 'NSGA-II_crowding_distance: 0.11118269771307476', 'NSGA-II_rank: 2', 'change: 0.3013690492404988', 'is_elite: False']\n", + "Id: 83_69 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_57', '82_36'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_69', 'origin': '82_57~CUW~82_36#MGNP'} Metrics: ['ELUC: -17.53849398367426', 'NSGA-II_crowding_distance: 0.1373737209142451', 'NSGA-II_rank: 1', 'change: 0.3013402254992387', 'is_elite: False']\n", + "Id: 83_77 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_57'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_77', 'origin': '2_49~CUW~82_57#MGNP'} Metrics: ['ELUC: -17.56100728148691', 'NSGA-II_crowding_distance: 0.008829824846749408', 'NSGA-II_rank: 1', 'change: 0.3027796304578505', 'is_elite: False']\n", + "Id: 83_53 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_53', 'origin': '2_49~CUW~81_20#MGNP'} Metrics: ['ELUC: -17.5953081069871', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30300595913908', 'is_elite: False']\n", + "Id: 83_31 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '82_36'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_31', 'origin': '81_95~CUW~82_36#MGNP'} Metrics: ['ELUC: -17.595846787170963', 'NSGA-II_crowding_distance: 0.0028137312554708267', 'NSGA-II_rank: 1', 'change: 0.30300155370569526', 'is_elite: False']\n", + "Id: 83_29 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_36', '2_49'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_29', 'origin': '82_36~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59663249402843', 'NSGA-II_crowding_distance: 0.0001509615698674752', 'NSGA-II_rank: 1', 'change: 0.30301461432334276', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 82_100 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_38', '81_42'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_100', 'origin': '81_38~CUW~81_42#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 83_12 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_73', '82_23'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_12', 'origin': '82_73~CUW~82_23#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 83_48 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_93', '2_49'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_48', 'origin': '82_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 83_50 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_100'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_50', 'origin': '2_49~CUW~82_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 83_55 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_23'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_55', 'origin': '2_49~CUW~82_23#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 83.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 84...:\n", + "PopulationResponse:\n", + " Generation: 84\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/84/20240220-054759\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 84 and asking ESP for generation 85...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 84 data persisted.\n", + "Evaluated candidates:\n", + "Id: 84_53 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_55', '1_1'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_53', 'origin': '83_55~CUW~1_1#MGNP'} Metrics: ['ELUC: 22.316433228833862', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.2907329580772056', 'is_elite: False']\n", + "Id: 84_51 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_25', '2_49'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_51', 'origin': '83_25~CUW~2_49#MGNP'} Metrics: ['ELUC: 13.32448175689805', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2330018825361234', 'is_elite: False']\n", + "Id: 84_67 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_20', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_67', 'origin': '81_20~CUW~83_55#MGNP'} Metrics: ['ELUC: 9.874129134128392', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28482916810266823', 'is_elite: False']\n", + "Id: 84_83 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_55', '1_1'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_83', 'origin': '83_55~CUW~1_1#MGNP'} Metrics: ['ELUC: 7.700390492244288', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2672271824016825', 'is_elite: False']\n", + "Id: 84_89 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_69', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_89', 'origin': '83_69~CUW~81_95#MGNP'} Metrics: ['ELUC: 4.409152409139373', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.23000688308322792', 'is_elite: False']\n", + "Id: 84_68 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_95', '83_59'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_68', 'origin': '81_95~CUW~83_59#MGNP'} Metrics: ['ELUC: 2.408012735081032', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.16533076562049448', 'is_elite: False']\n", + "Id: 84_28 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_57'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_28', 'origin': '82_23~CUW~82_57#MGNP'} Metrics: ['ELUC: 0.9619527252968278', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2613760916260979', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 84_55 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_55', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5197732299701425', 'NSGA-II_crowding_distance: 0.2232424004608835', 'NSGA-II_rank: 1', 'change: 0.028922443446518523', 'is_elite: True']\n", + "Id: 84_57 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_23', '83_59'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_57', 'origin': '82_23~CUW~83_59#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 84_13 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_57'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_13', 'origin': '82_23~CUW~82_57#MGNP'} Metrics: ['ELUC: -0.5663891183555326', 'NSGA-II_crowding_distance: 1.548991937264232', 'NSGA-II_rank: 6', 'change: 0.2386662765437636', 'is_elite: False']\n", + "Id: 84_90 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_95', '83_25'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_90', 'origin': '81_95~CUW~83_25#MGNP'} Metrics: ['ELUC: -0.7906509846305676', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08158821048863804', 'is_elite: False']\n", + "Id: 84_66 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_91', '1_1'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_66', 'origin': '83_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1895317627240631', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03907505872248894', 'is_elite: False']\n", + "Id: 84_12 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_12', 'origin': '81_95~CUW~81_95#MGNP'} Metrics: ['ELUC: -1.2103777149302966', 'NSGA-II_crowding_distance: 0.1511339792338054', 'NSGA-II_rank: 3', 'change: 0.0485153966908846', 'is_elite: False']\n", + "Id: 84_97 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '82_57'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_97', 'origin': '81_95~CUW~82_57#MGNP'} Metrics: ['ELUC: -1.4204269707378612', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.07326304379244901', 'is_elite: False']\n", + "Id: 84_87 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_87', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.5583215190653215', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30168740315593107', 'is_elite: False']\n", + "Id: 84_25 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_25', 'origin': '81_95~CUW~81_95#MGNP'} Metrics: ['ELUC: -1.6587190993440544', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03835386750596674', 'is_elite: False']\n", + "Id: 84_81 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_95', '83_67'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_81', 'origin': '81_95~CUW~83_67#MGNP'} Metrics: ['ELUC: -1.7724849391537252', 'NSGA-II_crowding_distance: 0.6165471188569014', 'NSGA-II_rank: 4', 'change: 0.10284557941218457', 'is_elite: False']\n", + "Id: 84_79 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_60', '83_59'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_79', 'origin': '83_60~CUW~83_59#MGNP'} Metrics: ['ELUC: -1.8381175900232842', 'NSGA-II_crowding_distance: 0.1605097493159039', 'NSGA-II_rank: 3', 'change: 0.06802164968157098', 'is_elite: False']\n", + "Id: 84_52 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_52', 'origin': '81_20~CUW~81_95#MGNP'} Metrics: ['ELUC: -1.970186277448457', 'NSGA-II_crowding_distance: 0.16345051700201335', 'NSGA-II_rank: 2', 'change: 0.05099438752114406', 'is_elite: False']\n", + "Id: 84_84 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_95', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_84', 'origin': '81_95~CUW~83_99#MGNP'} Metrics: ['ELUC: -2.0100666439564296', 'NSGA-II_crowding_distance: 0.16378351403567748', 'NSGA-II_rank: 3', 'change: 0.0774249154966877', 'is_elite: False']\n", + "Id: 81_95 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_78'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_95', 'origin': '1_1~CUW~80_78#MGNP'} Metrics: ['ELUC: -2.083618656113992', 'NSGA-II_crowding_distance: 0.24441214710437797', 'NSGA-II_rank: 1', 'change: 0.03614901748277748', 'is_elite: True']\n", + "Id: 84_60 Identity: {'ancestor_count': 82, 'ancestor_ids': ['1_1', '83_67'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_60', 'origin': '1_1~CUW~83_67#MGNP'} Metrics: ['ELUC: -2.6544037038605106', 'NSGA-II_crowding_distance: 0.35752671301903655', 'NSGA-II_rank: 3', 'change: 0.09751606902205481', 'is_elite: False']\n", + "Id: 84_18 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_23', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_18', 'origin': '82_23~CUW~83_99#MGNP'} Metrics: ['ELUC: -2.7270402728435132', 'NSGA-II_crowding_distance: 1.4329083177839754', 'NSGA-II_rank: 5', 'change: 0.21264452212079932', 'is_elite: False']\n", + "Id: 84_78 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_95', '83_91'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_78', 'origin': '81_95~CUW~83_91#MGNP'} Metrics: ['ELUC: -3.201718916673422', 'NSGA-II_crowding_distance: 0.1122558058937562', 'NSGA-II_rank: 2', 'change: 0.055927874811124156', 'is_elite: False']\n", + "Id: 84_63 Identity: {'ancestor_count': 81, 'ancestor_ids': ['83_33', '83_92'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_63', 'origin': '83_33~CUW~83_92#MGNP'} Metrics: ['ELUC: -3.219780350906091', 'NSGA-II_crowding_distance: 0.08320162541590301', 'NSGA-II_rank: 2', 'change: 0.05989920152835211', 'is_elite: False']\n", + "Id: 84_92 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '83_60'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_92', 'origin': '81_95~CUW~83_60#MGNP'} Metrics: ['ELUC: -3.5807072206516026', 'NSGA-II_crowding_distance: 0.16258246447182767', 'NSGA-II_rank: 1', 'change: 0.049904588161189256', 'is_elite: False']\n", + "Id: 84_30 Identity: {'ancestor_count': 81, 'ancestor_ids': ['1_1', '83_60'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_30', 'origin': '1_1~CUW~83_60#MGNP'} Metrics: ['ELUC: -3.6892594107435692', 'NSGA-II_crowding_distance: 0.11654807364840308', 'NSGA-II_rank: 1', 'change: 0.05741178321606986', 'is_elite: False']\n", + "Id: 84_47 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_91', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_47', 'origin': '83_91~CUW~81_95#MGNP'} Metrics: ['ELUC: -3.756100676378016', 'NSGA-II_crowding_distance: 0.26466266144405887', 'NSGA-II_rank: 2', 'change: 0.06872468180016046', 'is_elite: False']\n", + "Id: 84_29 Identity: {'ancestor_count': 81, 'ancestor_ids': ['83_92', '83_60'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_29', 'origin': '83_92~CUW~83_60#MGNP'} Metrics: ['ELUC: -4.560473125683267', 'NSGA-II_crowding_distance: 0.3142064794255041', 'NSGA-II_rank: 1', 'change: 0.06805300665022132', 'is_elite: True']\n", + "Id: 84_76 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_23', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_76', 'origin': '82_23~CUW~83_99#MGNP'} Metrics: ['ELUC: -4.614058191885695', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2553160878432571', 'is_elite: False']\n", + "Id: 84_65 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_20', '83_34'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_65', 'origin': '81_20~CUW~83_34#MGNP'} Metrics: ['ELUC: -4.693827772857999', 'NSGA-II_crowding_distance: 0.37168201227490505', 'NSGA-II_rank: 2', 'change: 0.105429588858401', 'is_elite: False']\n", + "Id: 84_24 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_25', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_24', 'origin': '83_25~CUW~81_95#MGNP'} Metrics: ['ELUC: -5.363837234993851', 'NSGA-II_crowding_distance: 0.45099666907433705', 'NSGA-II_rank: 3', 'change: 0.11582333611644156', 'is_elite: False']\n", + "Id: 84_11 Identity: {'ancestor_count': 81, 'ancestor_ids': ['83_60', '82_57'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_11', 'origin': '83_60~CUW~82_57#MGNP'} Metrics: ['ELUC: -6.3183295266881085', 'NSGA-II_crowding_distance: 0.8179571007833164', 'NSGA-II_rank: 4', 'change: 0.14212417537982047', 'is_elite: False']\n", + "Id: 84_40 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_23', '83_25'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_40', 'origin': '82_23~CUW~83_25#MGNP'} Metrics: ['ELUC: -6.369900997457033', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24574397360690958', 'is_elite: False']\n", + "Id: 84_69 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_57', '81_20'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_69', 'origin': '82_57~CUW~81_20#MGNP'} Metrics: ['ELUC: -6.419633712837191', 'NSGA-II_crowding_distance: 0.2841034188322743', 'NSGA-II_rank: 1', 'change: 0.104828701068093', 'is_elite: True']\n", + "Id: 84_71 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_20', '83_59'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_71', 'origin': '81_20~CUW~83_59#MGNP'} Metrics: ['ELUC: -7.002264252956633', 'NSGA-II_crowding_distance: 0.3603350420839404', 'NSGA-II_rank: 2', 'change: 0.11306392327912793', 'is_elite: False']\n", + "Id: 84_80 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_69', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_80', 'origin': '83_69~CUW~81_95#MGNP'} Metrics: ['ELUC: -7.012095613454127', 'NSGA-II_crowding_distance: 0.7595131091621901', 'NSGA-II_rank: 6', 'change: 0.2397954198645184', 'is_elite: False']\n", + "Id: 84_85 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_20'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_85', 'origin': '81_20~CUW~81_20#MGNP'} Metrics: ['ELUC: -7.334192098075331', 'NSGA-II_crowding_distance: 0.21850998427332416', 'NSGA-II_rank: 1', 'change: 0.1057522696744133', 'is_elite: True']\n", + "Id: 84_58 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_25', '1_1'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_58', 'origin': '83_25~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.396996163890536', 'NSGA-II_crowding_distance: 0.43100824811824534', 'NSGA-II_rank: 3', 'change: 0.1374885474213136', 'is_elite: False']\n", + "Id: 84_59 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '82_23'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_59', 'origin': '81_95~CUW~82_23#MGNP'} Metrics: ['ELUC: -7.778576304089413', 'NSGA-II_crowding_distance: 0.451008062735768', 'NSGA-II_rank: 6', 'change: 0.2541310105993634', 'is_elite: False']\n", + "Id: 84_64 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_93', '81_20'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_64', 'origin': '82_93~CUW~81_20#MGNP'} Metrics: ['ELUC: -9.36002215178249', 'NSGA-II_crowding_distance: 0.35922870665154344', 'NSGA-II_rank: 2', 'change: 0.12309539451350347', 'is_elite: False']\n", + "Id: 84_91 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_38', '83_38'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_91', 'origin': '83_38~CUW~83_38#MGNP'} Metrics: ['ELUC: -9.4488988235758', 'NSGA-II_crowding_distance: 0.19357935570611917', 'NSGA-II_rank: 1', 'change: 0.11861964829188279', 'is_elite: False']\n", + "Id: 84_98 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_20', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_98', 'origin': '81_20~CUW~83_99#MGNP'} Metrics: ['ELUC: -9.460222560038535', 'NSGA-II_crowding_distance: 0.06620124434977095', 'NSGA-II_rank: 1', 'change: 0.1274326432660321', 'is_elite: False']\n", + "Id: 84_17 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_55', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_17', 'origin': '83_55~CUW~81_95#MGNP'} Metrics: ['ELUC: -9.502161899366437', 'NSGA-II_crowding_distance: 0.7716036629525641', 'NSGA-II_rank: 5', 'change: 0.23963487337360984', 'is_elite: False']\n", + "Id: 84_73 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_55', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_73', 'origin': '83_55~CUW~81_95#MGNP'} Metrics: ['ELUC: -9.596525688926082', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2627619225868245', 'is_elite: False']\n", + "Id: 82_57 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_46'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_57', 'origin': '81_20~CUW~81_46#MGNP'} Metrics: ['ELUC: -9.722820978484933', 'NSGA-II_crowding_distance: 0.11944741422304513', 'NSGA-II_rank: 1', 'change: 0.1337240808867949', 'is_elite: False']\n", + "Id: 84_43 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_93'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_43', 'origin': '82_23~CUW~82_93#MGNP'} Metrics: ['ELUC: -9.86748425472061', 'NSGA-II_crowding_distance: 0.5025430333824841', 'NSGA-II_rank: 5', 'change: 0.2546424746132047', 'is_elite: False']\n", + "Id: 84_99 Identity: {'ancestor_count': 82, 'ancestor_ids': ['1_1', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_99', 'origin': '1_1~CUW~83_99#MGNP'} Metrics: ['ELUC: -10.328810893311383', 'NSGA-II_crowding_distance: 0.46335307128789777', 'NSGA-II_rank: 4', 'change: 0.16383618204739273', 'is_elite: False']\n", + "Id: 84_26 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_95', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_26', 'origin': '81_95~CUW~83_99#MGNP'} Metrics: ['ELUC: -10.366053822217852', 'NSGA-II_crowding_distance: 0.34297993319930176', 'NSGA-II_rank: 3', 'change: 0.14625739241487154', 'is_elite: False']\n", + "Id: 84_44 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_57', '83_38'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_44', 'origin': '82_57~CUW~83_38#MGNP'} Metrics: ['ELUC: -10.614952971062861', 'NSGA-II_crowding_distance: 0.1263871919919938', 'NSGA-II_rank: 1', 'change: 0.14347695878378494', 'is_elite: False']\n", + "Id: 84_38 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '83_25'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_38', 'origin': '83_59~CUW~83_25#MGNP'} Metrics: ['ELUC: -10.787438139818873', 'NSGA-II_crowding_distance: 0.28661890445248406', 'NSGA-II_rank: 2', 'change: 0.14512092990188882', 'is_elite: False']\n", + "Id: 84_54 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '83_33'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_54', 'origin': '83_59~CUW~83_33#MGNP'} Metrics: ['ELUC: -10.917631875664338', 'NSGA-II_crowding_distance: 0.34223378210612376', 'NSGA-II_rank: 4', 'change: 0.1803272456482535', 'is_elite: False']\n", + "Id: 84_23 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_25', '83_38'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_23', 'origin': '83_25~CUW~83_38#MGNP'} Metrics: ['ELUC: -11.329371511044547', 'NSGA-II_crowding_distance: 0.06739161686869705', 'NSGA-II_rank: 1', 'change: 0.1441715447346174', 'is_elite: False']\n", + "Id: 84_72 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_23'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_72', 'origin': '82_23~CUW~82_23#MGNP'} Metrics: ['ELUC: -11.383714469724621', 'NSGA-II_crowding_distance: 0.5851985120756525', 'NSGA-II_rank: 4', 'change: 0.22660460338435764', 'is_elite: False']\n", + "Id: 83_67 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_70', '81_20'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_67', 'origin': '82_70~CUW~81_20#MGNP'} Metrics: ['ELUC: -11.411812349162933', 'NSGA-II_crowding_distance: 0.1599882734586574', 'NSGA-II_rank: 3', 'change: 0.16114072126592383', 'is_elite: False']\n", + "Id: 84_74 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_20', '82_57'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_74', 'origin': '81_20~CUW~82_57#MGNP'} Metrics: ['ELUC: -11.643985593701949', 'NSGA-II_crowding_distance: 0.07027149609800797', 'NSGA-II_rank: 1', 'change: 0.14612211467200806', 'is_elite: False']\n", + "Id: 83_25 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_83', '82_70'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_25', 'origin': '82_83~CUW~82_70#MGNP'} Metrics: ['ELUC: -11.886470640391225', 'NSGA-II_crowding_distance: 0.4212251138469084', 'NSGA-II_rank: 3', 'change: 0.16311529936478042', 'is_elite: False']\n", + "Id: 84_94 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '83_38'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_94', 'origin': '83_59~CUW~83_38#MGNP'} Metrics: ['ELUC: -12.008750253113634', 'NSGA-II_crowding_distance: 0.5386682985423629', 'NSGA-II_rank: 2', 'change: 0.15486238412177378', 'is_elite: False']\n", + "Id: 84_50 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_93', '81_20'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_50', 'origin': '82_93~CUW~81_20#MGNP'} Metrics: ['ELUC: -12.036027182363203', 'NSGA-II_crowding_distance: 0.10763706720762048', 'NSGA-II_rank: 1', 'change: 0.15314682861506812', 'is_elite: False']\n", + "Id: 84_16 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_55', '83_25'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_16', 'origin': '83_55~CUW~83_25#MGNP'} Metrics: ['ELUC: -12.24067312416742', 'NSGA-II_crowding_distance: 0.43089344693670356', 'NSGA-II_rank: 3', 'change: 0.25799893752673764', 'is_elite: False']\n", + "Id: 84_35 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_60', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_35', 'origin': '83_60~CUW~83_55#MGNP'} Metrics: ['ELUC: -12.26174618832883', 'NSGA-II_crowding_distance: 0.14308349512086155', 'NSGA-II_rank: 3', 'change: 0.270009659684374', 'is_elite: False']\n", + "Id: 84_95 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_95', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_95', 'origin': '81_95~CUW~83_99#MGNP'} Metrics: ['ELUC: -12.26744048489418', 'NSGA-II_crowding_distance: 0.09807352019994273', 'NSGA-II_rank: 1', 'change: 0.16765839513492858', 'is_elite: False']\n", + "Id: 84_41 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '81_20'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_41', 'origin': '83_59~CUW~81_20#MGNP'} Metrics: ['ELUC: -12.442301760392164', 'NSGA-II_crowding_distance: 0.20398832298856373', 'NSGA-II_rank: 1', 'change: 0.17551517662290958', 'is_elite: False']\n", + "Id: 84_82 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '82_23'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_82', 'origin': '83_59~CUW~82_23#MGNP'} Metrics: ['ELUC: -12.761400313079962', 'NSGA-II_crowding_distance: 0.46843770208106994', 'NSGA-II_rank: 5', 'change: 0.29147437579196417', 'is_elite: False']\n", + "Id: 84_56 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_23', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_56', 'origin': '82_23~CUW~83_55#MGNP'} Metrics: ['ELUC: -12.951327438929662', 'NSGA-II_crowding_distance: 0.5664588707811515', 'NSGA-II_rank: 2', 'change: 0.2517268754993257', 'is_elite: False']\n", + "Id: 84_27 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '83_59'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_27', 'origin': '2_49~CUW~83_59#MGNP'} Metrics: ['ELUC: -12.96775661614046', 'NSGA-II_crowding_distance: 0.5849986738978519', 'NSGA-II_rank: 4', 'change: 0.2840238445948722', 'is_elite: False']\n", + "Id: 84_14 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_14', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.137350682966566', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2988839848851509', 'is_elite: False']\n", + "Id: 84_36 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_38', '82_23'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_36', 'origin': '83_38~CUW~82_23#MGNP'} Metrics: ['ELUC: -13.496727233035857', 'NSGA-II_crowding_distance: 0.18282739460148764', 'NSGA-II_rank: 3', 'change: 0.2747901043437415', 'is_elite: False']\n", + "Id: 84_21 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_99', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_21', 'origin': '83_99~CUW~83_99#MGNP'} Metrics: ['ELUC: -13.999027961448174', 'NSGA-II_crowding_distance: 0.17355255029728', 'NSGA-II_rank: 1', 'change: 0.19913839161030095', 'is_elite: False']\n", + "Id: 83_99 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_56', '82_28'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_99', 'origin': '82_56~CUW~82_28#MGNP'} Metrics: ['ELUC: -14.037646458736727', 'NSGA-II_crowding_distance: 0.03374529154457599', 'NSGA-II_rank: 1', 'change: 0.20022589873934377', 'is_elite: False']\n", + "Id: 84_100 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_93', '83_59'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_100', 'origin': '82_93~CUW~83_59#MGNP'} Metrics: ['ELUC: -14.419431984565865', 'NSGA-II_crowding_distance: 0.08222440541239293', 'NSGA-II_rank: 1', 'change: 0.20207284874490816', 'is_elite: False']\n", + "Id: 84_39 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_39', 'origin': '2_49~CUW~83_99#MGNP'} Metrics: ['ELUC: -14.493367781162092', 'NSGA-II_crowding_distance: 0.2203821084061641', 'NSGA-II_rank: 3', 'change: 0.2811049311759534', 'is_elite: False']\n", + "Id: 84_45 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '83_59'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_45', 'origin': '83_59~CUW~83_59#MGNP'} Metrics: ['ELUC: -14.75329476097628', 'NSGA-II_crowding_distance: 0.16020771111908694', 'NSGA-II_rank: 1', 'change: 0.21261505666315852', 'is_elite: False']\n", + "Id: 84_46 Identity: {'ancestor_count': 81, 'ancestor_ids': ['83_60', '82_23'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_46', 'origin': '83_60~CUW~82_23#MGNP'} Metrics: ['ELUC: -15.086548026071608', 'NSGA-II_crowding_distance: 0.26464199533985744', 'NSGA-II_rank: 2', 'change: 0.2535965836631553', 'is_elite: False']\n", + "Id: 84_96 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_96', 'origin': '2_49~CUW~81_95#MGNP'} Metrics: ['ELUC: -15.175716242699433', 'NSGA-II_crowding_distance: 0.24721744697975187', 'NSGA-II_rank: 2', 'change: 0.28474563022292454', 'is_elite: False']\n", + "Id: 83_59 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_25', '82_93'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_59', 'origin': '82_25~CUW~82_93#MGNP'} Metrics: ['ELUC: -15.378545380769976', 'NSGA-II_crowding_distance: 0.12779856973233555', 'NSGA-II_rank: 1', 'change: 0.2335988095120297', 'is_elite: False']\n", + "Id: 84_15 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_15', 'origin': '83_59~CUW~81_95#MGNP'} Metrics: ['ELUC: -15.545169290419825', 'NSGA-II_crowding_distance: 0.2186108813166388', 'NSGA-II_rank: 1', 'change: 0.23730894700508384', 'is_elite: True']\n", + "Id: 84_31 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_57', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_31', 'origin': '82_57~CUW~83_55#MGNP'} Metrics: ['ELUC: -15.785095458270016', 'NSGA-II_crowding_distance: 0.3349012977795484', 'NSGA-II_rank: 4', 'change: 0.29556963880941695', 'is_elite: False']\n", + "Id: 84_22 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_99', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_22', 'origin': '83_99~CUW~83_55#MGNP'} Metrics: ['ELUC: -16.0356472269055', 'NSGA-II_crowding_distance: 0.2016471460557715', 'NSGA-II_rank: 3', 'change: 0.2906623901535065', 'is_elite: False']\n", + "Id: 82_23 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_23', 'origin': '81_95~CUW~81_38#MGNP'} Metrics: ['ELUC: -16.70621669696751', 'NSGA-II_crowding_distance: 0.23839768148308899', 'NSGA-II_rank: 1', 'change: 0.27629643323483516', 'is_elite: True']\n", + "Id: 84_19 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_19', 'origin': '2_49~CUW~83_55#MGNP'} Metrics: ['ELUC: -16.763161192859688', 'NSGA-II_crowding_distance: 0.10641518708294428', 'NSGA-II_rank: 3', 'change: 0.2965088556271617', 'is_elite: False']\n", + "Id: 84_61 Identity: {'ancestor_count': 81, 'ancestor_ids': ['83_60', '82_23'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_61', 'origin': '83_60~CUW~82_23#MGNP'} Metrics: ['ELUC: -16.817995240096607', 'NSGA-II_crowding_distance: 0.14975230971546427', 'NSGA-II_rank: 2', 'change: 0.29021625988802313', 'is_elite: False']\n", + "Id: 84_33 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '83_59'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_33', 'origin': '2_49~CUW~83_59#MGNP'} Metrics: ['ELUC: -16.935556602752644', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.30214284602067903', 'is_elite: False']\n", + "Id: 84_42 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_23'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_42', 'origin': '82_23~CUW~82_23#MGNP'} Metrics: ['ELUC: -16.980384896135508', 'NSGA-II_crowding_distance: 0.06669240747882924', 'NSGA-II_rank: 1', 'change: 0.28408545120149137', 'is_elite: False']\n", + "Id: 84_48 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_23', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_48', 'origin': '82_23~CUW~83_55#MGNP'} Metrics: ['ELUC: -17.04080583315894', 'NSGA-II_crowding_distance: 0.07438527773027132', 'NSGA-II_rank: 2', 'change: 0.2933231549614512', 'is_elite: False']\n", + "Id: 84_62 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '1_1'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_62', 'origin': '82_23~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.0666905591052', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3015488602263801', 'is_elite: False']\n", + "Id: 84_86 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '82_23'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_86', 'origin': '82_23~CUW~82_23#MGNP'} Metrics: ['ELUC: -17.135800969373715', 'NSGA-II_crowding_distance: 0.03402963049495004', 'NSGA-II_rank: 1', 'change: 0.2889057838575962', 'is_elite: False']\n", + "Id: 84_32 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '83_33'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_32', 'origin': '82_23~CUW~83_33#MGNP'} Metrics: ['ELUC: -17.18856431061584', 'NSGA-II_crowding_distance: 0.0467032347043922', 'NSGA-II_rank: 1', 'change: 0.29070626575159336', 'is_elite: False']\n", + "Id: 84_75 Identity: {'ancestor_count': 82, 'ancestor_ids': ['81_95', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_75', 'origin': '81_95~CUW~83_55#MGNP'} Metrics: ['ELUC: -17.396923609465688', 'NSGA-II_crowding_distance: 0.06937453505795063', 'NSGA-II_rank: 2', 'change: 0.3002688363966111', 'is_elite: False']\n", + "Id: 84_88 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '83_69'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_88', 'origin': '83_59~CUW~83_69#MGNP'} Metrics: ['ELUC: -17.40015015959485', 'NSGA-II_crowding_distance: 0.04984400336229276', 'NSGA-II_rank: 1', 'change: 0.2983549010605369', 'is_elite: False']\n", + "Id: 84_37 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_23', '83_25'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_37', 'origin': '82_23~CUW~83_25#MGNP'} Metrics: ['ELUC: -17.497713472432167', 'NSGA-II_crowding_distance: 0.026003415156212607', 'NSGA-II_rank: 1', 'change: 0.30033224900417127', 'is_elite: False']\n", + "Id: 84_77 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '83_99'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_77', 'origin': '2_49~CUW~83_99#MGNP'} Metrics: ['ELUC: -17.549771250939123', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3032146750678024', 'is_elite: False']\n", + "Id: 84_93 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_23', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_93', 'origin': '82_23~CUW~83_55#MGNP'} Metrics: ['ELUC: -17.591906340449334', 'NSGA-II_crowding_distance: 0.014678377946404704', 'NSGA-II_rank: 1', 'change: 0.3028595791585457', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 83_55 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '82_23'], 'birth_generation': 83, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '83_55', 'origin': '2_49~CUW~82_23#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 84_20 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '83_91'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_20', 'origin': '2_49~CUW~83_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 84_34 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_91', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_34', 'origin': '83_91~CUW~83_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 84_49 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_55', '83_55'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_49', 'origin': '83_55~CUW~83_55#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 84_70 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '83_25'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_70', 'origin': '2_49~CUW~83_25#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 84.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 85...:\n", + "PopulationResponse:\n", + " Generation: 85\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/85/20240220-055515\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 4ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 85 and asking ESP for generation 86...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 85 data persisted.\n", + "Evaluated candidates:\n", + "Id: 85_48 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_70', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_48', 'origin': '84_70~CUW~81_95#MGNP'} Metrics: ['ELUC: 12.403283101517175', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2917243965251666', 'is_elite: False']\n", + "Id: 85_21 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '84_21'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_21', 'origin': '1_1~CUW~84_21#MGNP'} Metrics: ['ELUC: 6.74704467851774', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.13867673855732005', 'is_elite: False']\n", + "Id: 85_64 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_21', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_64', 'origin': '84_21~CUW~81_95#MGNP'} Metrics: ['ELUC: 5.573764273128057', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.10319379662517933', 'is_elite: False']\n", + "Id: 85_11 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_11', 'origin': '1_1~CUW~84_41#MGNP'} Metrics: ['ELUC: 4.460188931077581', 'NSGA-II_crowding_distance: 1.5848387547842688', 'NSGA-II_rank: 8', 'change: 0.1421804557993404', 'is_elite: False']\n", + "Id: 85_87 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_92', '84_15'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_87', 'origin': '84_92~CUW~84_15#MGNP'} Metrics: ['ELUC: 3.3381462157559563', 'NSGA-II_crowding_distance: 0.7470691333342894', 'NSGA-II_rank: 7', 'change: 0.10370573994003066', 'is_elite: False']\n", + "Id: 85_96 Identity: {'ancestor_count': 80, 'ancestor_ids': ['84_55', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_96', 'origin': '84_55~CUW~81_95#MGNP'} Metrics: ['ELUC: 0.23413267001493185', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05987532562146692', 'is_elite: False']\n", + "Id: 85_27 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '84_55'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_27', 'origin': '81_95~CUW~84_55#MGNP'} Metrics: ['ELUC: 0.12171368197991632', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.044188684924761426', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 85_79 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_41', '84_55'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_79', 'origin': '84_41~CUW~84_55#MGNP'} Metrics: ['ELUC: -0.1389777403308711', 'NSGA-II_crowding_distance: 1.3260559683909392', 'NSGA-II_rank: 7', 'change: 0.10840877975509566', 'is_elite: False']\n", + "Id: 85_100 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '84_70'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_100', 'origin': '1_1~CUW~84_70#MGNP'} Metrics: ['ELUC: -0.4947121253399106', 'NSGA-II_crowding_distance: 1.294035174133398', 'NSGA-II_rank: 8', 'change: 0.23851602852645215', 'is_elite: False']\n", + "Id: 84_55 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_55', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5197732299701425', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.028922443446518523', 'is_elite: False']\n", + "Id: 85_99 Identity: {'ancestor_count': 2, 'ancestor_ids': ['84_55', '84_55'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_99', 'origin': '84_55~CUW~84_55#MGNP'} Metrics: ['ELUC: -0.5366349835209826', 'NSGA-II_crowding_distance: 0.26935077861883594', 'NSGA-II_rank: 3', 'change: 0.05006310664091255', 'is_elite: False']\n", + "Id: 85_61 Identity: {'ancestor_count': 83, 'ancestor_ids': ['2_49', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_61', 'origin': '2_49~CUW~84_41#MGNP'} Metrics: ['ELUC: -0.5517874383101161', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.24411938081245757', 'is_elite: False']\n", + "Id: 85_16 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_29', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_16', 'origin': '84_29~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.41516124521573133', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 85_70 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_70', 'origin': '81_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.7155481107423199', 'NSGA-II_crowding_distance: 1.015480246194381', 'NSGA-II_rank: 7', 'change: 0.23189347508676078', 'is_elite: False']\n", + "Id: 85_88 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_55', '84_69'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_88', 'origin': '84_55~CUW~84_69#MGNP'} Metrics: ['ELUC: -0.7446242868686647', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.07880397210620645', 'is_elite: False']\n", + "Id: 85_73 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_69', '84_92'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_73', 'origin': '84_69~CUW~84_92#MGNP'} Metrics: ['ELUC: -0.779699010487249', 'NSGA-II_crowding_distance: 0.27582837961649076', 'NSGA-II_rank: 4', 'change: 0.07065762756373707', 'is_elite: False']\n", + "Id: 85_60 Identity: {'ancestor_count': 82, 'ancestor_ids': ['1_1', '84_69'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_60', 'origin': '1_1~CUW~84_69#MGNP'} Metrics: ['ELUC: -0.8339818386039111', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07460376448903547', 'is_elite: False']\n", + "Id: 85_58 Identity: {'ancestor_count': 2, 'ancestor_ids': ['84_55', '1_1'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_58', 'origin': '84_55~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9495250865089812', 'NSGA-II_crowding_distance: 0.2232424004608835', 'NSGA-II_rank: 1', 'change: 0.028409382533312558', 'is_elite: True']\n", + "Id: 85_38 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_38', 'origin': '81_95~CUW~81_95#MGNP'} Metrics: ['ELUC: -1.0482608459000913', 'NSGA-II_crowding_distance: 0.15309517811998274', 'NSGA-II_rank: 2', 'change: 0.03640983010632302', 'is_elite: False']\n", + "Id: 85_43 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_69', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_43', 'origin': '84_69~CUW~82_23#MGNP'} Metrics: ['ELUC: -1.0806305503653744', 'NSGA-II_crowding_distance: 0.39136217730498934', 'NSGA-II_rank: 7', 'change: 0.24883175689621642', 'is_elite: False']\n", + "Id: 85_40 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_69', '84_70'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_40', 'origin': '84_69~CUW~84_70#MGNP'} Metrics: ['ELUC: -1.5561892739158243', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.27876710745865113', 'is_elite: False']\n", + "Id: 85_49 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '84_44'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_49', 'origin': '1_1~CUW~84_44#MGNP'} Metrics: ['ELUC: -1.7481050947720835', 'NSGA-II_crowding_distance: 0.31580837676710877', 'NSGA-II_rank: 5', 'change: 0.08713112366472003', 'is_elite: False']\n", + "Id: 85_57 Identity: {'ancestor_count': 80, 'ancestor_ids': ['1_1', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_57', 'origin': '1_1~CUW~81_95#MGNP'} Metrics: ['ELUC: -1.7769519997087617', 'NSGA-II_crowding_distance: 0.1257665894268234', 'NSGA-II_rank: 2', 'change: 0.04921402263180453', 'is_elite: False']\n", + "Id: 85_54 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_55', '84_92'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_54', 'origin': '84_55~CUW~84_92#MGNP'} Metrics: ['ELUC: -2.0145759258521982', 'NSGA-II_crowding_distance: 0.051732805587034685', 'NSGA-II_rank: 2', 'change: 0.054171736554782975', 'is_elite: False']\n", + "Id: 81_95 Identity: {'ancestor_count': 79, 'ancestor_ids': ['1_1', '80_78'], 'birth_generation': 81, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '81_95', 'origin': '1_1~CUW~80_78#MGNP'} Metrics: ['ELUC: -2.083618656113992', 'NSGA-II_crowding_distance: 0.16772922677479712', 'NSGA-II_rank: 1', 'change: 0.03614901748277748', 'is_elite: False']\n", + "Id: 85_24 Identity: {'ancestor_count': 2, 'ancestor_ids': ['84_55', '1_1'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_24', 'origin': '84_55~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.262403539155817', 'NSGA-II_crowding_distance: 0.12992277448078926', 'NSGA-II_rank: 2', 'change: 0.055073866952320805', 'is_elite: False']\n", + "Id: 85_13 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_29', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_13', 'origin': '84_29~CUW~82_23#MGNP'} Metrics: ['ELUC: -2.4303503938155537', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.25959570724118025', 'is_elite: False']\n", + "Id: 85_41 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_92', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_41', 'origin': '84_92~CUW~84_41#MGNP'} Metrics: ['ELUC: -2.4668720309205643', 'NSGA-II_crowding_distance: 0.18442138250924522', 'NSGA-II_rank: 5', 'change: 0.11097570349358332', 'is_elite: False']\n", + "Id: 85_81 Identity: {'ancestor_count': 81, 'ancestor_ids': ['84_55', '84_85'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_81', 'origin': '84_55~CUW~84_85#MGNP'} Metrics: ['ELUC: -2.558931561287878', 'NSGA-II_crowding_distance: 0.17543557078522798', 'NSGA-II_rank: 5', 'change: 0.11098411848904319', 'is_elite: False']\n", + "Id: 85_83 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_55', '84_29'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_83', 'origin': '84_55~CUW~84_29#MGNP'} Metrics: ['ELUC: -2.562313381258197', 'NSGA-II_crowding_distance: 0.3875025797073026', 'NSGA-II_rank: 4', 'change: 0.07370897978992662', 'is_elite: False']\n", + "Id: 85_35 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_30', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_35', 'origin': '84_30~CUW~81_95#MGNP'} Metrics: ['ELUC: -2.6755948660018665', 'NSGA-II_crowding_distance: 0.2179509242320003', 'NSGA-II_rank: 1', 'change: 0.04916410977470227', 'is_elite: False']\n", + "Id: 85_23 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_92', '84_44'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_23', 'origin': '84_92~CUW~84_44#MGNP'} Metrics: ['ELUC: -2.802678699444059', 'NSGA-II_crowding_distance: 0.28076461661315666', 'NSGA-II_rank: 3', 'change: 0.06603671259313', 'is_elite: False']\n", + "Id: 85_95 Identity: {'ancestor_count': 80, 'ancestor_ids': ['84_55', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_95', 'origin': '84_55~CUW~81_95#MGNP'} Metrics: ['ELUC: -2.938632673683213', 'NSGA-II_crowding_distance: 0.16852523878810696', 'NSGA-II_rank: 3', 'change: 0.08396642998169329', 'is_elite: False']\n", + "Id: 85_98 Identity: {'ancestor_count': 82, 'ancestor_ids': ['1_1', '84_29'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_98', 'origin': '1_1~CUW~84_29#MGNP'} Metrics: ['ELUC: -3.516507923754853', 'NSGA-II_crowding_distance: 0.18972863267464235', 'NSGA-II_rank: 2', 'change: 0.06423922579241888', 'is_elite: False']\n", + "Id: 85_92 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '1_1'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_92', 'origin': '83_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.7524526018722404', 'NSGA-II_crowding_distance: 1.6649244667874463', 'NSGA-II_rank: 6', 'change: 0.12432456577717207', 'is_elite: False']\n", + "Id: 85_65 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_29', '84_15'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_65', 'origin': '84_29~CUW~84_15#MGNP'} Metrics: ['ELUC: -4.031267600802728', 'NSGA-II_crowding_distance: 0.2802900162723162', 'NSGA-II_rank: 4', 'change: 0.10156744478430492', 'is_elite: False']\n", + "Id: 85_53 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_69', '1_1'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_53', 'origin': '84_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.046587289204224', 'NSGA-II_crowding_distance: 0.15086148254760764', 'NSGA-II_rank: 3', 'change: 0.0897938289671356', 'is_elite: False']\n", + "Id: 85_19 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_29', '84_15'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_19', 'origin': '84_29~CUW~84_15#MGNP'} Metrics: ['ELUC: -4.363196290452668', 'NSGA-II_crowding_distance: 0.3611727846984837', 'NSGA-II_rank: 5', 'change: 0.11306998623741908', 'is_elite: False']\n", + "Id: 85_80 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_55', '84_21'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_80', 'origin': '84_55~CUW~84_21#MGNP'} Metrics: ['ELUC: -4.414742465174976', 'NSGA-II_crowding_distance: 0.23405074047511287', 'NSGA-II_rank: 4', 'change: 0.10453275677998099', 'is_elite: False']\n", + "Id: 85_84 Identity: {'ancestor_count': 82, 'ancestor_ids': ['1_1', '84_29'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_84', 'origin': '1_1~CUW~84_29#MGNP'} Metrics: ['ELUC: -4.486764927632902', 'NSGA-II_crowding_distance: 0.16322899236874608', 'NSGA-II_rank: 1', 'change: 0.06039858330048779', 'is_elite: False']\n", + "Id: 85_39 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_69', '1_1'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_39', 'origin': '84_69~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.548032237742002', 'NSGA-II_crowding_distance: 0.1645723561682359', 'NSGA-II_rank: 3', 'change: 0.09669467554146847', 'is_elite: False']\n", + "Id: 84_29 Identity: {'ancestor_count': 81, 'ancestor_ids': ['83_92', '83_60'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_29', 'origin': '83_92~CUW~83_60#MGNP'} Metrics: ['ELUC: -4.560473125683267', 'NSGA-II_crowding_distance: 0.1387304080885885', 'NSGA-II_rank: 2', 'change: 0.06805300665022132', 'is_elite: False']\n", + "Id: 85_86 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_44', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_86', 'origin': '84_44~CUW~81_95#MGNP'} Metrics: ['ELUC: -4.61601239939094', 'NSGA-II_crowding_distance: 0.06276296191110822', 'NSGA-II_rank: 1', 'change: 0.0649385199211703', 'is_elite: False']\n", + "Id: 85_50 Identity: {'ancestor_count': 82, 'ancestor_ids': ['82_57', '84_29'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_50', 'origin': '82_57~CUW~84_29#MGNP'} Metrics: ['ELUC: -4.680690406929018', 'NSGA-II_crowding_distance: 0.24594566768196344', 'NSGA-II_rank: 2', 'change: 0.08221642355224756', 'is_elite: False']\n", + "Id: 85_76 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_85', '84_29'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_76', 'origin': '84_85~CUW~84_29#MGNP'} Metrics: ['ELUC: -4.697965363682467', 'NSGA-II_crowding_distance: 0.054060823782062145', 'NSGA-II_rank: 1', 'change: 0.07554151593784708', 'is_elite: False']\n", + "Id: 85_68 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_29', '84_85'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_68', 'origin': '84_29~CUW~84_85#MGNP'} Metrics: ['ELUC: -4.85995853443804', 'NSGA-II_crowding_distance: 0.11055575461585496', 'NSGA-II_rank: 1', 'change: 0.07692922387026914', 'is_elite: False']\n", + "Id: 85_15 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '81_95'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_15', 'origin': '83_59~CUW~81_95#MGNP'} Metrics: ['ELUC: -4.921534660094409', 'NSGA-II_crowding_distance: 0.6530995534474436', 'NSGA-II_rank: 5', 'change: 0.14351544800091148', 'is_elite: False']\n", + "Id: 85_82 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_91', '84_69'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_82', 'origin': '84_91~CUW~84_69#MGNP'} Metrics: ['ELUC: -5.751771848241206', 'NSGA-II_crowding_distance: 0.15056625140441615', 'NSGA-II_rank: 3', 'change: 0.10454818379262931', 'is_elite: False']\n", + "Id: 85_45 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_85', '84_91'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_45', 'origin': '84_85~CUW~84_91#MGNP'} Metrics: ['ELUC: -5.76910397482249', 'NSGA-II_crowding_distance: 0.10952586589938004', 'NSGA-II_rank: 1', 'change: 0.0903513369893667', 'is_elite: False']\n", + "Id: 85_51 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_85', '84_69'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_51', 'origin': '84_85~CUW~84_69#MGNP'} Metrics: ['ELUC: -5.812115785642985', 'NSGA-II_crowding_distance: 0.07857203940298885', 'NSGA-II_rank: 1', 'change: 0.0934508994248355', 'is_elite: False']\n", + "Id: 85_56 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_70', '1_1'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_56', 'origin': '84_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.834045601107869', 'NSGA-II_crowding_distance: 1.331550240939492', 'NSGA-II_rank: 6', 'change: 0.2588487689691598', 'is_elite: False']\n", + "Id: 85_72 Identity: {'ancestor_count': 83, 'ancestor_ids': ['82_23', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_72', 'origin': '82_23~CUW~84_41#MGNP'} Metrics: ['ELUC: -6.176543672245346', 'NSGA-II_crowding_distance: 0.8372277530317104', 'NSGA-II_rank: 5', 'change: 0.2169126644010439', 'is_elite: False']\n", + "Id: 85_91 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '84_44'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_91', 'origin': '1_1~CUW~84_44#MGNP'} Metrics: ['ELUC: -6.316620325791313', 'NSGA-II_crowding_distance: 0.8048806421935011', 'NSGA-II_rank: 4', 'change: 0.11478944103896993', 'is_elite: False']\n", + "Id: 84_69 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_57', '81_20'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_69', 'origin': '82_57~CUW~81_20#MGNP'} Metrics: ['ELUC: -6.419633712837191', 'NSGA-II_crowding_distance: 0.1391440841568798', 'NSGA-II_rank: 3', 'change: 0.104828701068093', 'is_elite: False']\n", + "Id: 85_97 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_69', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_97', 'origin': '84_69~CUW~84_41#MGNP'} Metrics: ['ELUC: -6.583086822721992', 'NSGA-II_crowding_distance: 0.20896927845879146', 'NSGA-II_rank: 2', 'change: 0.10060236252358488', 'is_elite: False']\n", + "Id: 85_25 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '84_45'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_25', 'origin': '1_1~CUW~84_45#MGNP'} Metrics: ['ELUC: -6.615998424266885', 'NSGA-II_crowding_distance: 0.22207540617009122', 'NSGA-II_rank: 3', 'change: 0.12696707795706402', 'is_elite: False']\n", + "Id: 85_94 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_91', '84_55'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_94', 'origin': '84_91~CUW~84_55#MGNP'} Metrics: ['ELUC: -6.618069885262213', 'NSGA-II_crowding_distance: 0.08152339782156634', 'NSGA-II_rank: 2', 'change: 0.1062738790496108', 'is_elite: False']\n", + "Id: 85_42 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_85', '84_29'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_42', 'origin': '84_85~CUW~84_29#MGNP'} Metrics: ['ELUC: -6.767017303037045', 'NSGA-II_crowding_distance: 0.12779598639489118', 'NSGA-II_rank: 1', 'change: 0.09686058581544377', 'is_elite: False']\n", + "Id: 85_74 Identity: {'ancestor_count': 83, 'ancestor_ids': ['81_95', '84_91'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_74', 'origin': '81_95~CUW~84_91#MGNP'} Metrics: ['ELUC: -7.041996440268124', 'NSGA-II_crowding_distance: 0.19072352898015943', 'NSGA-II_rank: 2', 'change: 0.11486928254944569', 'is_elite: False']\n", + "Id: 84_85 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_20'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_85', 'origin': '81_20~CUW~81_20#MGNP'} Metrics: ['ELUC: -7.334192098075331', 'NSGA-II_crowding_distance: 0.22000834176871858', 'NSGA-II_rank: 1', 'change: 0.1057522696744133', 'is_elite: True']\n", + "Id: 85_36 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_36', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.698228867116312', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2717752941402047', 'is_elite: False']\n", + "Id: 85_55 Identity: {'ancestor_count': 83, 'ancestor_ids': ['2_49', '84_70'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_55', 'origin': '2_49~CUW~84_70#MGNP'} Metrics: ['ELUC: -7.7240649231896485', 'NSGA-II_crowding_distance: 0.5053558830175193', 'NSGA-II_rank: 5', 'change: 0.26788426794398496', 'is_elite: False']\n", + "Id: 85_26 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_26', 'origin': '81_95~CUW~82_23#MGNP'} Metrics: ['ELUC: -8.173267931493502', 'NSGA-II_crowding_distance: 0.7664813272839318', 'NSGA-II_rank: 4', 'change: 0.21950142748343576', 'is_elite: False']\n", + "Id: 85_31 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_29', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_31', 'origin': '84_29~CUW~84_41#MGNP'} Metrics: ['ELUC: -8.55183753395275', 'NSGA-II_crowding_distance: 0.3338569344335739', 'NSGA-II_rank: 3', 'change: 0.12764485293347227', 'is_elite: False']\n", + "Id: 85_47 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_55', '84_70'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_47', 'origin': '84_55~CUW~84_70#MGNP'} Metrics: ['ELUC: -8.583703844345449', 'NSGA-II_crowding_distance: 0.37601592096928127', 'NSGA-II_rank: 4', 'change: 0.24651186783110193', 'is_elite: False']\n", + "Id: 85_29 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_69', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_29', 'origin': '84_69~CUW~82_23#MGNP'} Metrics: ['ELUC: -8.645871608636439', 'NSGA-II_crowding_distance: 0.4777187624414354', 'NSGA-II_rank: 5', 'change: 0.27774433475326643', 'is_elite: False']\n", + "Id: 85_14 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_69', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_14', 'origin': '84_69~CUW~84_41#MGNP'} Metrics: ['ELUC: -8.817214292887792', 'NSGA-II_crowding_distance: 0.2533326657462633', 'NSGA-II_rank: 2', 'change: 0.1211457048608933', 'is_elite: False']\n", + "Id: 85_17 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_29', '84_44'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_17', 'origin': '84_29~CUW~84_44#MGNP'} Metrics: ['ELUC: -9.469482805223066', 'NSGA-II_crowding_distance: 0.2612008987749954', 'NSGA-II_rank: 1', 'change: 0.1166444995902892', 'is_elite: True']\n", + "Id: 85_75 Identity: {'ancestor_count': 81, 'ancestor_ids': ['81_95', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_75', 'origin': '81_95~CUW~82_23#MGNP'} Metrics: ['ELUC: -9.843087292680986', 'NSGA-II_crowding_distance: 0.3489761892779252', 'NSGA-II_rank: 4', 'change: 0.27466974278379663', 'is_elite: False']\n", + "Id: 85_46 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '1_1'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_46', 'origin': '83_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.90030130228375', 'NSGA-II_crowding_distance: 0.8677653310935274', 'NSGA-II_rank: 3', 'change: 0.15990984740773656', 'is_elite: False']\n", + "Id: 85_66 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_15', '82_57'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_66', 'origin': '84_15~CUW~82_57#MGNP'} Metrics: ['ELUC: -10.167251131099864', 'NSGA-II_crowding_distance: 0.2564474499334055', 'NSGA-II_rank: 2', 'change: 0.13126582825028504', 'is_elite: False']\n", + "Id: 85_90 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_44', '84_29'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_90', 'origin': '84_44~CUW~84_29#MGNP'} Metrics: ['ELUC: -10.437100661620907', 'NSGA-II_crowding_distance: 0.12182258644558847', 'NSGA-II_rank: 1', 'change: 0.13103148230301762', 'is_elite: False']\n", + "Id: 85_62 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_69', '84_91'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_62', 'origin': '84_69~CUW~84_91#MGNP'} Metrics: ['ELUC: -10.64292109180304', 'NSGA-II_crowding_distance: 0.1306767162542603', 'NSGA-II_rank: 1', 'change: 0.13308003515370134', 'is_elite: False']\n", + "Id: 85_77 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_85', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_77', 'origin': '84_85~CUW~84_41#MGNP'} Metrics: ['ELUC: -10.835694401719161', 'NSGA-II_crowding_distance: 0.7026551689614539', 'NSGA-II_rank: 2', 'change: 0.15657284945538397', 'is_elite: False']\n", + "Id: 85_78 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_41', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_78', 'origin': '84_41~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.168793349616497', 'NSGA-II_crowding_distance: 0.1899434003136503', 'NSGA-II_rank: 4', 'change: 0.2801653130221247', 'is_elite: False']\n", + "Id: 85_20 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_85', '84_45'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_20', 'origin': '84_85~CUW~84_45#MGNP'} Metrics: ['ELUC: -11.634620756363477', 'NSGA-II_crowding_distance: 0.3299468699408932', 'NSGA-II_rank: 1', 'change: 0.1497002171757431', 'is_elite: True']\n", + "Id: 85_22 Identity: {'ancestor_count': 83, 'ancestor_ids': ['82_23', '84_15'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_22', 'origin': '82_23~CUW~84_15#MGNP'} Metrics: ['ELUC: -11.9791065582957', 'NSGA-II_crowding_distance: 0.1370100904788393', 'NSGA-II_rank: 4', 'change: 0.28063162293208127', 'is_elite: False']\n", + "Id: 85_32 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '84_69'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_32', 'origin': '2_49~CUW~84_69#MGNP'} Metrics: ['ELUC: -12.295263395016631', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2844359175199826', 'is_elite: False']\n", + "Id: 85_71 Identity: {'ancestor_count': 83, 'ancestor_ids': ['2_49', '84_41'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_71', 'origin': '2_49~CUW~84_41#MGNP'} Metrics: ['ELUC: -12.863362784348732', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2818588048109239', 'is_elite: False']\n", + "Id: 85_33 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_15', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_33', 'origin': '84_15~CUW~82_23#MGNP'} Metrics: ['ELUC: -13.190349343661108', 'NSGA-II_crowding_distance: 0.2692273645741086', 'NSGA-II_rank: 1', 'change: 0.18829818560162756', 'is_elite: True']\n", + "Id: 85_52 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_52', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.526435689058971', 'NSGA-II_crowding_distance: 0.8156530337927113', 'NSGA-II_rank: 3', 'change: 0.2746073114011926', 'is_elite: False']\n", + "Id: 85_93 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_21', '82_57'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_93', 'origin': '84_21~CUW~82_57#MGNP'} Metrics: ['ELUC: -13.840404163180791', 'NSGA-II_crowding_distance: 0.2769369249016501', 'NSGA-II_rank: 1', 'change: 0.19259883869877753', 'is_elite: True']\n", + "Id: 85_59 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_91', '84_70'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_59', 'origin': '84_91~CUW~84_70#MGNP'} Metrics: ['ELUC: -15.315060846628697', 'NSGA-II_crowding_distance: 0.2637638855167052', 'NSGA-II_rank: 3', 'change: 0.2853229054616015', 'is_elite: False']\n", + "Id: 85_18 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_91', '84_15'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_18', 'origin': '84_91~CUW~84_15#MGNP'} Metrics: ['ELUC: -15.413861005177438', 'NSGA-II_crowding_distance: 0.8517728474232725', 'NSGA-II_rank: 2', 'change: 0.2330031571460521', 'is_elite: False']\n", + "Id: 85_67 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_15', '84_15'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_67', 'origin': '84_15~CUW~84_15#MGNP'} Metrics: ['ELUC: -15.438784776818347', 'NSGA-II_crowding_distance: 0.24680294245211115', 'NSGA-II_rank: 1', 'change: 0.2327733500830416', 'is_elite: True']\n", + "Id: 85_89 Identity: {'ancestor_count': 81, 'ancestor_ids': ['2_49', '84_85'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_89', 'origin': '2_49~CUW~84_85#MGNP'} Metrics: ['ELUC: -15.445950894176748', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3122614755294934', 'is_elite: False']\n", + "Id: 84_15 Identity: {'ancestor_count': 82, 'ancestor_ids': ['83_59', '81_95'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_15', 'origin': '83_59~CUW~81_95#MGNP'} Metrics: ['ELUC: -15.545169290419825', 'NSGA-II_crowding_distance: 0.0661998178763055', 'NSGA-II_rank: 1', 'change: 0.23730894700508384', 'is_elite: False']\n", + "Id: 85_30 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_21', '84_45'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_30', 'origin': '84_21~CUW~84_45#MGNP'} Metrics: ['ELUC: -15.784430604139455', 'NSGA-II_crowding_distance: 0.19669973891887188', 'NSGA-II_rank: 1', 'change: 0.24666018422630112', 'is_elite: False']\n", + "Id: 85_34 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_92', '84_70'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_34', 'origin': '84_92~CUW~84_70#MGNP'} Metrics: ['ELUC: -16.207989982870366', 'NSGA-II_crowding_distance: 0.3219864834070932', 'NSGA-II_rank: 2', 'change: 0.2961411790103377', 'is_elite: False']\n", + "Id: 82_23 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '81_38'], 'birth_generation': 82, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '82_23', 'origin': '81_95~CUW~81_38#MGNP'} Metrics: ['ELUC: -16.70621669696751', 'NSGA-II_crowding_distance: 0.15540908174631135', 'NSGA-II_rank: 1', 'change: 0.27629643323483516', 'is_elite: False']\n", + "Id: 85_63 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_91', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_63', 'origin': '84_91~CUW~82_23#MGNP'} Metrics: ['ELUC: -16.738364859386383', 'NSGA-II_crowding_distance: 0.06265047567434687', 'NSGA-II_rank: 1', 'change: 0.27684223254713985', 'is_elite: False']\n", + "Id: 85_12 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_69', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_12', 'origin': '84_69~CUW~82_23#MGNP'} Metrics: ['ELUC: -16.792883910053515', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.29647947165827654', 'is_elite: False']\n", + "Id: 85_28 Identity: {'ancestor_count': 83, 'ancestor_ids': ['83_59', '84_70'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_28', 'origin': '83_59~CUW~84_70#MGNP'} Metrics: ['ELUC: -17.021423972582625', 'NSGA-II_crowding_distance: 0.13629763043731152', 'NSGA-II_rank: 1', 'change: 0.2896407743669808', 'is_elite: False']\n", + "Id: 85_44 Identity: {'ancestor_count': 82, 'ancestor_ids': ['84_69', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_44', 'origin': '84_69~CUW~82_23#MGNP'} Metrics: ['ELUC: -17.592830796866053', 'NSGA-II_crowding_distance: 0.07759947869351776', 'NSGA-II_rank: 1', 'change: 0.3030098577134994', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 84_70 Identity: {'ancestor_count': 82, 'ancestor_ids': ['2_49', '83_25'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_70', 'origin': '2_49~CUW~83_25#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 85_37 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_37', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 85_69 Identity: {'ancestor_count': 81, 'ancestor_ids': ['82_23', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_69', 'origin': '82_23~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 85_85 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_15', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_85', 'origin': '84_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 85.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 86...:\n", + "PopulationResponse:\n", + " Generation: 86\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/86/20240220-060234\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 86 and asking ESP for generation 87...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 86 data persisted.\n", + "Evaluated candidates:\n", + "Id: 86_26 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_26', 'origin': '85_33~CUW~85_85#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 86_21 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '2_49'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_21', 'origin': '85_33~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.001471943806568', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2978433770473753', 'is_elite: False']\n", + "Id: 86_42 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_42', 'origin': '1_1~CUW~85_67#MGNP'} Metrics: ['ELUC: 7.891170487073816', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.19367163087554806', 'is_elite: False']\n", + "Id: 86_13 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_35', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_13', 'origin': '85_35~CUW~85_93#MGNP'} Metrics: ['ELUC: 6.54362189583865', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.1507000891338151', 'is_elite: False']\n", + "Id: 86_87 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_87', 'origin': '2_49~CUW~85_17#MGNP'} Metrics: ['ELUC: 5.449021884060304', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2489606647610732', 'is_elite: False']\n", + "Id: 86_71 Identity: {'ancestor_count': 84, 'ancestor_ids': ['81_95', '85_28'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_71', 'origin': '81_95~CUW~85_28#MGNP'} Metrics: ['ELUC: 5.2401182144435765', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.251481419097018', 'is_elite: False']\n", + "Id: 86_48 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '85_30'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_48', 'origin': '1_1~CUW~85_30#MGNP'} Metrics: ['ELUC: 3.660893121702842', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.08721875138993666', 'is_elite: False']\n", + "Id: 86_51 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_35', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_51', 'origin': '85_35~CUW~85_93#MGNP'} Metrics: ['ELUC: 3.2490837445205814', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.12423144715575947', 'is_elite: False']\n", + "Id: 86_96 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '2_49'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_96', 'origin': '85_17~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.5390658725417463', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2448183855989648', 'is_elite: False']\n", + "Id: 86_12 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '81_95'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_12', 'origin': '85_33~CUW~81_95#MGNP'} Metrics: ['ELUC: 1.3776039003712501', 'NSGA-II_crowding_distance: 1.096047326989859', 'NSGA-II_rank: 5', 'change: 0.1446271962737462', 'is_elite: False']\n", + "Id: 86_34 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_28', '1_1'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_34', 'origin': '85_28~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.5945429929110605', 'NSGA-II_crowding_distance: 0.9308090675438995', 'NSGA-II_rank: 7', 'change: 0.22631394565304305', 'is_elite: False']\n", + "Id: 86_54 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_28', '85_35'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_54', 'origin': '85_28~CUW~85_35#MGNP'} Metrics: ['ELUC: 0.12645249267037384', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23782461370603125', 'is_elite: False']\n", + "Id: 86_62 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_30', '85_84'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_62', 'origin': '85_30~CUW~85_84#MGNP'} Metrics: ['ELUC: 0.09977182856139943', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.0931736838057863', 'is_elite: False']\n", + "Id: 86_46 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_35', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_46', 'origin': '85_35~CUW~85_33#MGNP'} Metrics: ['ELUC: 0.004193149407442726', 'NSGA-II_crowding_distance: 0.9820192885170663', 'NSGA-II_rank: 6', 'change: 0.1874614068296616', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 86_33 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '2_49'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_33', 'origin': '85_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 85_58 Identity: {'ancestor_count': 2, 'ancestor_ids': ['84_55', '1_1'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_58', 'origin': '84_55~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9495250865089812', 'NSGA-II_crowding_distance: 0.19052996649312964', 'NSGA-II_rank: 1', 'change: 0.028409382533312558', 'is_elite: False']\n", + "Id: 86_43 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_95', '1_1'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_43', 'origin': '81_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1468153712959464', 'NSGA-II_crowding_distance: 0.1230604420248221', 'NSGA-II_rank: 1', 'change: 0.042286196639914606', 'is_elite: False']\n", + "Id: 86_84 Identity: {'ancestor_count': 81, 'ancestor_ids': ['84_85', '1_1'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_84', 'origin': '84_85~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.9708791868803133', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.07517193452112832', 'is_elite: False']\n", + "Id: 86_16 Identity: {'ancestor_count': 84, 'ancestor_ids': ['82_23', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_16', 'origin': '82_23~CUW~85_85#MGNP'} Metrics: ['ELUC: -2.0380701854503878', 'NSGA-II_crowding_distance: 0.41082731571859815', 'NSGA-II_rank: 7', 'change: 0.23206541852892576', 'is_elite: False']\n", + "Id: 86_53 Identity: {'ancestor_count': 83, 'ancestor_ids': ['85_84', '85_58'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_53', 'origin': '85_84~CUW~85_58#MGNP'} Metrics: ['ELUC: -2.1289109038996554', 'NSGA-II_crowding_distance: 0.14869546712659268', 'NSGA-II_rank: 1', 'change: 0.04511333518448471', 'is_elite: False']\n", + "Id: 86_44 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_58', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_44', 'origin': '85_58~CUW~85_93#MGNP'} Metrics: ['ELUC: -2.6212321007399875', 'NSGA-II_crowding_distance: 1.2835928831371684', 'NSGA-II_rank: 4', 'change: 0.11458440859035832', 'is_elite: False']\n", + "Id: 86_89 Identity: {'ancestor_count': 84, 'ancestor_ids': ['81_95', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_89', 'origin': '81_95~CUW~85_93#MGNP'} Metrics: ['ELUC: -3.087479733536773', 'NSGA-II_crowding_distance: 0.6036113483660819', 'NSGA-II_rank: 3', 'change: 0.09215558103258142', 'is_elite: False']\n", + "Id: 86_83 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '85_84'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_83', 'origin': '1_1~CUW~85_84#MGNP'} Metrics: ['ELUC: -3.511415664087156', 'NSGA-II_crowding_distance: 0.23180729849768328', 'NSGA-II_rank: 1', 'change: 0.04652561459631126', 'is_elite: True']\n", + "Id: 86_35 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_84', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_35', 'origin': '85_84~CUW~85_17#MGNP'} Metrics: ['ELUC: -3.5273941233860953', 'NSGA-II_crowding_distance: 0.20278354463892542', 'NSGA-II_rank: 2', 'change: 0.07975966439067292', 'is_elite: False']\n", + "Id: 86_27 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_20', '85_58'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_27', 'origin': '85_20~CUW~85_58#MGNP'} Metrics: ['ELUC: -4.230482534262296', 'NSGA-II_crowding_distance: 0.36169019689664983', 'NSGA-II_rank: 2', 'change: 0.08842144678361764', 'is_elite: False']\n", + "Id: 86_69 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '1_1'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_69', 'origin': '85_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.387758416251311', 'NSGA-II_crowding_distance: 0.28525398860443607', 'NSGA-II_rank: 1', 'change: 0.0759461286963884', 'is_elite: True']\n", + "Id: 86_36 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_36', 'origin': '85_33~CUW~85_20#MGNP'} Metrics: ['ELUC: -4.511571408247111', 'NSGA-II_crowding_distance: 0.5251482702517803', 'NSGA-II_rank: 7', 'change: 0.23912115904153775', 'is_elite: False']\n", + "Id: 86_40 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_40', 'origin': '85_67~CUW~85_33#MGNP'} Metrics: ['ELUC: -4.575643792767026', 'NSGA-II_crowding_distance: 0.4811834585611424', 'NSGA-II_rank: 3', 'change: 0.1338083347578945', 'is_elite: False']\n", + "Id: 86_68 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '1_1'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_68', 'origin': '85_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.377107646775525', 'NSGA-II_crowding_distance: 0.6643263267844468', 'NSGA-II_rank: 6', 'change: 0.1984205089516838', 'is_elite: False']\n", + "Id: 86_29 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_58', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_29', 'origin': '85_58~CUW~85_17#MGNP'} Metrics: ['ELUC: -5.803928675583575', 'NSGA-II_crowding_distance: 0.2674731546973712', 'NSGA-II_rank: 1', 'change: 0.09273439544794741', 'is_elite: True']\n", + "Id: 86_92 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_92', 'origin': '2_49~CUW~85_67#MGNP'} Metrics: ['ELUC: -6.044373652659297', 'NSGA-II_crowding_distance: 0.35729182476237076', 'NSGA-II_rank: 7', 'change: 0.262851372022445', 'is_elite: False']\n", + "Id: 86_61 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '2_49'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_61', 'origin': '85_17~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.484984756002168', 'NSGA-II_crowding_distance: 0.54404266220432', 'NSGA-II_rank: 7', 'change: 0.2643690971720908', 'is_elite: False']\n", + "Id: 86_64 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_64', 'origin': '85_17~CUW~85_67#MGNP'} Metrics: ['ELUC: -6.783956546407916', 'NSGA-II_crowding_distance: 0.46559403300098845', 'NSGA-II_rank: 3', 'change: 0.15844355034387425', 'is_elite: False']\n", + "Id: 86_82 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_84', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_82', 'origin': '85_84~CUW~85_17#MGNP'} Metrics: ['ELUC: -7.118647761470737', 'NSGA-II_crowding_distance: 0.39451060778319047', 'NSGA-II_rank: 2', 'change: 0.10979451303280124', 'is_elite: False']\n", + "Id: 84_85 Identity: {'ancestor_count': 80, 'ancestor_ids': ['81_20', '81_20'], 'birth_generation': 84, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '84_85', 'origin': '81_20~CUW~81_20#MGNP'} Metrics: ['ELUC: -7.334192098075331', 'NSGA-II_crowding_distance: 0.15348625360696125', 'NSGA-II_rank: 1', 'change: 0.1057522696744133', 'is_elite: False']\n", + "Id: 86_59 Identity: {'ancestor_count': 84, 'ancestor_ids': ['82_23', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_59', 'origin': '82_23~CUW~85_93#MGNP'} Metrics: ['ELUC: -7.447153186616337', 'NSGA-II_crowding_distance: 0.5550364401045114', 'NSGA-II_rank: 6', 'change: 0.22439086521293317', 'is_elite: False']\n", + "Id: 86_37 Identity: {'ancestor_count': 84, 'ancestor_ids': ['84_85', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_37', 'origin': '84_85~CUW~85_20#MGNP'} Metrics: ['ELUC: -7.634285505428248', 'NSGA-II_crowding_distance: 0.15795003773376648', 'NSGA-II_rank: 1', 'change: 0.10746955352726063', 'is_elite: False']\n", + "Id: 86_19 Identity: {'ancestor_count': 84, 'ancestor_ids': ['84_85', '85_30'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_19', 'origin': '84_85~CUW~85_30#MGNP'} Metrics: ['ELUC: -7.77546842582233', 'NSGA-II_crowding_distance: 0.16723637663465418', 'NSGA-II_rank: 2', 'change: 0.12660886529766616', 'is_elite: False']\n", + "Id: 86_94 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_94', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.854248058985703', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.3085006531667503', 'is_elite: False']\n", + "Id: 86_100 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_58', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_100', 'origin': '85_58~CUW~85_33#MGNP'} Metrics: ['ELUC: -8.025856170470114', 'NSGA-II_crowding_distance: 1.0638757491111541', 'NSGA-II_rank: 5', 'change: 0.1770444056244315', 'is_elite: False']\n", + "Id: 86_58 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_93', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_58', 'origin': '85_93~CUW~85_20#MGNP'} Metrics: ['ELUC: -8.467240170899204', 'NSGA-II_crowding_distance: 0.13969845257229352', 'NSGA-II_rank: 2', 'change: 0.12823062508291605', 'is_elite: False']\n", + "Id: 86_88 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_58', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_88', 'origin': '85_58~CUW~85_85#MGNP'} Metrics: ['ELUC: -8.718859833092603', 'NSGA-II_crowding_distance: 0.41854086744454755', 'NSGA-II_rank: 6', 'change: 0.2511392004432427', 'is_elite: False']\n", + "Id: 86_41 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_41', 'origin': '1_1~CUW~85_67#MGNP'} Metrics: ['ELUC: -8.843534977305094', 'NSGA-II_crowding_distance: 0.2273655706913093', 'NSGA-II_rank: 2', 'change: 0.1428617547214683', 'is_elite: False']\n", + "Id: 86_20 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_20', 'origin': '85_33~CUW~85_67#MGNP'} Metrics: ['ELUC: -8.918469051100582', 'NSGA-II_crowding_distance: 0.35672797778403315', 'NSGA-II_rank: 5', 'change: 0.20204446744031906', 'is_elite: False']\n", + "Id: 85_17 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_29', '84_44'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_17', 'origin': '84_29~CUW~84_44#MGNP'} Metrics: ['ELUC: -9.469482805223066', 'NSGA-II_crowding_distance: 0.20542183786812557', 'NSGA-II_rank: 1', 'change: 0.1166444995902892', 'is_elite: True']\n", + "Id: 86_24 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_42', '85_30'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_24', 'origin': '85_42~CUW~85_30#MGNP'} Metrics: ['ELUC: -9.784935677480362', 'NSGA-II_crowding_distance: 0.16318230114347237', 'NSGA-II_rank: 1', 'change: 0.13226565581166766', 'is_elite: False']\n", + "Id: 86_91 Identity: {'ancestor_count': 80, 'ancestor_ids': ['2_49', '81_95'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_91', 'origin': '2_49~CUW~81_95#MGNP'} Metrics: ['ELUC: -9.989034821556855', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.29592178916593453', 'is_elite: False']\n", + "Id: 86_95 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_95', 'origin': '85_33~CUW~85_93#MGNP'} Metrics: ['ELUC: -10.027289708522416', 'NSGA-II_crowding_distance: 0.20123062527030733', 'NSGA-II_rank: 5', 'change: 0.21007923705202775', 'is_elite: False']\n", + "Id: 86_38 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_20', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_38', 'origin': '85_20~CUW~85_33#MGNP'} Metrics: ['ELUC: -10.264013063217295', 'NSGA-II_crowding_distance: 0.1365846810931638', 'NSGA-II_rank: 5', 'change: 0.21862263515153535', 'is_elite: False']\n", + "Id: 86_73 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_93', '84_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_73', 'origin': '85_93~CUW~84_85#MGNP'} Metrics: ['ELUC: -10.357575837145257', 'NSGA-II_crowding_distance: 0.2137571047344649', 'NSGA-II_rank: 2', 'change: 0.1524661245079543', 'is_elite: False']\n", + "Id: 86_72 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_72', 'origin': '85_33~CUW~85_17#MGNP'} Metrics: ['ELUC: -10.87083932073003', 'NSGA-II_crowding_distance: 0.30190341842990237', 'NSGA-II_rank: 5', 'change: 0.2219940139123602', 'is_elite: False']\n", + "Id: 86_77 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '85_58'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_77', 'origin': '2_49~CUW~85_58#MGNP'} Metrics: ['ELUC: -10.931894018413313', 'NSGA-II_crowding_distance: 0.3454874166588183', 'NSGA-II_rank: 6', 'change: 0.2568297950737321', 'is_elite: False']\n", + "Id: 86_23 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_23', 'origin': '1_1~CUW~85_85#MGNP'} Metrics: ['ELUC: -10.975974267810697', 'NSGA-II_crowding_distance: 0.41064001413294404', 'NSGA-II_rank: 5', 'change: 0.25590713107530305', 'is_elite: False']\n", + "Id: 86_80 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '85_62'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_80', 'origin': '85_17~CUW~85_62#MGNP'} Metrics: ['ELUC: -11.061509816751814', 'NSGA-II_crowding_distance: 0.16363248598779848', 'NSGA-II_rank: 1', 'change: 0.13831727263440277', 'is_elite: False']\n", + "Id: 86_70 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_70', 'origin': '2_49~CUW~85_20#MGNP'} Metrics: ['ELUC: -11.244597691728677', 'NSGA-II_crowding_distance: 0.303166936293562', 'NSGA-II_rank: 6', 'change: 0.2805756326383486', 'is_elite: False']\n", + "Id: 86_74 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_35', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_74', 'origin': '85_35~CUW~85_20#MGNP'} Metrics: ['ELUC: -11.285552063277603', 'NSGA-II_crowding_distance: 0.10181745573105462', 'NSGA-II_rank: 2', 'change: 0.1559512672396169', 'is_elite: False']\n", + "Id: 86_76 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_76', 'origin': '85_33~CUW~85_33#MGNP'} Metrics: ['ELUC: -11.341113852437086', 'NSGA-II_crowding_distance: 1.3803241740391776', 'NSGA-II_rank: 4', 'change: 0.17682546539076904', 'is_elite: False']\n", + "Id: 86_90 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_90', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_90', 'origin': '85_90~CUW~85_20#MGNP'} Metrics: ['ELUC: -11.58123765852407', 'NSGA-II_crowding_distance: 0.42829724751202614', 'NSGA-II_rank: 3', 'change: 0.16311843666348727', 'is_elite: False']\n", + "Id: 85_20 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_85', '84_45'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_20', 'origin': '84_85~CUW~84_45#MGNP'} Metrics: ['ELUC: -11.634620756363477', 'NSGA-II_crowding_distance: 0.07845040540569787', 'NSGA-II_rank: 1', 'change: 0.1497002171757431', 'is_elite: False']\n", + "Id: 86_60 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_60', 'origin': '85_17~CUW~85_20#MGNP'} Metrics: ['ELUC: -11.644265079196721', 'NSGA-II_crowding_distance: 0.20510588133732532', 'NSGA-II_rank: 2', 'change: 0.15689990498465495', 'is_elite: False']\n", + "Id: 86_81 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_20', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_81', 'origin': '85_20~CUW~85_20#MGNP'} Metrics: ['ELUC: -11.65255495068065', 'NSGA-II_crowding_distance: 0.037374053315855194', 'NSGA-II_rank: 1', 'change: 0.15169490722709897', 'is_elite: False']\n", + "Id: 86_32 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_32', 'origin': '1_1~CUW~85_93#MGNP'} Metrics: ['ELUC: -11.822739565133599', 'NSGA-II_crowding_distance: 0.09851530036643011', 'NSGA-II_rank: 1', 'change: 0.1576593676239787', 'is_elite: False']\n", + "Id: 86_79 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_79', 'origin': '85_17~CUW~85_33#MGNP'} Metrics: ['ELUC: -11.868046356237631', 'NSGA-II_crowding_distance: 0.4869427440080889', 'NSGA-II_rank: 4', 'change: 0.24647408023642586', 'is_elite: False']\n", + "Id: 86_52 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_52', 'origin': '2_49~CUW~85_67#MGNP'} Metrics: ['ELUC: -12.004540447983295', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2913319340277207', 'is_elite: False']\n", + "Id: 86_45 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_85', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_45', 'origin': '85_85~CUW~85_33#MGNP'} Metrics: ['ELUC: -12.110541692015175', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27013010300958595', 'is_elite: False']\n", + "Id: 86_67 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_67', 'origin': '85_33~CUW~85_85#MGNP'} Metrics: ['ELUC: -12.201649346492854', 'NSGA-II_crowding_distance: 0.20753193591518287', 'NSGA-II_rank: 4', 'change: 0.25630299575508164', 'is_elite: False']\n", + "Id: 86_99 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_99', 'origin': '85_33~CUW~85_17#MGNP'} Metrics: ['ELUC: -12.316399718212185', 'NSGA-II_crowding_distance: 0.238442379951068', 'NSGA-II_rank: 3', 'change: 0.19466938398250547', 'is_elite: False']\n", + "Id: 86_86 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '85_58'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_86', 'origin': '2_49~CUW~85_58#MGNP'} Metrics: ['ELUC: -12.622813627982067', 'NSGA-II_crowding_distance: 0.18296417695323125', 'NSGA-II_rank: 4', 'change: 0.2750231062281493', 'is_elite: False']\n", + "Id: 86_85 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_20', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_85', 'origin': '85_20~CUW~85_93#MGNP'} Metrics: ['ELUC: -12.733848503275166', 'NSGA-II_crowding_distance: 0.23676865040819373', 'NSGA-II_rank: 2', 'change: 0.18156156466957293', 'is_elite: False']\n", + "Id: 86_47 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '85_30'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_47', 'origin': '1_1~CUW~85_30#MGNP'} Metrics: ['ELUC: -12.755720517157199', 'NSGA-II_crowding_distance: 0.15118219451010356', 'NSGA-II_rank: 1', 'change: 0.1623686177579267', 'is_elite: False']\n", + "Id: 86_98 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '2_49'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_98', 'origin': '85_67~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.006956140592154', 'NSGA-II_crowding_distance: 0.09877977508409479', 'NSGA-II_rank: 4', 'change: 0.27955299244486337', 'is_elite: False']\n", + "Id: 86_75 Identity: {'ancestor_count': 84, 'ancestor_ids': ['81_95', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_75', 'origin': '81_95~CUW~85_93#MGNP'} Metrics: ['ELUC: -13.138077744846019', 'NSGA-II_crowding_distance: 0.11438095141498214', 'NSGA-II_rank: 1', 'change: 0.18044707102112048', 'is_elite: False']\n", + "Id: 85_33 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_15', '82_23'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_33', 'origin': '84_15~CUW~82_23#MGNP'} Metrics: ['ELUC: -13.190349343661108', 'NSGA-II_crowding_distance: 0.10081155765226646', 'NSGA-II_rank: 2', 'change: 0.18829818560162756', 'is_elite: False']\n", + "Id: 86_31 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_33', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_31', 'origin': '85_33~CUW~85_33#MGNP'} Metrics: ['ELUC: -13.196650194543624', 'NSGA-II_crowding_distance: 0.43639234873122323', 'NSGA-II_rank: 3', 'change: 0.19816363236204265', 'is_elite: False']\n", + "Id: 86_30 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_90', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_30', 'origin': '85_90~CUW~85_67#MGNP'} Metrics: ['ELUC: -13.501832969209627', 'NSGA-II_crowding_distance: 0.22963048420969406', 'NSGA-II_rank: 2', 'change: 0.1933306712613446', 'is_elite: False']\n", + "Id: 86_14 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_20', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_14', 'origin': '85_20~CUW~85_67#MGNP'} Metrics: ['ELUC: -13.559445816386956', 'NSGA-II_crowding_distance: 0.08067111674814983', 'NSGA-II_rank: 1', 'change: 0.1828578785986956', 'is_elite: False']\n", + "Id: 86_22 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_35', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_22', 'origin': '85_35~CUW~85_85#MGNP'} Metrics: ['ELUC: -13.563165158539602', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2806385763979798', 'is_elite: False']\n", + "Id: 86_25 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_62'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_25', 'origin': '2_49~CUW~85_62#MGNP'} Metrics: ['ELUC: -13.691957017184997', 'NSGA-II_crowding_distance: 0.5386848448439602', 'NSGA-II_rank: 3', 'change: 0.2748674268992333', 'is_elite: False']\n", + "Id: 85_93 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_21', '82_57'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_93', 'origin': '84_21~CUW~82_57#MGNP'} Metrics: ['ELUC: -13.840404163180791', 'NSGA-II_crowding_distance: 0.1993619084279516', 'NSGA-II_rank: 1', 'change: 0.19259883869877753', 'is_elite: False']\n", + "Id: 86_50 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '85_20'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_50', 'origin': '85_67~CUW~85_20#MGNP'} Metrics: ['ELUC: -14.387105672051003', 'NSGA-II_crowding_distance: 0.5907661616463127', 'NSGA-II_rank: 2', 'change: 0.2231645114857934', 'is_elite: False']\n", + "Id: 86_15 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_30', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_15', 'origin': '85_30~CUW~85_17#MGNP'} Metrics: ['ELUC: -14.710186939615797', 'NSGA-II_crowding_distance: 0.22555143941853395', 'NSGA-II_rank: 1', 'change: 0.22281459768582487', 'is_elite: True']\n", + "Id: 86_97 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_97', 'origin': '2_49~CUW~85_67#MGNP'} Metrics: ['ELUC: -15.309590454711152', 'NSGA-II_crowding_distance: 0.24218341117431058', 'NSGA-II_rank: 3', 'change: 0.2929455014300043', 'is_elite: False']\n", + "Id: 85_67 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_15', '84_15'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_67', 'origin': '84_15~CUW~84_15#MGNP'} Metrics: ['ELUC: -15.438784776818347', 'NSGA-II_crowding_distance: 0.27180743099512256', 'NSGA-II_rank: 1', 'change: 0.2327733500830416', 'is_elite: True']\n", + "Id: 86_57 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_57', 'origin': '2_49~CUW~85_67#MGNP'} Metrics: ['ELUC: -15.868287124842308', 'NSGA-II_crowding_distance: 0.24532301733229028', 'NSGA-II_rank: 1', 'change: 0.28426256066316163', 'is_elite: True']\n", + "Id: 86_18 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_18', 'origin': '2_49~CUW~85_93#MGNP'} Metrics: ['ELUC: -16.0263810244428', 'NSGA-II_crowding_distance: 0.4856214474408187', 'NSGA-II_rank: 2', 'change: 0.29111461123828974', 'is_elite: False']\n", + "Id: 86_56 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_56', 'origin': '2_49~CUW~85_93#MGNP'} Metrics: ['ELUC: -16.503889321151064', 'NSGA-II_crowding_distance: 0.10002215610649423', 'NSGA-II_rank: 1', 'change: 0.28789711892939257', 'is_elite: False']\n", + "Id: 86_65 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '2_49'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_65', 'origin': '85_67~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.52200563087205', 'NSGA-II_crowding_distance: 0.1536673938379014', 'NSGA-II_rank: 3', 'change: 0.29838173249257516', 'is_elite: False']\n", + "Id: 86_66 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_85', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_66', 'origin': '85_85~CUW~85_67#MGNP'} Metrics: ['ELUC: -16.882854176258284', 'NSGA-II_crowding_distance: 0.15256668963522108', 'NSGA-II_rank: 2', 'change: 0.2974122012964194', 'is_elite: False']\n", + "Id: 86_78 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_85', '85_93'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_78', 'origin': '85_85~CUW~85_93#MGNP'} Metrics: ['ELUC: -16.912969289378495', 'NSGA-II_crowding_distance: 0.10684390513469963', 'NSGA-II_rank: 1', 'change: 0.29637836471923074', 'is_elite: False']\n", + "Id: 86_55 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '85_28'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_55', 'origin': '85_17~CUW~85_28#MGNP'} Metrics: ['ELUC: -17.523042126173507', 'NSGA-II_crowding_distance: 0.06106085328234648', 'NSGA-II_rank: 1', 'change: 0.3024816219667981', 'is_elite: False']\n", + "Id: 86_28 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_33'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_28', 'origin': '2_49~CUW~85_33#MGNP'} Metrics: ['ELUC: -17.583012534394445', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30301275210936507', 'is_elite: False']\n", + "Id: 86_49 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_30', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_49', 'origin': '85_30~CUW~85_85#MGNP'} Metrics: ['ELUC: -17.594106452188843', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030126535199546', 'is_elite: False']\n", + "Id: 86_63 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_63', 'origin': '2_49~CUW~85_85#MGNP'} Metrics: ['ELUC: -17.595765262031893', 'NSGA-II_crowding_distance: 0.0060342738533238', 'NSGA-II_rank: 1', 'change: 0.3030103044875815', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 85_85 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_15', '2_49'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_85', 'origin': '84_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 86_11 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_85', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_11', 'origin': '85_85~CUW~85_85#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 86_17 Identity: {'ancestor_count': 84, 'ancestor_ids': ['82_23', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_17', 'origin': '82_23~CUW~85_85#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 86_39 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_85', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_39', 'origin': '85_85~CUW~85_85#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 86_93 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_93', 'origin': '2_49~CUW~85_85#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 86.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 87...:\n", + "PopulationResponse:\n", + " Generation: 87\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/87/20240220-060951\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 87 and asking ESP for generation 88...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 87 data persisted.\n", + "Evaluated candidates:\n", + "Id: 87_78 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_78', 'origin': '86_69~CUW~86_93#MGNP'} Metrics: ['ELUC: 23.45938208362589', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.30187640171354957', 'is_elite: False']\n", + "Id: 87_31 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_17', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_31', 'origin': '85_17~CUW~86_93#MGNP'} Metrics: ['ELUC: 15.247080846292135', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.30218043010911', 'is_elite: False']\n", + "Id: 87_86 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '85_58'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_86', 'origin': '86_93~CUW~85_58#MGNP'} Metrics: ['ELUC: 8.074205133141778', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27077268370498186', 'is_elite: False']\n", + "Id: 87_67 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_67', 'origin': '2_49~CUW~86_29#MGNP'} Metrics: ['ELUC: 7.99432086350743', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.27870457841812785', 'is_elite: False']\n", + "Id: 87_22 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_22', 'origin': '86_93~CUW~86_29#MGNP'} Metrics: ['ELUC: 1.1697901467079452', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2775796503800181', 'is_elite: False']\n", + "Id: 87_47 Identity: {'ancestor_count': 84, 'ancestor_ids': ['86_83', '85_67'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_47', 'origin': '86_83~CUW~85_67#MGNP'} Metrics: ['ELUC: 0.9184725966655913', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1307244296804833', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 87_40 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '86_83'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_40', 'origin': '86_93~CUW~86_83#MGNP'} Metrics: ['ELUC: -0.07069871166349337', 'NSGA-II_crowding_distance: 1.5020713127495837', 'NSGA-II_rank: 7', 'change: 0.24868974618335163', 'is_elite: False']\n", + "Id: 87_29 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_15', '1_1'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_29', 'origin': '86_15~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.3081341536655708', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.06213322905683524', 'is_elite: False']\n", + "Id: 87_72 Identity: {'ancestor_count': 3, 'ancestor_ids': ['85_58', '85_58'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_72', 'origin': '85_58~CUW~85_58#MGNP'} Metrics: ['ELUC: -0.852540732516176', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.05603382871591381', 'is_elite: False']\n", + "Id: 87_48 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '1_1'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_48', 'origin': '85_67~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.2443883131853932', 'NSGA-II_crowding_distance: 0.24617844615045587', 'NSGA-II_rank: 3', 'change: 0.06649531674691915', 'is_elite: False']\n", + "Id: 87_36 Identity: {'ancestor_count': 85, 'ancestor_ids': ['1_1', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_36', 'origin': '1_1~CUW~86_24#MGNP'} Metrics: ['ELUC: -1.3523942720530395', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.12156339842686438', 'is_elite: False']\n", + "Id: 87_50 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '86_69'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_50', 'origin': '86_93~CUW~86_69#MGNP'} Metrics: ['ELUC: -1.423114632843845', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2620418062583847', 'is_elite: False']\n", + "Id: 87_69 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_80', '85_58'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_69', 'origin': '86_80~CUW~85_58#MGNP'} Metrics: ['ELUC: -1.462719667279556', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09693188526142096', 'is_elite: False']\n", + "Id: 87_37 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_83', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_37', 'origin': '86_83~CUW~86_29#MGNP'} Metrics: ['ELUC: -2.190403689000707', 'NSGA-II_crowding_distance: 0.26906977562098044', 'NSGA-II_rank: 2', 'change: 0.05802395212741623', 'is_elite: False']\n", + "Id: 87_55 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_47'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_55', 'origin': '86_69~CUW~86_47#MGNP'} Metrics: ['ELUC: -2.4611237057492654', 'NSGA-II_crowding_distance: 1.004750607113912', 'NSGA-II_rank: 5', 'change: 0.12510039423383845', 'is_elite: False']\n", + "Id: 87_49 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '86_43'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_49', 'origin': '85_67~CUW~86_43#MGNP'} Metrics: ['ELUC: -2.4737640254992757', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08734057148016842', 'is_elite: False']\n", + "Id: 87_79 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '85_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_79', 'origin': '1_1~CUW~85_93#MGNP'} Metrics: ['ELUC: -2.665394958535286', 'NSGA-II_crowding_distance: 0.5587157661933146', 'NSGA-II_rank: 4', 'change: 0.13304658090120405', 'is_elite: False']\n", + "Id: 87_15 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_47', '1_1'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_15', 'origin': '86_47~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.7459357828145783', 'NSGA-II_crowding_distance: 0.2921505325311703', 'NSGA-II_rank: 3', 'change: 0.08658551145265693', 'is_elite: False']\n", + "Id: 87_11 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_11', 'origin': '86_69~CUW~86_24#MGNP'} Metrics: ['ELUC: -3.3927009962334695', 'NSGA-II_crowding_distance: 0.2553930943672204', 'NSGA-II_rank: 2', 'change: 0.08405453493238153', 'is_elite: False']\n", + "Id: 86_83 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '85_84'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_83', 'origin': '1_1~CUW~85_84#MGNP'} Metrics: ['ELUC: -3.511415664087156', 'NSGA-II_crowding_distance: 0.48766922996041673', 'NSGA-II_rank: 1', 'change: 0.04652561459631126', 'is_elite: True']\n", + "Id: 87_39 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_39', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.5439082912640174', 'NSGA-II_crowding_distance: 0.8154530075820079', 'NSGA-II_rank: 7', 'change: 0.2569163561441663', 'is_elite: False']\n", + "Id: 87_76 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_93', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_76', 'origin': '85_93~CUW~86_29#MGNP'} Metrics: ['ELUC: -4.093264052432583', 'NSGA-II_crowding_distance: 0.14398177208004737', 'NSGA-II_rank: 2', 'change: 0.09215646603869349', 'is_elite: False']\n", + "Id: 87_97 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_29', '1_1'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_97', 'origin': '86_29~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.168981743808505', 'NSGA-II_crowding_distance: 0.31339985167231493', 'NSGA-II_rank: 3', 'change: 0.09506991013036747', 'is_elite: False']\n", + "Id: 87_52 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_83', '86_15'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_52', 'origin': '86_83~CUW~86_15#MGNP'} Metrics: ['ELUC: -4.363717619637027', 'NSGA-II_crowding_distance: 1.9197957509893855', 'NSGA-II_rank: 6', 'change: 0.16158550402539526', 'is_elite: False']\n", + "Id: 86_69 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '1_1'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_69', 'origin': '85_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.387758416251311', 'NSGA-II_crowding_distance: 0.1720051641608706', 'NSGA-II_rank: 1', 'change: 0.0759461286963884', 'is_elite: True']\n", + "Id: 87_65 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '85_17'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_65', 'origin': '86_57~CUW~85_17#MGNP'} Metrics: ['ELUC: -4.472521056413902', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2613765998134095', 'is_elite: False']\n", + "Id: 87_20 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_69'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_20', 'origin': '86_69~CUW~86_69#MGNP'} Metrics: ['ELUC: -4.529000657741282', 'NSGA-II_crowding_distance: 0.070249417847078', 'NSGA-II_rank: 1', 'change: 0.08057939140966783', 'is_elite: False']\n", + "Id: 87_44 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '85_17'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_44', 'origin': '86_69~CUW~85_17#MGNP'} Metrics: ['ELUC: -5.19377040646165', 'NSGA-II_crowding_distance: 0.10627690246113336', 'NSGA-II_rank: 2', 'change: 0.09249695646058115', 'is_elite: False']\n", + "Id: 87_83 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '86_83'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_83', 'origin': '85_17~CUW~86_83#MGNP'} Metrics: ['ELUC: -5.195869987539753', 'NSGA-II_crowding_distance: 0.10531136525116085', 'NSGA-II_rank: 1', 'change: 0.08319308703085655', 'is_elite: False']\n", + "Id: 86_29 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_58', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_29', 'origin': '85_58~CUW~85_17#MGNP'} Metrics: ['ELUC: -5.803928675583575', 'NSGA-II_crowding_distance: 0.09927465635826982', 'NSGA-II_rank: 2', 'change: 0.09273439544794741', 'is_elite: False']\n", + "Id: 87_28 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_17', '86_69'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_28', 'origin': '85_17~CUW~86_69#MGNP'} Metrics: ['ELUC: -6.008670937044126', 'NSGA-II_crowding_distance: 0.1000022770577194', 'NSGA-II_rank: 2', 'change: 0.10464904211360204', 'is_elite: False']\n", + "Id: 87_80 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_29', '86_80'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_80', 'origin': '86_29~CUW~86_80#MGNP'} Metrics: ['ELUC: -6.010999234229565', 'NSGA-II_crowding_distance: 0.4343782628633164', 'NSGA-II_rank: 3', 'change: 0.11544066496646885', 'is_elite: False']\n", + "Id: 87_75 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_75', 'origin': '86_69~CUW~86_57#MGNP'} Metrics: ['ELUC: -6.024265724006364', 'NSGA-II_crowding_distance: 0.360105241967857', 'NSGA-II_rank: 7', 'change: 0.25718080142647565', 'is_elite: False']\n", + "Id: 87_81 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_81', 'origin': '86_93~CUW~86_24#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.18253089448095322', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 87_25 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_25', 'origin': '86_69~CUW~86_29#MGNP'} Metrics: ['ELUC: -6.1661604629856965', 'NSGA-II_crowding_distance: 0.16050765593150823', 'NSGA-II_rank: 1', 'change: 0.08421884945578938', 'is_elite: False']\n", + "Id: 87_66 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '85_58'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_66', 'origin': '85_67~CUW~85_58#MGNP'} Metrics: ['ELUC: -6.212701814208913', 'NSGA-II_crowding_distance: 0.5632162584597725', 'NSGA-II_rank: 4', 'change: 0.13622098658548454', 'is_elite: False']\n", + "Id: 87_16 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_17', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_16', 'origin': '85_17~CUW~86_29#MGNP'} Metrics: ['ELUC: -6.565483111940294', 'NSGA-II_crowding_distance: 0.07804015780951536', 'NSGA-II_rank: 2', 'change: 0.10585521163306509', 'is_elite: False']\n", + "Id: 87_23 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_29', '86_37'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_23', 'origin': '86_29~CUW~86_37#MGNP'} Metrics: ['ELUC: -6.749884221571001', 'NSGA-II_crowding_distance: 0.13035620397597783', 'NSGA-II_rank: 1', 'change: 0.10471289409831422', 'is_elite: False']\n", + "Id: 87_54 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_54', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.995075863410545', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2652315825245758', 'is_elite: False']\n", + "Id: 87_84 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_80', '85_58'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_84', 'origin': '86_80~CUW~85_58#MGNP'} Metrics: ['ELUC: -7.0643115615738665', 'NSGA-II_crowding_distance: 0.20765156048655473', 'NSGA-II_rank: 2', 'change: 0.10804697140391284', 'is_elite: False']\n", + "Id: 87_57 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_29', '85_58'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_57', 'origin': '86_29~CUW~85_58#MGNP'} Metrics: ['ELUC: -7.121716568153345', 'NSGA-II_crowding_distance: 0.09479948570762257', 'NSGA-II_rank: 1', 'change: 0.10689815407609873', 'is_elite: False']\n", + "Id: 87_12 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_15', '86_83'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_12', 'origin': '86_15~CUW~86_83#MGNP'} Metrics: ['ELUC: -7.269618370075337', 'NSGA-II_crowding_distance: 0.9977532165195652', 'NSGA-II_rank: 5', 'change: 0.15326506843569304', 'is_elite: False']\n", + "Id: 87_90 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_15', '86_80'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_90', 'origin': '86_15~CUW~86_80#MGNP'} Metrics: ['ELUC: -7.8223044674709605', 'NSGA-II_crowding_distance: 0.16619425538382282', 'NSGA-II_rank: 1', 'change: 0.11479964590911781', 'is_elite: True']\n", + "Id: 87_38 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_83', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_38', 'origin': '86_83~CUW~86_93#MGNP'} Metrics: ['ELUC: -8.279469864382493', 'NSGA-II_crowding_distance: 1.2778376151087663', 'NSGA-II_rank: 6', 'change: 0.24718864560113174', 'is_elite: False']\n", + "Id: 87_93 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '85_58'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_93', 'origin': '85_67~CUW~85_58#MGNP'} Metrics: ['ELUC: -8.478231202898396', 'NSGA-II_crowding_distance: 0.7444908732185969', 'NSGA-II_rank: 5', 'change: 0.17602899944735653', 'is_elite: False']\n", + "Id: 87_61 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '86_75'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_61', 'origin': '86_57~CUW~86_75#MGNP'} Metrics: ['ELUC: -8.629561050579909', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2513544285870604', 'is_elite: False']\n", + "Id: 87_56 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_80', '85_67'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_56', 'origin': '86_80~CUW~85_67#MGNP'} Metrics: ['ELUC: -8.913623142067731', 'NSGA-II_crowding_distance: 0.26900825238246906', 'NSGA-II_rank: 3', 'change: 0.13197902427934716', 'is_elite: False']\n", + "Id: 87_19 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_19', 'origin': '86_57~CUW~86_29#MGNP'} Metrics: ['ELUC: -8.988723547522182', 'NSGA-II_crowding_distance: 0.7218108297337699', 'NSGA-II_rank: 5', 'change: 0.24667143235650496', 'is_elite: False']\n", + "Id: 87_58 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_80', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_58', 'origin': '86_80~CUW~86_29#MGNP'} Metrics: ['ELUC: -9.089643175314922', 'NSGA-II_crowding_distance: 0.20242461402921724', 'NSGA-II_rank: 2', 'change: 0.11911875085746858', 'is_elite: False']\n", + "Id: 87_71 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_83', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_71', 'origin': '86_83~CUW~86_24#MGNP'} Metrics: ['ELUC: -9.130921066403598', 'NSGA-II_crowding_distance: 1.0858291119392225', 'NSGA-II_rank: 4', 'change: 0.13767006418859942', 'is_elite: False']\n", + "Id: 87_42 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_47', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_42', 'origin': '86_47~CUW~86_24#MGNP'} Metrics: ['ELUC: -9.178612984379969', 'NSGA-II_crowding_distance: 0.1632350790614801', 'NSGA-II_rank: 3', 'change: 0.1350717373474559', 'is_elite: False']\n", + "Id: 87_64 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_29', '85_17'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_64', 'origin': '86_29~CUW~85_17#MGNP'} Metrics: ['ELUC: -9.25996855464495', 'NSGA-II_crowding_distance: 0.07773201851976116', 'NSGA-II_rank: 2', 'change: 0.12490593099150103', 'is_elite: False']\n", + "Id: 87_82 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '85_17'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_82', 'origin': '86_69~CUW~85_17#MGNP'} Metrics: ['ELUC: -9.45349640556953', 'NSGA-II_crowding_distance: 0.1646628107159544', 'NSGA-II_rank: 2', 'change: 0.13270025753751916', 'is_elite: False']\n", + "Id: 85_17 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_29', '84_44'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_17', 'origin': '84_29~CUW~84_44#MGNP'} Metrics: ['ELUC: -9.469482805223066', 'NSGA-II_crowding_distance: 0.24746117807920714', 'NSGA-II_rank: 1', 'change: 0.1166444995902892', 'is_elite: True']\n", + "Id: 87_60 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_67', '86_80'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_60', 'origin': '85_67~CUW~86_80#MGNP'} Metrics: ['ELUC: -9.598130911412863', 'NSGA-II_crowding_distance: 0.5536141222041504', 'NSGA-II_rank: 3', 'change: 0.16130745188890022', 'is_elite: False']\n", + "Id: 87_41 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '86_83'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_41', 'origin': '86_57~CUW~86_83#MGNP'} Metrics: ['ELUC: -10.045917874996134', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2685705149579812', 'is_elite: False']\n", + "Id: 87_51 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_47', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_51', 'origin': '86_47~CUW~86_24#MGNP'} Metrics: ['ELUC: -10.116011219869531', 'NSGA-II_crowding_distance: 0.5992232636030566', 'NSGA-II_rank: 2', 'change: 0.1524115512262559', 'is_elite: False']\n", + "Id: 87_21 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '85_67'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_21', 'origin': '86_57~CUW~85_67#MGNP'} Metrics: ['ELUC: -10.611913414954104', 'NSGA-II_crowding_distance: 0.4458839919454777', 'NSGA-II_rank: 3', 'change: 0.2470389312012273', 'is_elite: False']\n", + "Id: 87_70 Identity: {'ancestor_count': 85, 'ancestor_ids': ['1_1', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_70', 'origin': '1_1~CUW~86_57#MGNP'} Metrics: ['ELUC: -10.779024465897635', 'NSGA-II_crowding_distance: 0.07894744526153546', 'NSGA-II_rank: 3', 'change: 0.2511134796381866', 'is_elite: False']\n", + "Id: 87_85 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_37', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_85', 'origin': '86_37~CUW~86_24#MGNP'} Metrics: ['ELUC: -10.901056624672252', 'NSGA-II_crowding_distance: 0.5718637744313279', 'NSGA-II_rank: 1', 'change: 0.13638917374028248', 'is_elite: True']\n", + "Id: 87_45 Identity: {'ancestor_count': 85, 'ancestor_ids': ['1_1', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_45', 'origin': '1_1~CUW~86_93#MGNP'} Metrics: ['ELUC: -11.605073771671302', 'NSGA-II_crowding_distance: 0.1170765106448793', 'NSGA-II_rank: 3', 'change: 0.25190598598486086', 'is_elite: False']\n", + "Id: 87_18 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_18', 'origin': '86_69~CUW~86_57#MGNP'} Metrics: ['ELUC: -11.830522085673337', 'NSGA-II_crowding_distance: 0.8880390631741009', 'NSGA-II_rank: 4', 'change: 0.2585155847497807', 'is_elite: False']\n", + "Id: 87_89 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_67'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_89', 'origin': '2_49~CUW~85_67#MGNP'} Metrics: ['ELUC: -12.330324223926969', 'NSGA-II_crowding_distance: 0.35545512186746275', 'NSGA-II_rank: 4', 'change: 0.2607893324340282', 'is_elite: False']\n", + "Id: 87_68 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_93', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_68', 'origin': '85_93~CUW~86_57#MGNP'} Metrics: ['ELUC: -12.428809063046371', 'NSGA-II_crowding_distance: 0.1606255150801401', 'NSGA-II_rank: 3', 'change: 0.2558409031758005', 'is_elite: False']\n", + "Id: 87_14 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '86_80'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_14', 'origin': '86_57~CUW~86_80#MGNP'} Metrics: ['ELUC: -13.178188722737188', 'NSGA-II_crowding_distance: 0.20604489759847092', 'NSGA-II_rank: 3', 'change: 0.2681066673618584', 'is_elite: False']\n", + "Id: 87_63 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_80', '85_67'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_63', 'origin': '86_80~CUW~85_67#MGNP'} Metrics: ['ELUC: -13.380044955825994', 'NSGA-II_crowding_distance: 0.5953673177728869', 'NSGA-II_rank: 2', 'change: 0.22076421494166593', 'is_elite: False']\n", + "Id: 87_99 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_15', '86_83'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_99', 'origin': '86_15~CUW~86_83#MGNP'} Metrics: ['ELUC: -13.999376343062668', 'NSGA-II_crowding_distance: 0.4862460801536179', 'NSGA-II_rank: 1', 'change: 0.21040221623306005', 'is_elite: True']\n", + "Id: 87_32 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_93', '86_15'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_32', 'origin': '85_93~CUW~86_15#MGNP'} Metrics: ['ELUC: -14.438287621487577', 'NSGA-II_crowding_distance: 0.08202709232720624', 'NSGA-II_rank: 1', 'change: 0.2214462676824548', 'is_elite: False']\n", + "Id: 87_59 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_67'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_59', 'origin': '2_49~CUW~85_67#MGNP'} Metrics: ['ELUC: -14.449164130558874', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2856403542956523', 'is_elite: False']\n", + "Id: 87_87 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_87', 'origin': '86_57~CUW~86_57#MGNP'} Metrics: ['ELUC: -14.57283202615429', 'NSGA-II_crowding_distance: 0.19682497083002676', 'NSGA-II_rank: 3', 'change: 0.27484825320506134', 'is_elite: False']\n", + "Id: 87_92 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_15', '86_80'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_92', 'origin': '86_15~CUW~86_80#MGNP'} Metrics: ['ELUC: -14.608553190978956', 'NSGA-II_crowding_distance: 0.2695531093036511', 'NSGA-II_rank: 2', 'change: 0.2311407768269575', 'is_elite: False']\n", + "Id: 87_96 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_96', 'origin': '85_67~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.612738558065843', 'NSGA-II_crowding_distance: 0.16504525591572666', 'NSGA-II_rank: 2', 'change: 0.2682918923055847', 'is_elite: False']\n", + "Id: 86_15 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_30', '85_17'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_15', 'origin': '85_30~CUW~85_17#MGNP'} Metrics: ['ELUC: -14.710186939615797', 'NSGA-II_crowding_distance: 0.08957277026986221', 'NSGA-II_rank: 1', 'change: 0.22281459768582487', 'is_elite: False']\n", + "Id: 87_98 Identity: {'ancestor_count': 85, 'ancestor_ids': ['1_1', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_98', 'origin': '1_1~CUW~86_57#MGNP'} Metrics: ['ELUC: -14.74079404700712', 'NSGA-II_crowding_distance: 0.14168178763258643', 'NSGA-II_rank: 2', 'change: 0.2694733266634379', 'is_elite: False']\n", + "Id: 87_26 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_26', 'origin': '86_57~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.360185602924515', 'NSGA-II_crowding_distance: 0.10622119598341591', 'NSGA-II_rank: 3', 'change: 0.284379007973316', 'is_elite: False']\n", + "Id: 87_24 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '85_67'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_24', 'origin': '85_67~CUW~85_67#MGNP'} Metrics: ['ELUC: -15.361103118252753', 'NSGA-II_crowding_distance: 0.07481551452959771', 'NSGA-II_rank: 1', 'change: 0.23251232278345202', 'is_elite: False']\n", + "Id: 85_67 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_15', '84_15'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_67', 'origin': '84_15~CUW~84_15#MGNP'} Metrics: ['ELUC: -15.438784776818347', 'NSGA-II_crowding_distance: 0.09658335290828302', 'NSGA-II_rank: 1', 'change: 0.2327733500830416', 'is_elite: False']\n", + "Id: 87_95 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_37', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_95', 'origin': '86_37~CUW~86_57#MGNP'} Metrics: ['ELUC: -15.456731189804813', 'NSGA-II_crowding_distance: 0.18140139641890726', 'NSGA-II_rank: 3', 'change: 0.28776261271575415', 'is_elite: False']\n", + "Id: 86_57 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_67'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_57', 'origin': '2_49~CUW~85_67#MGNP'} Metrics: ['ELUC: -15.868287124842308', 'NSGA-II_crowding_distance: 0.2821336396974018', 'NSGA-II_rank: 2', 'change: 0.28426256066316163', 'is_elite: False']\n", + "Id: 87_88 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_67', '86_15'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_88', 'origin': '85_67~CUW~86_15#MGNP'} Metrics: ['ELUC: -15.97232990733867', 'NSGA-II_crowding_distance: 0.14643902066222178', 'NSGA-II_rank: 1', 'change: 0.2509579358994585', 'is_elite: False']\n", + "Id: 87_74 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_80', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_74', 'origin': '86_80~CUW~86_57#MGNP'} Metrics: ['ELUC: -15.982329860717774', 'NSGA-II_crowding_distance: 0.0957050742559595', 'NSGA-II_rank: 1', 'change: 0.2672433627863366', 'is_elite: False']\n", + "Id: 87_17 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_93', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_17', 'origin': '85_93~CUW~86_93#MGNP'} Metrics: ['ELUC: -16.141153053350685', 'NSGA-II_crowding_distance: 0.17466377976467265', 'NSGA-II_rank: 1', 'change: 0.276649216396141', 'is_elite: True']\n", + "Id: 87_53 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '86_29'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_53', 'origin': '86_93~CUW~86_29#MGNP'} Metrics: ['ELUC: -17.268999342794448', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3008143917853325', 'is_elite: False']\n", + "Id: 87_91 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_91', 'origin': '86_57~CUW~86_93#MGNP'} Metrics: ['ELUC: -17.315538793328507', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30017053380927766', 'is_elite: False']\n", + "Id: 87_27 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_93', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_27', 'origin': '85_93~CUW~86_57#MGNP'} Metrics: ['ELUC: -17.36098814345455', 'NSGA-II_crowding_distance: 0.16059406474950993', 'NSGA-II_rank: 1', 'change: 0.2959628862600437', 'is_elite: False']\n", + "Id: 87_13 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_13', 'origin': '2_49~CUW~86_24#MGNP'} Metrics: ['ELUC: -17.5250782500467', 'NSGA-II_crowding_distance: 0.03308501561043349', 'NSGA-II_rank: 1', 'change: 0.3010812693087656', 'is_elite: False']\n", + "Id: 87_30 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '85_17'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_30', 'origin': '86_93~CUW~85_17#MGNP'} Metrics: ['ELUC: -17.537478755156922', 'NSGA-II_crowding_distance: 0.01035690843405203', 'NSGA-II_rank: 1', 'change: 0.30283961752855293', 'is_elite: False']\n", + "Id: 87_94 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_94', 'origin': '2_49~CUW~86_93#MGNP'} Metrics: ['ELUC: -17.594144533259207', 'NSGA-II_crowding_distance: 0.004013380282985771', 'NSGA-II_rank: 1', 'change: 0.30299946386516274', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 86_93 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_85'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_93', 'origin': '2_49~CUW~85_85#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_33 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_33', 'origin': '2_49~CUW~86_24#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_34 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_47', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_34', 'origin': '86_47~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_35 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_17', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_35', 'origin': '85_17~CUW~86_93#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_43 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_57', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_43', 'origin': '86_57~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_46 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_46', 'origin': '86_93~CUW~86_93#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_62 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_62', 'origin': '2_49~CUW~86_93#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_73 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '86_57'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_73', 'origin': '2_49~CUW~86_57#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_77 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_93', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_77', 'origin': '86_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 87_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 87.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 88...:\n", + "PopulationResponse:\n", + " Generation: 88\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/88/20240220-061707\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 88 and asking ESP for generation 89...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 88 data persisted.\n", + "Evaluated candidates:\n", + "Id: 88_42 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_25', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_42', 'origin': '87_25~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 88_11 Identity: {'ancestor_count': 85, 'ancestor_ids': ['87_100', '86_69'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_11', 'origin': '87_100~CUW~86_69#MGNP'} Metrics: ['ELUC: 23.53230128381753', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037294294395911', 'is_elite: False']\n", + "Id: 88_85 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_88', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_85', 'origin': '87_88~CUW~86_83#MGNP'} Metrics: ['ELUC: 6.04383016083775', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.1192437446490459', 'is_elite: False']\n", + "Id: 88_99 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_99', 'origin': '86_69~CUW~2_49#MGNP'} Metrics: ['ELUC: 5.535789685642507', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.25521166777638504', 'is_elite: False']\n", + "Id: 88_26 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '87_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_26', 'origin': '87_85~CUW~87_17#MGNP'} Metrics: ['ELUC: 4.801780156007561', 'NSGA-II_crowding_distance: 1.414581223653629', 'NSGA-II_rank: 9', 'change: 0.16479084762918952', 'is_elite: False']\n", + "Id: 88_70 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '87_100'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_70', 'origin': '1_1~CUW~87_100#MGNP'} Metrics: ['ELUC: 4.6312525693978905', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.25431341882672404', 'is_elite: False']\n", + "Id: 88_73 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '85_67'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_73', 'origin': '86_69~CUW~85_67#MGNP'} Metrics: ['ELUC: 4.47958175541989', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.11729835532666866', 'is_elite: False']\n", + "Id: 88_86 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '87_100'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_86', 'origin': '86_69~CUW~87_100#MGNP'} Metrics: ['ELUC: 3.6782691480353935', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.2634497748370119', 'is_elite: False']\n", + "Id: 88_40 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_100', '87_57'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_40', 'origin': '87_100~CUW~87_57#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 88_15 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '86_69'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_15', 'origin': '87_85~CUW~86_69#MGNP'} Metrics: ['ELUC: 1.5298905833467304', 'NSGA-II_crowding_distance: 1.3572496554641402', 'NSGA-II_rank: 8', 'change: 0.11840994409780571', 'is_elite: False']\n", + "Id: 88_72 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_90', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_72', 'origin': '87_90~CUW~2_49#MGNP'} Metrics: ['ELUC: 0.33826719497338614', 'NSGA-II_crowding_distance: 1.2406414432494062', 'NSGA-II_rank: 9', 'change: 0.24010949815192353', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 88_22 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '1_1'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_22', 'origin': '87_85~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.1230457441190163', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07333604120916848', 'is_elite: False']\n", + "Id: 88_32 Identity: {'ancestor_count': 86, 'ancestor_ids': ['1_1', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_32', 'origin': '1_1~CUW~87_85#MGNP'} Metrics: ['ELUC: -0.5053319514077677', 'NSGA-II_crowding_distance: 0.5610403139697167', 'NSGA-II_rank: 5', 'change: 0.09171668234795673', 'is_elite: False']\n", + "Id: 88_19 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '87_23'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_19', 'origin': '2_49~CUW~87_23#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 1.1061939656836952', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 88_97 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '87_25'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_97', 'origin': '2_49~CUW~87_25#MGNP'} Metrics: ['ELUC: -0.6118794530001079', 'NSGA-II_crowding_distance: 0.585418776346371', 'NSGA-II_rank: 9', 'change: 0.2577010985657357', 'is_elite: False']\n", + "Id: 88_64 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_64', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6628422430987615', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.33360101879466975', 'is_elite: False']\n", + "Id: 88_34 Identity: {'ancestor_count': 86, 'ancestor_ids': ['86_69', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_34', 'origin': '86_69~CUW~87_27#MGNP'} Metrics: ['ELUC: -1.1218223140334276', 'NSGA-II_crowding_distance: 0.43897498064892937', 'NSGA-II_rank: 8', 'change: 0.25080098405829193', 'is_elite: False']\n", + "Id: 88_88 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_88', 'origin': '1_1~CUW~86_83#MGNP'} Metrics: ['ELUC: -1.3221503501141663', 'NSGA-II_crowding_distance: 0.33922543361972235', 'NSGA-II_rank: 1', 'change: 0.04462980410980077', 'is_elite: True']\n", + "Id: 88_18 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_100', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_18', 'origin': '87_100~CUW~87_85#MGNP'} Metrics: ['ELUC: -1.8918211630740804', 'NSGA-II_crowding_distance: 0.5001413959302361', 'NSGA-II_rank: 8', 'change: 0.2849045697378476', 'is_elite: False']\n", + "Id: 88_81 Identity: {'ancestor_count': 86, 'ancestor_ids': ['86_83', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_81', 'origin': '86_83~CUW~87_85#MGNP'} Metrics: ['ELUC: -1.9196266401361868', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.06450500148438024', 'is_elite: False']\n", + "Id: 88_91 Identity: {'ancestor_count': 85, 'ancestor_ids': ['1_1', '86_69'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_91', 'origin': '1_1~CUW~86_69#MGNP'} Metrics: ['ELUC: -2.36848352530388', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.058073746096543505', 'is_elite: False']\n", + "Id: 88_53 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_23', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_53', 'origin': '87_23~CUW~86_83#MGNP'} Metrics: ['ELUC: -2.5330755979745607', 'NSGA-II_crowding_distance: 0.21011009891793903', 'NSGA-II_rank: 3', 'change: 0.07019911263575533', 'is_elite: False']\n", + "Id: 88_49 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_90', '85_67'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_49', 'origin': '87_90~CUW~85_67#MGNP'} Metrics: ['ELUC: -2.732174712042025', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.11420511332926976', 'is_elite: False']\n", + "Id: 88_46 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_23', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_46', 'origin': '87_23~CUW~86_83#MGNP'} Metrics: ['ELUC: -2.735905120611432', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.0529018000345645', 'is_elite: False']\n", + "Id: 88_75 Identity: {'ancestor_count': 86, 'ancestor_ids': ['85_17', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_75', 'origin': '85_17~CUW~87_27#MGNP'} Metrics: ['ELUC: -3.09140836336164', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 7', 'change: 0.21480971747918295', 'is_elite: False']\n", + "Id: 88_37 Identity: {'ancestor_count': 85, 'ancestor_ids': ['87_83', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_37', 'origin': '87_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.1364530175814784', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2919523491332904', 'is_elite: False']\n", + "Id: 88_69 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '85_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_69', 'origin': '1_1~CUW~85_17#MGNP'} Metrics: ['ELUC: -3.234902311970669', 'NSGA-II_crowding_distance: 0.5320990091047894', 'NSGA-II_rank: 5', 'change: 0.09794893744201205', 'is_elite: False']\n", + "Id: 86_83 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '85_84'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_83', 'origin': '1_1~CUW~85_84#MGNP'} Metrics: ['ELUC: -3.511415664087156', 'NSGA-II_crowding_distance: 0.26133218176115325', 'NSGA-II_rank: 1', 'change: 0.04652561459631126', 'is_elite: True']\n", + "Id: 88_43 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_43', 'origin': '85_67~CUW~86_83#MGNP'} Metrics: ['ELUC: -3.543740526217576', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11297607227528737', 'is_elite: False']\n", + "Id: 88_50 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_83', '87_90'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_50', 'origin': '87_83~CUW~87_90#MGNP'} Metrics: ['ELUC: -3.6575407500299315', 'NSGA-II_crowding_distance: 0.7024566357233077', 'NSGA-II_rank: 5', 'change: 0.10836389511245026', 'is_elite: False']\n", + "Id: 88_83 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_17', '86_69'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_83', 'origin': '85_17~CUW~86_69#MGNP'} Metrics: ['ELUC: -3.9376093614702534', 'NSGA-II_crowding_distance: 0.7960444153944598', 'NSGA-II_rank: 4', 'change: 0.08328599821903243', 'is_elite: False']\n", + "Id: 88_20 Identity: {'ancestor_count': 86, 'ancestor_ids': ['86_83', '87_23'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_20', 'origin': '86_83~CUW~87_23#MGNP'} Metrics: ['ELUC: -4.068983483137322', 'NSGA-II_crowding_distance: 0.2032835567066541', 'NSGA-II_rank: 2', 'change: 0.07348563693522225', 'is_elite: False']\n", + "Id: 88_94 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_69'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_94', 'origin': '86_69~CUW~86_69#MGNP'} Metrics: ['ELUC: -4.235468751757977', 'NSGA-II_crowding_distance: 0.3399488427858875', 'NSGA-II_rank: 3', 'change: 0.07947546865466312', 'is_elite: False']\n", + "Id: 86_69 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '1_1'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_69', 'origin': '85_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.387758416251311', 'NSGA-II_crowding_distance: 0.15066970748985042', 'NSGA-II_rank: 2', 'change: 0.0759461286963884', 'is_elite: False']\n", + "Id: 88_47 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_100', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_47', 'origin': '87_100~CUW~87_27#MGNP'} Metrics: ['ELUC: -4.39350607460011', 'NSGA-II_crowding_distance: 1.0343401478336627', 'NSGA-II_rank: 5', 'change: 0.2200215688306051', 'is_elite: False']\n", + "Id: 88_57 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '86_69'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_57', 'origin': '86_69~CUW~86_69#MGNP'} Metrics: ['ELUC: -4.4910400849858645', 'NSGA-II_crowding_distance: 0.1880178081209007', 'NSGA-II_rank: 1', 'change: 0.06882846784507161', 'is_elite: False']\n", + "Id: 88_65 Identity: {'ancestor_count': 86, 'ancestor_ids': ['1_1', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_65', 'origin': '1_1~CUW~87_85#MGNP'} Metrics: ['ELUC: -4.649741221609017', 'NSGA-II_crowding_distance: 0.2766209079001199', 'NSGA-II_rank: 2', 'change: 0.1013967909843089', 'is_elite: False']\n", + "Id: 88_80 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_83', '86_69'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_80', 'origin': '86_83~CUW~86_69#MGNP'} Metrics: ['ELUC: -4.706552386318063', 'NSGA-II_crowding_distance: 0.1746477034913792', 'NSGA-II_rank: 1', 'change: 0.08234409996584624', 'is_elite: False']\n", + "Id: 88_54 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_100', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_54', 'origin': '87_100~CUW~87_85#MGNP'} Metrics: ['ELUC: -5.384907050007284', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.2584130118481585', 'is_elite: False']\n", + "Id: 88_24 Identity: {'ancestor_count': 86, 'ancestor_ids': ['86_83', '87_90'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_24', 'origin': '86_83~CUW~87_90#MGNP'} Metrics: ['ELUC: -5.394494789008663', 'NSGA-II_crowding_distance: 0.40577334436690415', 'NSGA-II_rank: 3', 'change: 0.10739361905822427', 'is_elite: False']\n", + "Id: 88_63 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_23', '87_88'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_63', 'origin': '87_23~CUW~87_88#MGNP'} Metrics: ['ELUC: -5.893475177564891', 'NSGA-II_crowding_distance: 0.982080756440506', 'NSGA-II_rank: 4', 'change: 0.1332465095562126', 'is_elite: False']\n", + "Id: 88_78 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_78', 'origin': '87_85~CUW~87_27#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 88_38 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_23', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_38', 'origin': '87_23~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.048674222320232', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.26271498044521496', 'is_elite: False']\n", + "Id: 88_17 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_25', '87_25'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_17', 'origin': '87_25~CUW~87_25#MGNP'} Metrics: ['ELUC: -6.394497711811051', 'NSGA-II_crowding_distance: 0.26402500695751985', 'NSGA-II_rank: 1', 'change: 0.08863718792163766', 'is_elite: True']\n", + "Id: 88_98 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_17', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_98', 'origin': '87_17~CUW~87_85#MGNP'} Metrics: ['ELUC: -6.445461240600419', 'NSGA-II_crowding_distance: 0.504152603629018', 'NSGA-II_rank: 5', 'change: 0.25204649082380937', 'is_elite: False']\n", + "Id: 88_84 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_90', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_84', 'origin': '87_90~CUW~87_27#MGNP'} Metrics: ['ELUC: -6.621073454247764', 'NSGA-II_crowding_distance: 0.297506309247245', 'NSGA-II_rank: 5', 'change: 0.2610976559812406', 'is_elite: False']\n", + "Id: 88_30 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_90', '87_23'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_30', 'origin': '87_90~CUW~87_23#MGNP'} Metrics: ['ELUC: -6.707016962971262', 'NSGA-II_crowding_distance: 0.26706154122145886', 'NSGA-II_rank: 2', 'change: 0.10610107073994503', 'is_elite: False']\n", + "Id: 88_66 Identity: {'ancestor_count': 84, 'ancestor_ids': ['87_100', '85_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_66', 'origin': '87_100~CUW~85_17#MGNP'} Metrics: ['ELUC: -6.98571076042143', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.302095172538511', 'is_elite: False']\n", + "Id: 88_77 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_74', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_77', 'origin': '87_74~CUW~87_85#MGNP'} Metrics: ['ELUC: -7.5065997529023765', 'NSGA-II_crowding_distance: 0.8800146221833469', 'NSGA-II_rank: 4', 'change: 0.20363211971758274', 'is_elite: False']\n", + "Id: 87_90 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_15', '86_80'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_90', 'origin': '86_15~CUW~86_80#MGNP'} Metrics: ['ELUC: -7.8223044674709605', 'NSGA-II_crowding_distance: 0.18458031684780832', 'NSGA-II_rank: 2', 'change: 0.11479964590911781', 'is_elite: False']\n", + "Id: 88_96 Identity: {'ancestor_count': 86, 'ancestor_ids': ['85_17', '87_99'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_96', 'origin': '85_17~CUW~87_99#MGNP'} Metrics: ['ELUC: -7.835554441287421', 'NSGA-II_crowding_distance: 0.4052435570570424', 'NSGA-II_rank: 3', 'change: 0.12089623948935059', 'is_elite: False']\n", + "Id: 88_16 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_25', '85_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_16', 'origin': '87_25~CUW~85_17#MGNP'} Metrics: ['ELUC: -7.976135032312253', 'NSGA-II_crowding_distance: 0.26875585022806847', 'NSGA-II_rank: 1', 'change: 0.1056374529963489', 'is_elite: True']\n", + "Id: 88_13 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '87_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_13', 'origin': '87_85~CUW~87_83#MGNP'} Metrics: ['ELUC: -8.764586185180697', 'NSGA-II_crowding_distance: 0.2317417637997753', 'NSGA-II_rank: 2', 'change: 0.11763917466764733', 'is_elite: False']\n", + "Id: 88_23 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_27', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_23', 'origin': '87_27~CUW~87_85#MGNP'} Metrics: ['ELUC: -9.360994435737954', 'NSGA-II_crowding_distance: 0.6871830018811704', 'NSGA-II_rank: 4', 'change: 0.23390433253163742', 'is_elite: False']\n", + "Id: 88_55 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '87_99'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_55', 'origin': '87_85~CUW~87_99#MGNP'} Metrics: ['ELUC: -9.36407044840332', 'NSGA-II_crowding_distance: 0.33102301625170427', 'NSGA-II_rank: 3', 'change: 0.14272867191372915', 'is_elite: False']\n", + "Id: 85_17 Identity: {'ancestor_count': 83, 'ancestor_ids': ['84_29', '84_44'], 'birth_generation': 85, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '85_17', 'origin': '84_29~CUW~84_44#MGNP'} Metrics: ['ELUC: -9.469482805223066', 'NSGA-II_crowding_distance: 0.1789347257060712', 'NSGA-II_rank: 1', 'change: 0.1166444995902892', 'is_elite: False']\n", + "Id: 88_29 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '85_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_29', 'origin': '87_85~CUW~85_17#MGNP'} Metrics: ['ELUC: -9.840843954195439', 'NSGA-II_crowding_distance: 0.10230952202662502', 'NSGA-II_rank: 1', 'change: 0.1273829024267705', 'is_elite: False']\n", + "Id: 88_56 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_90', '87_99'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_56', 'origin': '87_90~CUW~87_99#MGNP'} Metrics: ['ELUC: -10.135944637975484', 'NSGA-II_crowding_distance: 0.20509542521755791', 'NSGA-II_rank: 2', 'change: 0.1338240347332522', 'is_elite: False']\n", + "Id: 88_90 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_100', '87_25'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_90', 'origin': '87_100~CUW~87_25#MGNP'} Metrics: ['ELUC: -10.15186578929883', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28389751117105805', 'is_elite: False']\n", + "Id: 88_74 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_17', '85_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_74', 'origin': '85_17~CUW~85_17#MGNP'} Metrics: ['ELUC: -10.308469112435727', 'NSGA-II_crowding_distance: 0.09048399312161863', 'NSGA-II_rank: 1', 'change: 0.1329335247491692', 'is_elite: False']\n", + "Id: 88_60 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_60', 'origin': '87_85~CUW~87_85#MGNP'} Metrics: ['ELUC: -10.583919093366225', 'NSGA-II_crowding_distance: 0.07040346381021301', 'NSGA-II_rank: 2', 'change: 0.13831800486178325', 'is_elite: False']\n", + "Id: 88_87 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_57', '87_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_87', 'origin': '87_57~CUW~87_83#MGNP'} Metrics: ['ELUC: -10.599088039876325', 'NSGA-II_crowding_distance: 0.5521318650234749', 'NSGA-II_rank: 3', 'change: 0.15748094576690946', 'is_elite: False']\n", + "Id: 88_68 Identity: {'ancestor_count': 86, 'ancestor_ids': ['86_83', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_68', 'origin': '86_83~CUW~87_85#MGNP'} Metrics: ['ELUC: -10.657604661851018', 'NSGA-II_crowding_distance: 0.11523224526056182', 'NSGA-II_rank: 2', 'change: 0.1426537192159619', 'is_elite: False']\n", + "Id: 87_85 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_37', '86_24'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_85', 'origin': '86_37~CUW~86_24#MGNP'} Metrics: ['ELUC: -10.901056624672252', 'NSGA-II_crowding_distance: 0.1095268983808227', 'NSGA-II_rank: 1', 'change: 0.13638917374028248', 'is_elite: False']\n", + "Id: 88_44 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_90', '87_99'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_44', 'origin': '87_90~CUW~87_99#MGNP'} Metrics: ['ELUC: -10.98374024303171', 'NSGA-II_crowding_distance: 0.1807795492624432', 'NSGA-II_rank: 2', 'change: 0.1604107504425273', 'is_elite: False']\n", + "Id: 88_89 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_90', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_89', 'origin': '87_90~CUW~87_27#MGNP'} Metrics: ['ELUC: -11.200617386283033', 'NSGA-II_crowding_distance: 0.5629164035844847', 'NSGA-II_rank: 3', 'change: 0.24844730110426524', 'is_elite: False']\n", + "Id: 88_93 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_99', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_93', 'origin': '87_99~CUW~87_85#MGNP'} Metrics: ['ELUC: -11.692086514279534', 'NSGA-II_crowding_distance: 0.30720255686191345', 'NSGA-II_rank: 2', 'change: 0.1704597326653675', 'is_elite: False']\n", + "Id: 88_27 Identity: {'ancestor_count': 86, 'ancestor_ids': ['85_17', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_27', 'origin': '85_17~CUW~87_85#MGNP'} Metrics: ['ELUC: -11.704302117970624', 'NSGA-II_crowding_distance: 0.17670317075048028', 'NSGA-II_rank: 1', 'change: 0.14192619409561086', 'is_elite: False']\n", + "Id: 88_79 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '86_15'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_79', 'origin': '87_85~CUW~86_15#MGNP'} Metrics: ['ELUC: -12.48983153313787', 'NSGA-II_crowding_distance: 0.2666051584029244', 'NSGA-II_rank: 1', 'change: 0.16215146214524234', 'is_elite: True']\n", + "Id: 88_25 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_17', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_25', 'origin': '87_17~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.803918909413882', 'NSGA-II_crowding_distance: 0.2295809302579197', 'NSGA-II_rank: 3', 'change: 0.2599063304703815', 'is_elite: False']\n", + "Id: 88_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_82', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.08753829034826', 'NSGA-II_crowding_distance: 0.25358614678479835', 'NSGA-II_rank: 3', 'change: 0.27429979176251584', 'is_elite: False']\n", + "Id: 88_62 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_99', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_62', 'origin': '87_99~CUW~86_83#MGNP'} Metrics: ['ELUC: -13.458235742010094', 'NSGA-II_crowding_distance: 0.3885648255815319', 'NSGA-II_rank: 2', 'change: 0.19560209622794017', 'is_elite: False']\n", + "Id: 88_12 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_88', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_12', 'origin': '87_88~CUW~87_85#MGNP'} Metrics: ['ELUC: -13.637293585397972', 'NSGA-II_crowding_distance: 0.24756605854656927', 'NSGA-II_rank: 1', 'change: 0.1886717710118233', 'is_elite: False']\n", + "Id: 87_99 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_15', '86_83'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_99', 'origin': '86_15~CUW~86_83#MGNP'} Metrics: ['ELUC: -13.999376343062668', 'NSGA-II_crowding_distance: 0.12379039423699274', 'NSGA-II_rank: 1', 'change: 0.21040221623306005', 'is_elite: False']\n", + "Id: 88_35 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_99', '87_99'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_35', 'origin': '87_99~CUW~87_99#MGNP'} Metrics: ['ELUC: -14.08497602095397', 'NSGA-II_crowding_distance: 0.08698671096639779', 'NSGA-II_rank: 1', 'change: 0.21801075701284867', 'is_elite: False']\n", + "Id: 88_52 Identity: {'ancestor_count': 86, 'ancestor_ids': ['86_15', '87_99'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_52', 'origin': '86_15~CUW~87_99#MGNP'} Metrics: ['ELUC: -14.426284386696873', 'NSGA-II_crowding_distance: 0.4553755692544335', 'NSGA-II_rank: 2', 'change: 0.22163050948764618', 'is_elite: False']\n", + "Id: 88_67 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_67', 'origin': '2_49~CUW~87_27#MGNP'} Metrics: ['ELUC: -14.919687539559241', 'NSGA-II_crowding_distance: 0.41279684256603655', 'NSGA-II_rank: 3', 'change: 0.28795343458269046', 'is_elite: False']\n", + "Id: 88_58 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_99', '85_67'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_58', 'origin': '87_99~CUW~85_67#MGNP'} Metrics: ['ELUC: -14.96086152924623', 'NSGA-II_crowding_distance: 0.1493524397518487', 'NSGA-II_rank: 1', 'change: 0.22004041232367247', 'is_elite: False']\n", + "Id: 88_51 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '85_67'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_51', 'origin': '85_67~CUW~85_67#MGNP'} Metrics: ['ELUC: -15.518710623569989', 'NSGA-II_crowding_distance: 0.26416562790758824', 'NSGA-II_rank: 1', 'change: 0.23824327858471578', 'is_elite: True']\n", + "Id: 88_61 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_27', '86_69'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_61', 'origin': '87_27~CUW~86_69#MGNP'} Metrics: ['ELUC: -15.601313355558855', 'NSGA-II_crowding_distance: 0.33536058447286127', 'NSGA-II_rank: 2', 'change: 0.27343203461463883', 'is_elite: False']\n", + "Id: 87_17 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_93', '86_93'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_17', 'origin': '85_93~CUW~86_93#MGNP'} Metrics: ['ELUC: -16.141153053350685', 'NSGA-II_crowding_distance: 0.17906237304160638', 'NSGA-II_rank: 2', 'change: 0.276649216396141', 'is_elite: False']\n", + "Id: 88_39 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_27', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_39', 'origin': '87_27~CUW~87_85#MGNP'} Metrics: ['ELUC: -16.538662252728123', 'NSGA-II_crowding_distance: 0.25728105842526405', 'NSGA-II_rank: 1', 'change: 0.27208578408966216', 'is_elite: True']\n", + "Id: 88_33 Identity: {'ancestor_count': 3, 'ancestor_ids': ['87_100', '87_100'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_33', 'origin': '87_100~CUW~87_100#MGNP'} Metrics: ['ELUC: -16.79610201628125', 'NSGA-II_crowding_distance: 0.20342204564223723', 'NSGA-II_rank: 2', 'change: 0.2981105879695043', 'is_elite: False']\n", + "Id: 88_95 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '87_99'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_95', 'origin': '2_49~CUW~87_99#MGNP'} Metrics: ['ELUC: -16.84437639050258', 'NSGA-II_crowding_distance: 0.10422396692081702', 'NSGA-II_rank: 1', 'change: 0.29251325615665535', 'is_elite: False']\n", + "Id: 88_76 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_99', '87_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_76', 'origin': '87_99~CUW~87_17#MGNP'} Metrics: ['ELUC: -17.03435637301038', 'NSGA-II_crowding_distance: 0.07214051591005836', 'NSGA-II_rank: 1', 'change: 0.29477181114418416', 'is_elite: False']\n", + "Id: 88_45 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_100', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_45', 'origin': '87_100~CUW~87_27#MGNP'} Metrics: ['ELUC: -17.520337658068556', 'NSGA-II_crowding_distance: 0.05918745867223563', 'NSGA-II_rank: 1', 'change: 0.3025671073874541', 'is_elite: False']\n", + "Id: 88_92 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_92', 'origin': '2_49~CUW~86_83#MGNP'} Metrics: ['ELUC: -17.57338690317179', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3031641904704404', 'is_elite: False']\n", + "Id: 88_100 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '87_25'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_100', 'origin': '2_49~CUW~87_25#MGNP'} Metrics: ['ELUC: -17.590228721177624', 'NSGA-II_crowding_distance: 0.005817999580643687', 'NSGA-II_rank: 1', 'change: 0.30299870473196083', 'is_elite: False']\n", + "Id: 88_36 Identity: {'ancestor_count': 3, 'ancestor_ids': ['87_100', '87_100'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_36', 'origin': '87_100~CUW~87_100#MGNP'} Metrics: ['ELUC: -17.596185419203294', 'NSGA-II_crowding_distance: 0.000480038710078993', 'NSGA-II_rank: 1', 'change: 0.30301590892425123', 'is_elite: False']\n", + "Id: 88_48 Identity: {'ancestor_count': 85, 'ancestor_ids': ['86_69', '87_100'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_48', 'origin': '86_69~CUW~87_100#MGNP'} Metrics: ['ELUC: -17.59738799084857', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 87_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 87, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '87_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 88_14 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '87_99'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_14', 'origin': '2_49~CUW~87_99#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 88_21 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_21', 'origin': '2_49~CUW~87_85#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 88_28 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_28', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 88_31 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_27', '87_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_31', 'origin': '87_27~CUW~87_17#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 88_41 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_99', '87_27'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_41', 'origin': '87_99~CUW~87_27#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 88_59 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_27', '87_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_59', 'origin': '87_27~CUW~87_17#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 88_71 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_88', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_71', 'origin': '87_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 88.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 89...:\n", + "PopulationResponse:\n", + " Generation: 89\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/89/20240220-062423\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 89 and asking ESP for generation 90...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 89 data persisted.\n", + "Evaluated candidates:\n", + "Id: 89_64 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_17', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_64', 'origin': '88_17~CUW~2_49#MGNP'} Metrics: ['ELUC: 10.213489395372457', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.24561630404614132', 'is_elite: False']\n", + "Id: 89_63 Identity: {'ancestor_count': 86, 'ancestor_ids': ['88_57', '88_51'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_63', 'origin': '88_57~CUW~88_51#MGNP'} Metrics: ['ELUC: 6.614675792012286', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.14201834696013535', 'is_elite: False']\n", + "Id: 89_98 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '1_1'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_98', 'origin': '87_85~CUW~1_1#MGNP'} Metrics: ['ELUC: 5.752780738711955', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.13246054515716174', 'is_elite: False']\n", + "Id: 89_38 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_38', 'origin': '88_71~CUW~2_49#MGNP'} Metrics: ['ELUC: 4.724053627328397', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.23996346432380153', 'is_elite: False']\n", + "Id: 89_84 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_17', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_84', 'origin': '88_17~CUW~88_39#MGNP'} Metrics: ['ELUC: 3.4312283260669605', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.20139616275696448', 'is_elite: False']\n", + "Id: 89_87 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_87', 'origin': '1_1~CUW~88_39#MGNP'} Metrics: ['ELUC: 2.678440419418834', 'NSGA-II_crowding_distance: 1.3864434469266969', 'NSGA-II_rank: 10', 'change: 0.1974844592617469', 'is_elite: False']\n", + "Id: 89_80 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_79'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_80', 'origin': '1_1~CUW~88_79#MGNP'} Metrics: ['ELUC: 2.6047398419524863', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.12987861812187082', 'is_elite: False']\n", + "Id: 89_36 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_36', 'origin': '88_16~CUW~88_71#MGNP'} Metrics: ['ELUC: 2.241019886381866', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.32845916617412557', 'is_elite: False']\n", + "Id: 89_50 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_57', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_50', 'origin': '88_57~CUW~88_71#MGNP'} Metrics: ['ELUC: 2.1560003740617204', 'NSGA-II_crowding_distance: 1.0549177458616115', 'NSGA-II_rank: 10', 'change: 0.2545521306456017', 'is_elite: False']\n", + "Id: 89_83 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '88_57'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_83', 'origin': '88_79~CUW~88_57#MGNP'} Metrics: ['ELUC: 1.9807719419928476', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.13241685613247658', 'is_elite: False']\n", + "Id: 89_19 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_17'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_19', 'origin': '1_1~CUW~88_17#MGNP'} Metrics: ['ELUC: 0.7092658827025624', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.07252271959875253', 'is_elite: False']\n", + "Id: 89_60 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_60', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.22256735582311496', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03082767450454034', 'is_elite: False']\n", + "Id: 89_65 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_65', 'origin': '88_16~CUW~88_71#MGNP'} Metrics: ['ELUC: 0.14641949181530461', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.296366068069043', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 89_49 Identity: {'ancestor_count': 85, 'ancestor_ids': ['1_1', '88_51'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_49', 'origin': '1_1~CUW~88_51#MGNP'} Metrics: ['ELUC: -0.42978218325900674', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.06711365205501225', 'is_elite: False']\n", + "Id: 89_47 Identity: {'ancestor_count': 85, 'ancestor_ids': ['1_1', '88_88'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_47', 'origin': '1_1~CUW~88_88#MGNP'} Metrics: ['ELUC: -1.028522974281389', 'NSGA-II_crowding_distance: 0.1809533804489657', 'NSGA-II_rank: 2', 'change: 0.045968084002716764', 'is_elite: False']\n", + "Id: 89_77 Identity: {'ancestor_count': 84, 'ancestor_ids': ['86_83', '1_1'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_77', 'origin': '86_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.0550335760932197', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.05550929289365036', 'is_elite: False']\n", + "Id: 89_75 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '88_88'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_75', 'origin': '88_88~CUW~88_88#MGNP'} Metrics: ['ELUC: -1.2170808455765243', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04990664217568205', 'is_elite: False']\n", + "Id: 88_88 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_88', 'origin': '1_1~CUW~86_83#MGNP'} Metrics: ['ELUC: -1.3221503501141663', 'NSGA-II_crowding_distance: 0.33922543361972235', 'NSGA-II_rank: 1', 'change: 0.04462980410980077', 'is_elite: True']\n", + "Id: 89_70 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '86_83'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_70', 'origin': '88_88~CUW~86_83#MGNP'} Metrics: ['ELUC: -1.3772421251077742', 'NSGA-II_crowding_distance: 0.137845978129903', 'NSGA-II_rank: 5', 'change: 0.05783484850645649', 'is_elite: False']\n", + "Id: 89_12 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '86_83'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_12', 'origin': '1_1~CUW~86_83#MGNP'} Metrics: ['ELUC: -1.6015108253246604', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.06662016997494254', 'is_elite: False']\n", + "Id: 89_89 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '88_88'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_89', 'origin': '88_88~CUW~88_88#MGNP'} Metrics: ['ELUC: -1.7873207857761602', 'NSGA-II_crowding_distance: 0.1176512756100457', 'NSGA-II_rank: 2', 'change: 0.04936770440846344', 'is_elite: False']\n", + "Id: 89_99 Identity: {'ancestor_count': 87, 'ancestor_ids': ['86_83', '88_79'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_99', 'origin': '86_83~CUW~88_79#MGNP'} Metrics: ['ELUC: -2.0872660442234423', 'NSGA-II_crowding_distance: 1.663020837519718', 'NSGA-II_rank: 6', 'change: 0.11543700472140468', 'is_elite: False']\n", + "Id: 89_18 Identity: {'ancestor_count': 87, 'ancestor_ids': ['86_83', '88_17'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_18', 'origin': '86_83~CUW~88_17#MGNP'} Metrics: ['ELUC: -2.1041414642058274', 'NSGA-II_crowding_distance: 1.3293027381514815', 'NSGA-II_rank: 5', 'change: 0.06396160950145491', 'is_elite: False']\n", + "Id: 89_74 Identity: {'ancestor_count': 86, 'ancestor_ids': ['88_88', '88_80'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_74', 'origin': '88_88~CUW~88_80#MGNP'} Metrics: ['ELUC: -2.12678775578665', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05506085640766982', 'is_elite: False']\n", + "Id: 89_14 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_27', '86_83'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_14', 'origin': '88_27~CUW~86_83#MGNP'} Metrics: ['ELUC: -2.339503348456234', 'NSGA-II_crowding_distance: 0.635690936717798', 'NSGA-II_rank: 4', 'change: 0.10088790114196268', 'is_elite: False']\n", + "Id: 89_34 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '88_88'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_34', 'origin': '88_88~CUW~88_88#MGNP'} Metrics: ['ELUC: -2.841080720683815', 'NSGA-II_crowding_distance: 0.41637912303862795', 'NSGA-II_rank: 3', 'change: 0.05504769180307813', 'is_elite: False']\n", + "Id: 89_85 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '86_83'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_85', 'origin': '88_88~CUW~86_83#MGNP'} Metrics: ['ELUC: -2.85122365095219', 'NSGA-II_crowding_distance: 0.07873402710279519', 'NSGA-II_rank: 2', 'change: 0.05013545835587969', 'is_elite: False']\n", + "Id: 89_11 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '88_88'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_11', 'origin': '88_16~CUW~88_88#MGNP'} Metrics: ['ELUC: -2.874893311017872', 'NSGA-II_crowding_distance: 0.2562786683062239', 'NSGA-II_rank: 2', 'change: 0.054177609033044076', 'is_elite: False']\n", + "Id: 89_67 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_67', 'origin': '88_71~CUW~2_49#MGNP'} Metrics: ['ELUC: -3.1641626587201714', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.24797349949815137', 'is_elite: False']\n", + "Id: 86_83 Identity: {'ancestor_count': 83, 'ancestor_ids': ['1_1', '85_84'], 'birth_generation': 86, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '86_83', 'origin': '1_1~CUW~85_84#MGNP'} Metrics: ['ELUC: -3.511415664087156', 'NSGA-II_crowding_distance: 0.19014810019480766', 'NSGA-II_rank: 1', 'change: 0.04652561459631126', 'is_elite: False']\n", + "Id: 89_91 Identity: {'ancestor_count': 84, 'ancestor_ids': ['86_83', '86_83'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_91', 'origin': '86_83~CUW~86_83#MGNP'} Metrics: ['ELUC: -3.655625842347465', 'NSGA-II_crowding_distance: 0.0882619999776312', 'NSGA-II_rank: 1', 'change: 0.06176596143295524', 'is_elite: False']\n", + "Id: 89_28 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_57', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_28', 'origin': '88_57~CUW~88_39#MGNP'} Metrics: ['ELUC: -3.7982502902546695', 'NSGA-II_crowding_distance: 1.2877114086837256', 'NSGA-II_rank: 4', 'change: 0.1461603841092159', 'is_elite: False']\n", + "Id: 89_57 Identity: {'ancestor_count': 86, 'ancestor_ids': ['88_88', '88_80'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_57', 'origin': '88_88~CUW~88_80#MGNP'} Metrics: ['ELUC: -3.8446610764240403', 'NSGA-II_crowding_distance: 0.18610934571626886', 'NSGA-II_rank: 1', 'change: 0.0672057510727318', 'is_elite: False']\n", + "Id: 89_46 Identity: {'ancestor_count': 84, 'ancestor_ids': ['2_49', '85_17'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_46', 'origin': '2_49~CUW~85_17#MGNP'} Metrics: ['ELUC: -4.209988648277263', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2689697819737604', 'is_elite: False']\n", + "Id: 89_72 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_12', '1_1'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_72', 'origin': '88_12~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.309804121653173', 'NSGA-II_crowding_distance: 0.4884293967028438', 'NSGA-II_rank: 3', 'change: 0.10735283211620425', 'is_elite: False']\n", + "Id: 89_88 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '88_80'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_88', 'origin': '88_16~CUW~88_80#MGNP'} Metrics: ['ELUC: -4.9469531812090235', 'NSGA-II_crowding_distance: 0.2813538872732563', 'NSGA-II_rank: 2', 'change: 0.08787076172415892', 'is_elite: False']\n", + "Id: 89_30 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '88_80'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_30', 'origin': '88_71~CUW~88_80#MGNP'} Metrics: ['ELUC: -5.040722349736508', 'NSGA-II_crowding_distance: 1.8005777734938568', 'NSGA-II_rank: 7', 'change: 0.2436856410161491', 'is_elite: False']\n", + "Id: 89_55 Identity: {'ancestor_count': 87, 'ancestor_ids': ['87_85', '88_16'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_55', 'origin': '87_85~CUW~88_16#MGNP'} Metrics: ['ELUC: -5.636789177807197', 'NSGA-II_crowding_distance: 0.08057167747277401', 'NSGA-II_rank: 2', 'change: 0.08855606523890484', 'is_elite: False']\n", + "Id: 89_82 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_27'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_82', 'origin': '1_1~CUW~88_27#MGNP'} Metrics: ['ELUC: -5.8355481433659575', 'NSGA-II_crowding_distance: 0.07925909279396604', 'NSGA-II_rank: 2', 'change: 0.09622273082464643', 'is_elite: False']\n", + "Id: 89_76 Identity: {'ancestor_count': 86, 'ancestor_ids': ['88_57', '88_80'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_76', 'origin': '88_57~CUW~88_80#MGNP'} Metrics: ['ELUC: -5.891118330896432', 'NSGA-II_crowding_distance: 0.21684913856613244', 'NSGA-II_rank: 1', 'change: 0.07935984619362409', 'is_elite: True']\n", + "Id: 89_40 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_57', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_40', 'origin': '88_57~CUW~88_71#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 89_96 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '88_27'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_96', 'origin': '88_71~CUW~88_27#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 88_17 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_25', '87_25'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_17', 'origin': '87_25~CUW~87_25#MGNP'} Metrics: ['ELUC: -6.394497711811051', 'NSGA-II_crowding_distance: 0.11452966236975413', 'NSGA-II_rank: 1', 'change: 0.08863718792163766', 'is_elite: False']\n", + "Id: 89_23 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_51', '88_17'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_23', 'origin': '88_51~CUW~88_17#MGNP'} Metrics: ['ELUC: -6.4676356038053', 'NSGA-II_crowding_distance: 0.15477432408988612', 'NSGA-II_rank: 2', 'change: 0.09743347803471113', 'is_elite: False']\n", + "Id: 89_48 Identity: {'ancestor_count': 87, 'ancestor_ids': ['85_17', '88_17'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_48', 'origin': '85_17~CUW~88_17#MGNP'} Metrics: ['ELUC: -6.8873672775873995', 'NSGA-II_crowding_distance: 0.147231331857414', 'NSGA-II_rank: 1', 'change: 0.09662629344216693', 'is_elite: False']\n", + "Id: 89_15 Identity: {'ancestor_count': 87, 'ancestor_ids': ['86_83', '88_17'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_15', 'origin': '86_83~CUW~88_17#MGNP'} Metrics: ['ELUC: -7.080279336067302', 'NSGA-II_crowding_distance: 0.2410286691567714', 'NSGA-II_rank: 3', 'change: 0.1129521767470629', 'is_elite: False']\n", + "Id: 89_37 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_12'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_37', 'origin': '1_1~CUW~88_12#MGNP'} Metrics: ['ELUC: -7.267496357911368', 'NSGA-II_crowding_distance: 0.10514831544742319', 'NSGA-II_rank: 3', 'change: 0.12249855598912694', 'is_elite: False']\n", + "Id: 89_68 Identity: {'ancestor_count': 86, 'ancestor_ids': ['85_17', '87_99'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_68', 'origin': '85_17~CUW~87_99#MGNP'} Metrics: ['ELUC: -7.2921576988577845', 'NSGA-II_crowding_distance: 0.19383053988260757', 'NSGA-II_rank: 3', 'change: 0.1362869696910703', 'is_elite: False']\n", + "Id: 89_13 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_13', 'origin': '88_79~CUW~88_39#MGNP'} Metrics: ['ELUC: -7.29332784518619', 'NSGA-II_crowding_distance: 1.6771233623905843', 'NSGA-II_rank: 6', 'change: 0.24221977285988666', 'is_elite: False']\n", + "Id: 89_93 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_93', 'origin': '1_1~CUW~88_39#MGNP'} Metrics: ['ELUC: -7.405362240680831', 'NSGA-II_crowding_distance: 1.4283474999064607', 'NSGA-II_rank: 5', 'change: 0.23507911411379498', 'is_elite: False']\n", + "Id: 88_16 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_25', '85_17'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_16', 'origin': '87_25~CUW~85_17#MGNP'} Metrics: ['ELUC: -7.976135032312253', 'NSGA-II_crowding_distance: 0.33690980076627774', 'NSGA-II_rank: 2', 'change: 0.1056374529963489', 'is_elite: False']\n", + "Id: 89_35 Identity: {'ancestor_count': 87, 'ancestor_ids': ['85_17', '88_16'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_35', 'origin': '85_17~CUW~88_16#MGNP'} Metrics: ['ELUC: -7.993466070211103', 'NSGA-II_crowding_distance: 0.11232103757567191', 'NSGA-II_rank: 1', 'change: 0.1054327504126408', 'is_elite: False']\n", + "Id: 89_53 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '87_99'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_53', 'origin': '88_16~CUW~87_99#MGNP'} Metrics: ['ELUC: -8.057098228790363', 'NSGA-II_crowding_distance: 0.028162759571060896', 'NSGA-II_rank: 1', 'change: 0.11028969319460148', 'is_elite: False']\n", + "Id: 89_54 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_12'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_54', 'origin': '1_1~CUW~88_12#MGNP'} Metrics: ['ELUC: -8.16109887432313', 'NSGA-II_crowding_distance: 0.3039602777299214', 'NSGA-II_rank: 3', 'change: 0.15771137707703997', 'is_elite: False']\n", + "Id: 89_92 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '88_16'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_92', 'origin': '88_16~CUW~88_16#MGNP'} Metrics: ['ELUC: -8.174373917400874', 'NSGA-II_crowding_distance: 0.19959425622892413', 'NSGA-II_rank: 1', 'change: 0.11076582832709338', 'is_elite: True']\n", + "Id: 89_31 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '88_88'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_31', 'origin': '88_71~CUW~88_88#MGNP'} Metrics: ['ELUC: -8.233020674345402', 'NSGA-II_crowding_distance: 0.6410853342701992', 'NSGA-II_rank: 7', 'change: 0.26055298101744895', 'is_elite: False']\n", + "Id: 89_39 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '88_80'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_39', 'origin': '88_71~CUW~88_80#MGNP'} Metrics: ['ELUC: -8.869084667984591', 'NSGA-II_crowding_distance: 1.0361617021908311', 'NSGA-II_rank: 4', 'change: 0.21893857711183354', 'is_elite: False']\n", + "Id: 89_61 Identity: {'ancestor_count': 87, 'ancestor_ids': ['87_85', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_61', 'origin': '87_85~CUW~88_71#MGNP'} Metrics: ['ELUC: -9.108368172758734', 'NSGA-II_crowding_distance: 0.2693910802881998', 'NSGA-II_rank: 5', 'change: 0.24207402771562667', 'is_elite: False']\n", + "Id: 89_100 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '88_95'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_100', 'origin': '88_16~CUW~88_95#MGNP'} Metrics: ['ELUC: -9.25398056986998', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2782279354703185', 'is_elite: False']\n", + "Id: 89_44 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_12', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_44', 'origin': '88_12~CUW~88_71#MGNP'} Metrics: ['ELUC: -9.465387728412374', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2535817861853933', 'is_elite: False']\n", + "Id: 89_97 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_88', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_97', 'origin': '88_88~CUW~88_71#MGNP'} Metrics: ['ELUC: -9.483900674444989', 'NSGA-II_crowding_distance: 0.43380652196363606', 'NSGA-II_rank: 5', 'change: 0.2509353260723928', 'is_elite: False']\n", + "Id: 89_20 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_27'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_20', 'origin': '1_1~CUW~88_27#MGNP'} Metrics: ['ELUC: -9.73774303349349', 'NSGA-II_crowding_distance: 0.39280469867094725', 'NSGA-II_rank: 2', 'change: 0.1391681895071083', 'is_elite: False']\n", + "Id: 89_69 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_17', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_69', 'origin': '88_17~CUW~88_39#MGNP'} Metrics: ['ELUC: -9.846357470489384', 'NSGA-II_crowding_distance: 0.45929032304864215', 'NSGA-II_rank: 4', 'change: 0.2243563055496376', 'is_elite: False']\n", + "Id: 89_90 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_17', '88_12'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_90', 'origin': '88_17~CUW~88_12#MGNP'} Metrics: ['ELUC: -10.199131629670944', 'NSGA-II_crowding_distance: 0.336245217405286', 'NSGA-II_rank: 3', 'change: 0.16815233047541173', 'is_elite: False']\n", + "Id: 89_33 Identity: {'ancestor_count': 87, 'ancestor_ids': ['85_17', '88_79'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_33', 'origin': '85_17~CUW~88_79#MGNP'} Metrics: ['ELUC: -10.450862547553172', 'NSGA-II_crowding_distance: 0.4176594746843521', 'NSGA-II_rank: 1', 'change: 0.1292212529995411', 'is_elite: True']\n", + "Id: 89_78 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '1_1'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_78', 'origin': '88_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.222755631387109', 'NSGA-II_crowding_distance: 0.2734405489127307', 'NSGA-II_rank: 2', 'change: 0.1629487528357713', 'is_elite: False']\n", + "Id: 89_17 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_88', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_17', 'origin': '88_88~CUW~88_39#MGNP'} Metrics: ['ELUC: -11.284602859067641', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.29502246185765874', 'is_elite: False']\n", + "Id: 89_22 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '88_57'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_22', 'origin': '88_71~CUW~88_57#MGNP'} Metrics: ['ELUC: -11.532054912425954', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2539788264017655', 'is_elite: False']\n", + "Id: 89_66 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_57', '88_58'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_66', 'origin': '88_57~CUW~88_58#MGNP'} Metrics: ['ELUC: -11.733485135358844', 'NSGA-II_crowding_distance: 0.6103292030079974', 'NSGA-II_rank: 3', 'change: 0.1874292018660242', 'is_elite: False']\n", + "Id: 89_24 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_88', '88_12'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_24', 'origin': '88_88~CUW~88_12#MGNP'} Metrics: ['ELUC: -12.28494297037779', 'NSGA-II_crowding_distance: 0.5191550958604114', 'NSGA-II_rank: 2', 'change: 0.1746742612943892', 'is_elite: False']\n", + "Id: 88_79 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '86_15'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_79', 'origin': '87_85~CUW~86_15#MGNP'} Metrics: ['ELUC: -12.48983153313787', 'NSGA-II_crowding_distance: 0.30241150709718456', 'NSGA-II_rank: 1', 'change: 0.16215146214524234', 'is_elite: True']\n", + "Id: 89_52 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '88_58'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_52', 'origin': '88_79~CUW~88_58#MGNP'} Metrics: ['ELUC: -13.00330729543699', 'NSGA-II_crowding_distance: 0.15964033124391136', 'NSGA-II_rank: 1', 'change: 0.17613833333425663', 'is_elite: False']\n", + "Id: 89_73 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_12', '88_16'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_73', 'origin': '88_12~CUW~88_16#MGNP'} Metrics: ['ELUC: -13.636813457869764', 'NSGA-II_crowding_distance: 0.18754930562246955', 'NSGA-II_rank: 1', 'change: 0.19031994257787296', 'is_elite: False']\n", + "Id: 89_42 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_12', '87_99'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_42', 'origin': '88_12~CUW~87_99#MGNP'} Metrics: ['ELUC: -13.95199260469149', 'NSGA-II_crowding_distance: 0.2676463656705436', 'NSGA-II_rank: 1', 'change: 0.21599938442574076', 'is_elite: True']\n", + "Id: 89_41 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_41', 'origin': '88_39~CUW~88_71#MGNP'} Metrics: ['ELUC: -14.108428560901205', 'NSGA-II_crowding_distance: 0.47864080802729403', 'NSGA-II_rank: 3', 'change: 0.2620364218349322', 'is_elite: False']\n", + "Id: 89_59 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_12', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_59', 'origin': '88_12~CUW~88_71#MGNP'} Metrics: ['ELUC: -14.591335126976805', 'NSGA-II_crowding_distance: 0.1252511413520261', 'NSGA-II_rank: 3', 'change: 0.264281895778399', 'is_elite: False']\n", + "Id: 89_26 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '88_12'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_26', 'origin': '88_71~CUW~88_12#MGNP'} Metrics: ['ELUC: -14.893300251021353', 'NSGA-II_crowding_distance: 0.3338756424894132', 'NSGA-II_rank: 3', 'change: 0.28157296518942276', 'is_elite: False']\n", + "Id: 89_27 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_17', '88_51'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_27', 'origin': '88_17~CUW~88_51#MGNP'} Metrics: ['ELUC: -15.360864792369076', 'NSGA-II_crowding_distance: 0.42462303404433566', 'NSGA-II_rank: 2', 'change: 0.2410311754101852', 'is_elite: False']\n", + "Id: 89_71 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '88_58'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_71', 'origin': '88_16~CUW~88_58#MGNP'} Metrics: ['ELUC: -15.389111606330145', 'NSGA-II_crowding_distance: 0.1593714185053145', 'NSGA-II_rank: 2', 'change: 0.24282584952784114', 'is_elite: False']\n", + "Id: 88_51 Identity: {'ancestor_count': 84, 'ancestor_ids': ['85_67', '85_67'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_51', 'origin': '85_67~CUW~85_67#MGNP'} Metrics: ['ELUC: -15.518710623569989', 'NSGA-II_crowding_distance: 0.18056754260405333', 'NSGA-II_rank: 1', 'change: 0.23824327858471578', 'is_elite: False']\n", + "Id: 89_21 Identity: {'ancestor_count': 85, 'ancestor_ids': ['85_17', '88_51'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_21', 'origin': '85_17~CUW~88_51#MGNP'} Metrics: ['ELUC: -15.560938056959857', 'NSGA-II_crowding_distance: 0.17143170050610035', 'NSGA-II_rank: 1', 'change: 0.24257241492761072', 'is_elite: False']\n", + "Id: 89_58 Identity: {'ancestor_count': 87, 'ancestor_ids': ['87_85', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_58', 'origin': '87_85~CUW~88_39#MGNP'} Metrics: ['ELUC: -16.151309288915282', 'NSGA-II_crowding_distance: 0.1928139746342038', 'NSGA-II_rank: 2', 'change: 0.2723370210230274', 'is_elite: False']\n", + "Id: 89_45 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '88_12'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_45', 'origin': '88_71~CUW~88_12#MGNP'} Metrics: ['ELUC: -16.397849825901385', 'NSGA-II_crowding_distance: 0.11953009926302545', 'NSGA-II_rank: 2', 'change: 0.27989948316142815', 'is_elite: False']\n", + "Id: 88_39 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_27', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_39', 'origin': '87_27~CUW~87_85#MGNP'} Metrics: ['ELUC: -16.538662252728123', 'NSGA-II_crowding_distance: 0.24597836888469252', 'NSGA-II_rank: 1', 'change: 0.27208578408966216', 'is_elite: True']\n", + "Id: 89_56 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '85_17'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_56', 'origin': '88_71~CUW~85_17#MGNP'} Metrics: ['ELUC: -16.948767174097533', 'NSGA-II_crowding_distance: 0.15191225402346875', 'NSGA-II_rank: 2', 'change: 0.2926887397567143', 'is_elite: False']\n", + "Id: 89_62 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_62', 'origin': '88_39~CUW~88_39#MGNP'} Metrics: ['ELUC: -17.094406685507682', 'NSGA-II_crowding_distance: 0.15605762733541942', 'NSGA-II_rank: 1', 'change: 0.2899434432284001', 'is_elite: False']\n", + "Id: 89_86 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_86', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.4816185155907', 'NSGA-II_crowding_distance: 0.06936681861966187', 'NSGA-II_rank: 1', 'change: 0.30264764387487214', 'is_elite: False']\n", + "Id: 89_94 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_12', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_94', 'origin': '88_12~CUW~88_71#MGNP'} Metrics: ['ELUC: -17.53931279827837', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30308516437575017', 'is_elite: False']\n", + "Id: 89_95 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_95', 'origin': '88_39~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.564746328181265', 'NSGA-II_crowding_distance: 0.007801745676548105', 'NSGA-II_rank: 1', 'change: 0.3026591473417241', 'is_elite: False']\n", + "Id: 89_81 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_81', 'origin': '88_39~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.586935345450964', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3030805467838557', 'is_elite: False']\n", + "Id: 89_51 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '1_1'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_51', 'origin': '88_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.596871637985824', 'NSGA-II_crowding_distance: 0.003067368175557814', 'NSGA-II_rank: 1', 'change: 0.30301962991360737', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 88_71 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_88', '2_49'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_71', 'origin': '87_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 89_16 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_71', '88_39'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_16', 'origin': '88_71~CUW~88_39#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 89_25 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_25', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 89_29 Identity: {'ancestor_count': 87, 'ancestor_ids': ['2_49', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_29', 'origin': '2_49~CUW~88_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 89_32 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_32', 'origin': '88_39~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 89_43 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '88_71'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_43', 'origin': '88_79~CUW~88_71#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 89_79 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_51', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_79', 'origin': '88_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 89.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 90...:\n", + "PopulationResponse:\n", + " Generation: 90\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/90/20240220-063140\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 90 and asking ESP for generation 91...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 90 data persisted.\n", + "Evaluated candidates:\n", + "Id: 90_87 Identity: {'ancestor_count': 87, 'ancestor_ids': ['89_76', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_87', 'origin': '89_76~CUW~89_79#MGNP'} Metrics: ['ELUC: 23.7970628924838', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3036072729627471', 'is_elite: False']\n", + "Id: 90_44 Identity: {'ancestor_count': 86, 'ancestor_ids': ['88_88', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_44', 'origin': '88_88~CUW~89_79#MGNP'} Metrics: ['ELUC: 23.473197177477804', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.3037133087218595', 'is_elite: False']\n", + "Id: 90_30 Identity: {'ancestor_count': 87, 'ancestor_ids': ['89_76', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_30', 'origin': '89_76~CUW~89_79#MGNP'} Metrics: ['ELUC: 6.690981147944656', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.1869190409515929', 'is_elite: False']\n", + "Id: 90_70 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_79', '89_42'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_70', 'origin': '89_79~CUW~89_42#MGNP'} Metrics: ['ELUC: 2.5242632532521028', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3517319306189846', 'is_elite: False']\n", + "Id: 90_85 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_85', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.0616993629566018', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.041735438312522834', 'is_elite: False']\n", + "Id: 90_81 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '89_92'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_81', 'origin': '89_42~CUW~89_92#MGNP'} Metrics: ['ELUC: 0.45325822635106483', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09930344853835228', 'is_elite: False']\n", + "Id: 90_72 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_17', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_72', 'origin': '88_17~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.36160685058187625', 'NSGA-II_crowding_distance: 0.14874621771952978', 'NSGA-II_rank: 2', 'change: 0.057587713489133885', 'is_elite: False']\n", + "Id: 90_99 Identity: {'ancestor_count': 87, 'ancestor_ids': ['1_1', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_99', 'origin': '1_1~CUW~88_79#MGNP'} Metrics: ['ELUC: 0.282972875111947', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.12215764190418177', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 90_17 Identity: {'ancestor_count': 85, 'ancestor_ids': ['1_1', '88_88'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_17', 'origin': '1_1~CUW~88_88#MGNP'} Metrics: ['ELUC: -0.1699398186570407', 'NSGA-II_crowding_distance: 0.1486613713567499', 'NSGA-II_rank: 1', 'change: 0.031128250543945468', 'is_elite: False']\n", + "Id: 90_39 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_88', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_39', 'origin': '88_88~CUW~88_79#MGNP'} Metrics: ['ELUC: -0.22936377487037873', 'NSGA-II_crowding_distance: 0.6580631474563408', 'NSGA-II_rank: 4', 'change: 0.10050288721020706', 'is_elite: False']\n", + "Id: 90_69 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_73', '86_83'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_69', 'origin': '89_73~CUW~86_83#MGNP'} Metrics: ['ELUC: -0.37993903535894036', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15141589352037246', 'is_elite: False']\n", + "Id: 90_49 Identity: {'ancestor_count': 87, 'ancestor_ids': ['89_76', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_49', 'origin': '89_76~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.47049101465446475', 'NSGA-II_crowding_distance: 0.18545555402454056', 'NSGA-II_rank: 2', 'change: 0.05914505571271888', 'is_elite: False']\n", + "Id: 90_64 Identity: {'ancestor_count': 86, 'ancestor_ids': ['89_79', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_64', 'origin': '89_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 90_13 Identity: {'ancestor_count': 84, 'ancestor_ids': ['86_83', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_13', 'origin': '86_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6073611172490841', 'NSGA-II_crowding_distance: 0.11078213876796025', 'NSGA-II_rank: 1', 'change: 0.03894824585274922', 'is_elite: False']\n", + "Id: 90_76 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_88', '89_33'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_76', 'origin': '88_88~CUW~89_33#MGNP'} Metrics: ['ELUC: -0.6367770303679062', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.09690678094883859', 'is_elite: False']\n", + "Id: 90_86 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_88', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_86', 'origin': '88_88~CUW~88_79#MGNP'} Metrics: ['ELUC: -0.9851349518183514', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.14610706189534878', 'is_elite: False']\n", + "Id: 90_33 Identity: {'ancestor_count': 87, 'ancestor_ids': ['89_76', '88_39'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_33', 'origin': '89_76~CUW~88_39#MGNP'} Metrics: ['ELUC: -1.1089391968448117', 'NSGA-II_crowding_distance: 1.1509360633004588', 'NSGA-II_rank: 7', 'change: 0.19847981916696245', 'is_elite: False']\n", + "Id: 88_88 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_88', 'origin': '1_1~CUW~86_83#MGNP'} Metrics: ['ELUC: -1.3221503501141663', 'NSGA-II_crowding_distance: 0.2338468000116527', 'NSGA-II_rank: 1', 'change: 0.04462980410980077', 'is_elite: True']\n", + "Id: 90_35 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_73', '86_83'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_35', 'origin': '89_73~CUW~86_83#MGNP'} Metrics: ['ELUC: -1.525591467362549', 'NSGA-II_crowding_distance: 0.5678756918674093', 'NSGA-II_rank: 5', 'change: 0.14131871349668432', 'is_elite: False']\n", + "Id: 90_16 Identity: {'ancestor_count': 87, 'ancestor_ids': ['2_49', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_16', 'origin': '2_49~CUW~88_79#MGNP'} Metrics: ['ELUC: -1.6853607682709086', 'NSGA-II_crowding_distance: 1.5025466971283257', 'NSGA-II_rank: 7', 'change: 0.26823298913257415', 'is_elite: False']\n", + "Id: 90_84 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_88', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_84', 'origin': '88_88~CUW~88_79#MGNP'} Metrics: ['ELUC: -2.067666148003346', 'NSGA-II_crowding_distance: 0.7611058053941151', 'NSGA-II_rank: 6', 'change: 0.14900381529293488', 'is_elite: False']\n", + "Id: 90_15 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '86_83'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_15', 'origin': '89_33~CUW~86_83#MGNP'} Metrics: ['ELUC: -2.4981897996326747', 'NSGA-II_crowding_distance: 0.20069980786433528', 'NSGA-II_rank: 3', 'change: 0.09745939177914535', 'is_elite: False']\n", + "Id: 90_29 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_92', '88_88'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_29', 'origin': '89_92~CUW~88_88#MGNP'} Metrics: ['ELUC: -2.9551159010052968', 'NSGA-II_crowding_distance: 0.3335793793721943', 'NSGA-II_rank: 2', 'change: 0.059599777180066024', 'is_elite: False']\n", + "Id: 90_92 Identity: {'ancestor_count': 88, 'ancestor_ids': ['1_1', '89_92'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_92', 'origin': '1_1~CUW~89_92#MGNP'} Metrics: ['ELUC: -3.1107748929975365', 'NSGA-II_crowding_distance: 0.16721082227436276', 'NSGA-II_rank: 3', 'change: 0.10206479730629209', 'is_elite: False']\n", + "Id: 90_59 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_39', '89_33'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_59', 'origin': '88_39~CUW~89_33#MGNP'} Metrics: ['ELUC: -3.152459585635734', 'NSGA-II_crowding_distance: 1.2537858000668418', 'NSGA-II_rank: 6', 'change: 0.2188885661028549', 'is_elite: False']\n", + "Id: 90_96 Identity: {'ancestor_count': 84, 'ancestor_ids': ['86_83', '86_83'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_96', 'origin': '86_83~CUW~86_83#MGNP'} Metrics: ['ELUC: -3.788780802958937', 'NSGA-II_crowding_distance: 0.2391111768114113', 'NSGA-II_rank: 1', 'change: 0.05473324707588939', 'is_elite: True']\n", + "Id: 90_90 Identity: {'ancestor_count': 88, 'ancestor_ids': ['1_1', '89_42'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_90', 'origin': '1_1~CUW~89_42#MGNP'} Metrics: ['ELUC: -3.9935325267655175', 'NSGA-II_crowding_distance: 0.2759967974235744', 'NSGA-II_rank: 3', 'change: 0.10928577949420944', 'is_elite: False']\n", + "Id: 90_77 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_77', 'origin': '88_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -4.065968710782686', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.31800954320098834', 'is_elite: False']\n", + "Id: 90_31 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '86_83'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_31', 'origin': '1_1~CUW~86_83#MGNP'} Metrics: ['ELUC: -4.099694888326758', 'NSGA-II_crowding_distance: 0.186472371830002', 'NSGA-II_rank: 1', 'change: 0.06883946376440994', 'is_elite: False']\n", + "Id: 90_93 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_92', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_93', 'origin': '89_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.320101363766253', 'NSGA-II_crowding_distance: 0.3166393238524694', 'NSGA-II_rank: 2', 'change: 0.0923975490064765', 'is_elite: False']\n", + "Id: 90_74 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_88', '89_52'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_74', 'origin': '88_88~CUW~89_52#MGNP'} Metrics: ['ELUC: -5.249458143692194', 'NSGA-II_crowding_distance: 0.6886554098582699', 'NSGA-II_rank: 5', 'change: 0.1415403927731472', 'is_elite: False']\n", + "Id: 90_45 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_88', '89_76'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_45', 'origin': '88_88~CUW~89_76#MGNP'} Metrics: ['ELUC: -5.7722475203501675', 'NSGA-II_crowding_distance: 0.1371462690996652', 'NSGA-II_rank: 1', 'change: 0.0767124057414156', 'is_elite: False']\n", + "Id: 89_76 Identity: {'ancestor_count': 86, 'ancestor_ids': ['88_57', '88_80'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_76', 'origin': '88_57~CUW~88_80#MGNP'} Metrics: ['ELUC: -5.891118330896432', 'NSGA-II_crowding_distance: 0.024108261001861524', 'NSGA-II_rank: 1', 'change: 0.07935984619362409', 'is_elite: False']\n", + "Id: 90_28 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_92', '89_76'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_28', 'origin': '89_92~CUW~89_76#MGNP'} Metrics: ['ELUC: -5.996082816764932', 'NSGA-II_crowding_distance: 0.22000888443945207', 'NSGA-II_rank: 2', 'change: 0.09974967871244654', 'is_elite: False']\n", + "Id: 90_36 Identity: {'ancestor_count': 87, 'ancestor_ids': ['89_76', '89_76'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_36', 'origin': '89_76~CUW~89_76#MGNP'} Metrics: ['ELUC: -6.032079587179596', 'NSGA-II_crowding_distance: 0.1630430483698813', 'NSGA-II_rank: 1', 'change: 0.07949634331067157', 'is_elite: False']\n", + "Id: 90_54 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '88_88'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_54', 'origin': '89_33~CUW~88_88#MGNP'} Metrics: ['ELUC: -6.1875405102782635', 'NSGA-II_crowding_distance: 0.2682284459911743', 'NSGA-II_rank: 3', 'change: 0.11348780729594915', 'is_elite: False']\n", + "Id: 90_89 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_92', '88_39'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_89', 'origin': '89_92~CUW~88_39#MGNP'} Metrics: ['ELUC: -6.372545039753456', 'NSGA-II_crowding_distance: 0.6588399067868167', 'NSGA-II_rank: 5', 'change: 0.19079303190402563', 'is_elite: False']\n", + "Id: 90_14 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_14', 'origin': '88_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.395287346241045', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.27649832212910813', 'is_elite: False']\n", + "Id: 90_79 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '88_88'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_79', 'origin': '89_42~CUW~88_88#MGNP'} Metrics: ['ELUC: -6.7503891670255145', 'NSGA-II_crowding_distance: 0.17404661958170464', 'NSGA-II_rank: 3', 'change: 0.12349166085143552', 'is_elite: False']\n", + "Id: 90_66 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_39', '89_33'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_66', 'origin': '88_39~CUW~89_33#MGNP'} Metrics: ['ELUC: -6.865940031492328', 'NSGA-II_crowding_distance: 0.6847595900007439', 'NSGA-II_rank: 5', 'change: 0.23099752657019507', 'is_elite: False']\n", + "Id: 90_50 Identity: {'ancestor_count': 86, 'ancestor_ids': ['88_88', '89_21'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_50', 'origin': '88_88~CUW~89_21#MGNP'} Metrics: ['ELUC: -7.079223790311002', 'NSGA-II_crowding_distance: 0.13166215377218649', 'NSGA-II_rank: 2', 'change: 0.1112460731568955', 'is_elite: False']\n", + "Id: 90_82 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '88_51'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_82', 'origin': '89_33~CUW~88_51#MGNP'} Metrics: ['ELUC: -7.194221938086874', 'NSGA-II_crowding_distance: 0.07972655951709287', 'NSGA-II_rank: 2', 'change: 0.11737326913855317', 'is_elite: False']\n", + "Id: 90_21 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_88', '89_52'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_21', 'origin': '88_88~CUW~89_52#MGNP'} Metrics: ['ELUC: -7.276869060031223', 'NSGA-II_crowding_distance: 1.1454064325742905', 'NSGA-II_rank: 4', 'change: 0.1297644146611738', 'is_elite: False']\n", + "Id: 90_46 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_17', '89_33'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_46', 'origin': '88_17~CUW~89_33#MGNP'} Metrics: ['ELUC: -7.40133983869486', 'NSGA-II_crowding_distance: 0.2266418593916947', 'NSGA-II_rank: 1', 'change: 0.10237933392156229', 'is_elite: True']\n", + "Id: 90_80 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_80', 'origin': '88_39~CUW~88_79#MGNP'} Metrics: ['ELUC: -7.453432596420894', 'NSGA-II_crowding_distance: 0.9103338209514492', 'NSGA-II_rank: 6', 'change: 0.24518900370682142', 'is_elite: False']\n", + "Id: 90_51 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_76', '89_73'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_51', 'origin': '89_76~CUW~89_73#MGNP'} Metrics: ['ELUC: -7.55079113618812', 'NSGA-II_crowding_distance: 0.26759889673118964', 'NSGA-II_rank: 3', 'change: 0.12836869390817257', 'is_elite: False']\n", + "Id: 90_57 Identity: {'ancestor_count': 88, 'ancestor_ids': ['86_83', '89_92'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_57', 'origin': '86_83~CUW~89_92#MGNP'} Metrics: ['ELUC: -7.698763780891689', 'NSGA-II_crowding_distance: 0.14046204674531682', 'NSGA-II_rank: 2', 'change: 0.1234019005285311', 'is_elite: False']\n", + "Id: 89_92 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_16', '88_16'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_92', 'origin': '88_16~CUW~88_16#MGNP'} Metrics: ['ELUC: -8.174373917400874', 'NSGA-II_crowding_distance: 0.20228822983907185', 'NSGA-II_rank: 1', 'change: 0.11076582832709338', 'is_elite: False']\n", + "Id: 90_73 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_73', 'origin': '88_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.823117343998698', 'NSGA-II_crowding_distance: 0.5183539578353129', 'NSGA-II_rank: 3', 'change: 0.1466810695108536', 'is_elite: False']\n", + "Id: 90_27 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '89_52'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_27', 'origin': '89_33~CUW~89_52#MGNP'} Metrics: ['ELUC: -8.890410805490975', 'NSGA-II_crowding_distance: 0.3523624399581794', 'NSGA-II_rank: 2', 'change: 0.13032185223702006', 'is_elite: False']\n", + "Id: 90_42 Identity: {'ancestor_count': 86, 'ancestor_ids': ['86_83', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_42', 'origin': '86_83~CUW~89_79#MGNP'} Metrics: ['ELUC: -9.302511726799576', 'NSGA-II_crowding_distance: 0.6179593802620728', 'NSGA-II_rank: 6', 'change: 0.2594772671959775', 'is_elite: False']\n", + "Id: 90_67 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '89_73'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_67', 'origin': '89_33~CUW~89_73#MGNP'} Metrics: ['ELUC: -9.385031857495306', 'NSGA-II_crowding_distance: 0.19132842540441936', 'NSGA-II_rank: 1', 'change: 0.12907376871633416', 'is_elite: False']\n", + "Id: 89_33 Identity: {'ancestor_count': 87, 'ancestor_ids': ['85_17', '88_79'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_33', 'origin': '85_17~CUW~88_79#MGNP'} Metrics: ['ELUC: -10.450862547553172', 'NSGA-II_crowding_distance: 0.28744472724532977', 'NSGA-II_rank: 1', 'change: 0.1292212529995411', 'is_elite: True']\n", + "Id: 90_40 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '89_62'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_40', 'origin': '89_42~CUW~89_62#MGNP'} Metrics: ['ELUC: -11.080877402772401', 'NSGA-II_crowding_distance: 0.5778976211620044', 'NSGA-II_rank: 5', 'change: 0.24153825232759288', 'is_elite: False']\n", + "Id: 90_43 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '88_88'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_43', 'origin': '2_49~CUW~88_88#MGNP'} Metrics: ['ELUC: -11.155070690525665', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.27892127184908555', 'is_elite: False']\n", + "Id: 90_88 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_51', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_88', 'origin': '88_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.222439477991907', 'NSGA-II_crowding_distance: 0.3655033473532884', 'NSGA-II_rank: 5', 'change: 0.2684832070991586', 'is_elite: False']\n", + "Id: 90_32 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_79', '89_42'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_32', 'origin': '88_79~CUW~89_42#MGNP'} Metrics: ['ELUC: -11.31476893758738', 'NSGA-II_crowding_distance: 0.336848639798229', 'NSGA-II_rank: 2', 'change: 0.16483334874579578', 'is_elite: False']\n", + "Id: 90_75 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '89_57'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_75', 'origin': '89_42~CUW~89_57#MGNP'} Metrics: ['ELUC: -11.371610078192345', 'NSGA-II_crowding_distance: 0.40711918845591777', 'NSGA-II_rank: 3', 'change: 0.17587149379722553', 'is_elite: False']\n", + "Id: 90_20 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '89_76'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_20', 'origin': '89_42~CUW~89_76#MGNP'} Metrics: ['ELUC: -11.397142223936516', 'NSGA-II_crowding_distance: 1.1375657076419312', 'NSGA-II_rank: 4', 'change: 0.18386867815398866', 'is_elite: False']\n", + "Id: 90_62 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_62', 'origin': '88_39~CUW~89_79#MGNP'} Metrics: ['ELUC: -11.906841907853954', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.29215368516986273', 'is_elite: False']\n", + "Id: 90_48 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_48', 'origin': '89_42~CUW~88_79#MGNP'} Metrics: ['ELUC: -11.985069326049993', 'NSGA-II_crowding_distance: 0.5836185305958645', 'NSGA-II_rank: 3', 'change: 0.1818471958186188', 'is_elite: False']\n", + "Id: 90_19 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_19', 'origin': '89_42~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.019311271484405', 'NSGA-II_crowding_distance: 0.15343829823589739', 'NSGA-II_rank: 2', 'change: 0.17452079758739059', 'is_elite: False']\n", + "Id: 88_79 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '86_15'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_79', 'origin': '87_85~CUW~86_15#MGNP'} Metrics: ['ELUC: -12.48983153313787', 'NSGA-II_crowding_distance: 0.24542664803437353', 'NSGA-II_rank: 1', 'change: 0.16215146214524234', 'is_elite: True']\n", + "Id: 90_11 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_92', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_11', 'origin': '89_92~CUW~88_79#MGNP'} Metrics: ['ELUC: -12.613228717797956', 'NSGA-II_crowding_distance: 0.02778558987682231', 'NSGA-II_rank: 1', 'change: 0.16575507500544673', 'is_elite: False']\n", + "Id: 90_60 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_60', 'origin': '89_33~CUW~88_79#MGNP'} Metrics: ['ELUC: -12.693183619723094', 'NSGA-II_crowding_distance: 0.08732648397898202', 'NSGA-II_rank: 1', 'change: 0.16699111536926375', 'is_elite: False']\n", + "Id: 90_55 Identity: {'ancestor_count': 87, 'ancestor_ids': ['89_76', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_55', 'origin': '89_76~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.736063382579436', 'NSGA-II_crowding_distance: 0.8038551653003403', 'NSGA-II_rank: 4', 'change: 0.28729037739608665', 'is_elite: False']\n", + "Id: 90_68 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '89_73'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_68', 'origin': '89_33~CUW~89_73#MGNP'} Metrics: ['ELUC: -13.029082823173418', 'NSGA-II_crowding_distance: 0.09081574301971784', 'NSGA-II_rank: 2', 'change: 0.18091862579578027', 'is_elite: False']\n", + "Id: 90_18 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_79', '89_92'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_18', 'origin': '88_79~CUW~89_92#MGNP'} Metrics: ['ELUC: -13.195874787872725', 'NSGA-II_crowding_distance: 0.09471440520776543', 'NSGA-II_rank: 2', 'change: 0.1817739538315336', 'is_elite: False']\n", + "Id: 90_22 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_62', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_22', 'origin': '89_62~CUW~89_79#MGNP'} Metrics: ['ELUC: -13.229940753751865', 'NSGA-II_crowding_distance: 0.588915867901194', 'NSGA-II_rank: 3', 'change: 0.26186905052537435', 'is_elite: False']\n", + "Id: 90_52 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '89_33'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_52', 'origin': '89_42~CUW~89_33#MGNP'} Metrics: ['ELUC: -13.363236287607942', 'NSGA-II_crowding_distance: 0.17151182579023722', 'NSGA-II_rank: 2', 'change: 0.20098687893612438', 'is_elite: False']\n", + "Id: 90_56 Identity: {'ancestor_count': 88, 'ancestor_ids': ['2_49', '89_92'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_56', 'origin': '2_49~CUW~89_92#MGNP'} Metrics: ['ELUC: -13.457084011503808', 'NSGA-II_crowding_distance: 0.18846379691688558', 'NSGA-II_rank: 3', 'change: 0.2739900594632506', 'is_elite: False']\n", + "Id: 90_34 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '88_88'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_34', 'origin': '88_79~CUW~88_88#MGNP'} Metrics: ['ELUC: -13.49234230889764', 'NSGA-II_crowding_distance: 0.12013677648305551', 'NSGA-II_rank: 1', 'change: 0.17689252314380943', 'is_elite: False']\n", + "Id: 90_83 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_73', '89_73'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_83', 'origin': '89_73~CUW~89_73#MGNP'} Metrics: ['ELUC: -13.569132521199732', 'NSGA-II_crowding_distance: 0.0638722568081984', 'NSGA-II_rank: 1', 'change: 0.18797212935105295', 'is_elite: False']\n", + "Id: 90_97 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '89_73'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_97', 'origin': '89_33~CUW~89_73#MGNP'} Metrics: ['ELUC: -13.671680341749157', 'NSGA-II_crowding_distance: 0.08710596386171335', 'NSGA-II_rank: 1', 'change: 0.1929071594583667', 'is_elite: False']\n", + "Id: 89_42 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_12', '87_99'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_42', 'origin': '88_12~CUW~87_99#MGNP'} Metrics: ['ELUC: -13.95199260469149', 'NSGA-II_crowding_distance: 0.41704558222589083', 'NSGA-II_rank: 2', 'change: 0.21599938442574076', 'is_elite: False']\n", + "Id: 90_24 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_73', '88_51'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_24', 'origin': '89_73~CUW~88_51#MGNP'} Metrics: ['ELUC: -14.206589193647947', 'NSGA-II_crowding_distance: 0.17214074955064163', 'NSGA-II_rank: 1', 'change: 0.20314477158125765', 'is_elite: False']\n", + "Id: 90_63 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_51', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_63', 'origin': '88_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.499799912842525', 'NSGA-II_crowding_distance: 0.16746494924846456', 'NSGA-II_rank: 3', 'change: 0.2807278309846197', 'is_elite: False']\n", + "Id: 90_25 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_51', '88_88'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_25', 'origin': '88_51~CUW~88_88#MGNP'} Metrics: ['ELUC: -14.583702329910752', 'NSGA-II_crowding_distance: 0.17479278181019584', 'NSGA-II_rank: 1', 'change: 0.22879282866475703', 'is_elite: False']\n", + "Id: 90_71 Identity: {'ancestor_count': 87, 'ancestor_ids': ['86_83', '88_39'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_71', 'origin': '86_83~CUW~88_39#MGNP'} Metrics: ['ELUC: -14.608341521601725', 'NSGA-II_crowding_distance: 0.25628330832829244', 'NSGA-II_rank: 1', 'change: 0.24848118149412177', 'is_elite: True']\n", + "Id: 90_12 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_92', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_12', 'origin': '89_92~CUW~89_79#MGNP'} Metrics: ['ELUC: -14.782114096338207', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.3014562488829136', 'is_elite: False']\n", + "Id: 90_23 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '88_51'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_23', 'origin': '2_49~CUW~88_51#MGNP'} Metrics: ['ELUC: -14.895115508104926', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.28662723950555913', 'is_elite: False']\n", + "Id: 90_61 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_61', 'origin': '88_39~CUW~88_79#MGNP'} Metrics: ['ELUC: -15.865009559368955', 'NSGA-II_crowding_distance: 0.3655940466440124', 'NSGA-II_rank: 2', 'change: 0.274921882435088', 'is_elite: False']\n", + "Id: 90_53 Identity: {'ancestor_count': 87, 'ancestor_ids': ['89_79', '88_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_53', 'origin': '89_79~CUW~88_79#MGNP'} Metrics: ['ELUC: -16.337692622230342', 'NSGA-II_crowding_distance: 0.052290163776574805', 'NSGA-II_rank: 2', 'change: 0.27811626106926973', 'is_elite: False']\n", + "Id: 90_26 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_79', '89_62'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_26', 'origin': '88_79~CUW~89_62#MGNP'} Metrics: ['ELUC: -16.391918051724534', 'NSGA-II_crowding_distance: 0.0756211046770473', 'NSGA-II_rank: 2', 'change: 0.28120612346314533', 'is_elite: False']\n", + "Id: 90_91 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '88_39'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_91', 'origin': '89_42~CUW~88_39#MGNP'} Metrics: ['ELUC: -16.456648729116612', 'NSGA-II_crowding_distance: 0.1428860848835736', 'NSGA-II_rank: 2', 'change: 0.2962091688933098', 'is_elite: False']\n", + "Id: 88_39 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_27', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_39', 'origin': '87_27~CUW~87_85#MGNP'} Metrics: ['ELUC: -16.538662252728123', 'NSGA-II_crowding_distance: 0.319243057394925', 'NSGA-II_rank: 1', 'change: 0.27208578408966216', 'is_elite: True']\n", + "Id: 90_65 Identity: {'ancestor_count': 87, 'ancestor_ids': ['89_79', '89_57'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_65', 'origin': '89_79~CUW~89_57#MGNP'} Metrics: ['ELUC: -17.18511231546954', 'NSGA-II_crowding_distance: 0.1588516659128735', 'NSGA-II_rank: 1', 'change: 0.30000760083917416', 'is_elite: False']\n", + "Id: 90_98 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_42', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_98', 'origin': '89_42~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.528580947871035', 'NSGA-II_crowding_distance: 0.08719872976200624', 'NSGA-II_rank: 2', 'change: 0.3026232244263771', 'is_elite: False']\n", + "Id: 90_78 Identity: {'ancestor_count': 86, 'ancestor_ids': ['89_79', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_78', 'origin': '89_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.53723338811864', 'NSGA-II_crowding_distance: 0.033478615781521746', 'NSGA-II_rank: 1', 'change: 0.30253752119396804', 'is_elite: False']\n", + "Id: 90_47 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_47', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.596583314261725', 'NSGA-II_crowding_distance: 0.00503979839025814', 'NSGA-II_rank: 1', 'change: 0.30301408404479724', 'is_elite: False']\n", + "Id: 90_38 Identity: {'ancestor_count': 86, 'ancestor_ids': ['89_21', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_38', 'origin': '89_21~CUW~89_79#MGNP'} Metrics: ['ELUC: -17.59726606357932', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302061467220565', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 89_79 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_51', '2_49'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_79', 'origin': '88_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 90_37 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_37', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 90_41 Identity: {'ancestor_count': 86, 'ancestor_ids': ['89_79', '89_79'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_41', 'origin': '89_79~CUW~89_79#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 90_58 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_79', '89_52'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_58', 'origin': '89_79~CUW~89_52#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 90_94 Identity: {'ancestor_count': 84, 'ancestor_ids': ['86_83', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_94', 'origin': '86_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 90_95 Identity: {'ancestor_count': 86, 'ancestor_ids': ['89_79', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_95', 'origin': '89_79~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 90_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 90.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 91...:\n", + "PopulationResponse:\n", + " Generation: 91\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/91/20240220-063855\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 91 and asking ESP for generation 92...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 91 data persisted.\n", + "Evaluated candidates:\n", + "Id: 91_12 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '90_96'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_12', 'origin': '2_49~CUW~90_96#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 91_77 Identity: {'ancestor_count': 86, 'ancestor_ids': ['90_25', '90_100'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_77', 'origin': '90_25~CUW~90_100#MGNP'} Metrics: ['ELUC: 22.177112596985868', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2921232408609782', 'is_elite: False']\n", + "Id: 91_52 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_67', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_52', 'origin': '90_67~CUW~1_1#MGNP'} Metrics: ['ELUC: 8.160642458200753', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15096078312273978', 'is_elite: False']\n", + "Id: 91_95 Identity: {'ancestor_count': 3, 'ancestor_ids': ['90_100', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_95', 'origin': '90_100~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 91_37 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_37', 'origin': '89_33~CUW~1_1#MGNP'} Metrics: ['ELUC: 2.143985916323711', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10634314567445634', 'is_elite: False']\n", + "Id: 91_11 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_67', '90_31'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_11', 'origin': '90_67~CUW~90_31#MGNP'} Metrics: ['ELUC: 1.492801122524208', 'NSGA-II_crowding_distance: 0.3382505611535128', 'NSGA-II_rank: 6', 'change: 0.10829984932789001', 'is_elite: False']\n", + "Id: 91_86 Identity: {'ancestor_count': 86, 'ancestor_ids': ['90_25', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_86', 'origin': '90_25~CUW~88_88#MGNP'} Metrics: ['ELUC: 0.7080102885990216', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.08854106361983789', 'is_elite: False']\n", + "Id: 91_54 Identity: {'ancestor_count': 86, 'ancestor_ids': ['90_25', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_54', 'origin': '90_25~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.3889220930796463', 'NSGA-II_crowding_distance: 1.3248481794361617', 'NSGA-II_rank: 6', 'change: 0.1421108902695656', 'is_elite: False']\n", + "Id: 91_84 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_36', '90_67'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_84', 'origin': '90_36~CUW~90_67#MGNP'} Metrics: ['ELUC: 0.16668002387347364', 'NSGA-II_crowding_distance: 0.375761108479186', 'NSGA-II_rank: 5', 'change: 0.12034149049205439', 'is_elite: False']\n", + "Id: 91_29 Identity: {'ancestor_count': 86, 'ancestor_ids': ['90_17', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_29', 'origin': '90_17~CUW~88_88#MGNP'} Metrics: ['ELUC: 0.14320944460440801', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.05194987396634379', 'is_elite: False']\n", + "Id: 91_39 Identity: {'ancestor_count': 87, 'ancestor_ids': ['90_100', '88_39'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_39', 'origin': '90_100~CUW~88_39#MGNP'} Metrics: ['ELUC: 0.08271159392214239', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.340380515315627', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 91_51 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '2_49'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_51', 'origin': '89_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.018263909671792023', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2534328808383573', 'is_elite: False']\n", + "Id: 91_59 Identity: {'ancestor_count': 86, 'ancestor_ids': ['1_1', '90_17'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_59', 'origin': '1_1~CUW~90_17#MGNP'} Metrics: ['ELUC: -0.2849959664464308', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.04693013460859544', 'is_elite: False']\n", + "Id: 91_28 Identity: {'ancestor_count': 88, 'ancestor_ids': ['2_49', '90_36'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_28', 'origin': '2_49~CUW~90_36#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 91_96 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_24', '90_100'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_96', 'origin': '90_24~CUW~90_100#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 91_93 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '89_92'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_93', 'origin': '90_71~CUW~89_92#MGNP'} Metrics: ['ELUC: -0.6854105550106605', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24102300012355804', 'is_elite: False']\n", + "Id: 91_34 Identity: {'ancestor_count': 88, 'ancestor_ids': ['2_49', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_34', 'origin': '2_49~CUW~89_33#MGNP'} Metrics: ['ELUC: -0.7407280187150662', 'NSGA-II_crowding_distance: 1.5170497370007396', 'NSGA-II_rank: 7', 'change: 0.23639119694221272', 'is_elite: False']\n", + "Id: 91_44 Identity: {'ancestor_count': 89, 'ancestor_ids': ['88_88', '90_46'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_44', 'origin': '88_88~CUW~90_46#MGNP'} Metrics: ['ELUC: -0.9731498722467241', 'NSGA-II_crowding_distance: 0.2519502985618615', 'NSGA-II_rank: 4', 'change: 0.0679504178241251', 'is_elite: False']\n", + "Id: 91_25 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_25', 'origin': '88_88~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1284853779609225', 'NSGA-II_crowding_distance: 0.11862540589865396', 'NSGA-II_rank: 3', 'change: 0.05408074112603497', 'is_elite: False']\n", + "Id: 91_35 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_35', 'origin': '90_46~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1353214174591426', 'NSGA-II_crowding_distance: 0.2537055342950766', 'NSGA-II_rank: 3', 'change: 0.0640614473309139', 'is_elite: False']\n", + "Id: 91_53 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_53', 'origin': '90_46~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.1826697218607782', 'NSGA-II_crowding_distance: 0.22965476986538458', 'NSGA-II_rank: 4', 'change: 0.0900061649001409', 'is_elite: False']\n", + "Id: 91_18 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '90_100'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_18', 'origin': '89_33~CUW~90_100#MGNP'} Metrics: ['ELUC: -1.2568592524700153', 'NSGA-II_crowding_distance: 0.21228511350386395', 'NSGA-II_rank: 7', 'change: 0.24037498458325998', 'is_elite: False']\n", + "Id: 88_88 Identity: {'ancestor_count': 84, 'ancestor_ids': ['1_1', '86_83'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_88', 'origin': '1_1~CUW~86_83#MGNP'} Metrics: ['ELUC: -1.3221503501141663', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04462980410980077', 'is_elite: False']\n", + "Id: 91_43 Identity: {'ancestor_count': 85, 'ancestor_ids': ['90_96', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_43', 'origin': '90_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.3764217631979803', 'NSGA-II_crowding_distance: 0.1237980290254334', 'NSGA-II_rank: 2', 'change: 0.051228178393540054', 'is_elite: False']\n", + "Id: 91_57 Identity: {'ancestor_count': 85, 'ancestor_ids': ['90_100', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_57', 'origin': '90_100~CUW~88_88#MGNP'} Metrics: ['ELUC: -1.3921225889464932', 'NSGA-II_crowding_distance: 0.48295026299926014', 'NSGA-II_rank: 7', 'change: 0.2556770744733048', 'is_elite: False']\n", + "Id: 91_82 Identity: {'ancestor_count': 86, 'ancestor_ids': ['88_88', '90_25'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_82', 'origin': '88_88~CUW~90_25#MGNP'} Metrics: ['ELUC: -1.638734340003489', 'NSGA-II_crowding_distance: 0.5790914910459599', 'NSGA-II_rank: 5', 'change: 0.12374790204483775', 'is_elite: False']\n", + "Id: 91_70 Identity: {'ancestor_count': 85, 'ancestor_ids': ['90_96', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_70', 'origin': '90_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6637054409234922', 'NSGA-II_crowding_distance: 0.31107141237623037', 'NSGA-II_rank: 1', 'change: 0.03948720599796149', 'is_elite: True']\n", + "Id: 91_45 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_36', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_45', 'origin': '90_36~CUW~88_88#MGNP'} Metrics: ['ELUC: -2.0002965620504103', 'NSGA-II_crowding_distance: 0.11049895521388088', 'NSGA-II_rank: 2', 'change: 0.06580279220008788', 'is_elite: False']\n", + "Id: 91_74 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_74', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.0229742892799614', 'NSGA-II_crowding_distance: 0.09182436008853637', 'NSGA-II_rank: 2', 'change: 0.06946805867436237', 'is_elite: False']\n", + "Id: 91_99 Identity: {'ancestor_count': 88, 'ancestor_ids': ['1_1', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_99', 'origin': '1_1~CUW~90_71#MGNP'} Metrics: ['ELUC: -2.4570757787945774', 'NSGA-II_crowding_distance: 0.18433331787586538', 'NSGA-II_rank: 4', 'change: 0.09817423384169661', 'is_elite: False']\n", + "Id: 91_16 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '90_36'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_16', 'origin': '89_33~CUW~90_36#MGNP'} Metrics: ['ELUC: -2.4583525540055473', 'NSGA-II_crowding_distance: 0.4493058420155457', 'NSGA-II_rank: 4', 'change: 0.11289370958466001', 'is_elite: False']\n", + "Id: 91_32 Identity: {'ancestor_count': 85, 'ancestor_ids': ['90_96', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_32', 'origin': '90_96~CUW~88_88#MGNP'} Metrics: ['ELUC: -2.5982095139005286', 'NSGA-II_crowding_distance: 0.1439797898526165', 'NSGA-II_rank: 2', 'change: 0.07999224754033644', 'is_elite: False']\n", + "Id: 91_78 Identity: {'ancestor_count': 88, 'ancestor_ids': ['1_1', '90_36'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_78', 'origin': '1_1~CUW~90_36#MGNP'} Metrics: ['ELUC: -2.6224097843264116', 'NSGA-II_crowding_distance: 0.17196064712610437', 'NSGA-II_rank: 1', 'change: 0.05321178582983602', 'is_elite: False']\n", + "Id: 91_75 Identity: {'ancestor_count': 88, 'ancestor_ids': ['1_1', '89_92'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_75', 'origin': '1_1~CUW~89_92#MGNP'} Metrics: ['ELUC: -3.2151817294306304', 'NSGA-II_crowding_distance: 0.22306350700901423', 'NSGA-II_rank: 3', 'change: 0.08661697025114301', 'is_elite: False']\n", + "Id: 91_26 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '90_96'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_26', 'origin': '90_46~CUW~90_96#MGNP'} Metrics: ['ELUC: -3.2747830192126193', 'NSGA-II_crowding_distance: 0.3530754377267385', 'NSGA-II_rank: 3', 'change: 0.08800373456757725', 'is_elite: False']\n", + "Id: 91_14 Identity: {'ancestor_count': 85, 'ancestor_ids': ['90_31', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_14', 'origin': '90_31~CUW~88_88#MGNP'} Metrics: ['ELUC: -3.3325451311633674', 'NSGA-II_crowding_distance: 0.6347449346497279', 'NSGA-II_rank: 2', 'change: 0.08577790656888269', 'is_elite: False']\n", + "Id: 90_96 Identity: {'ancestor_count': 84, 'ancestor_ids': ['86_83', '86_83'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_96', 'origin': '86_83~CUW~86_83#MGNP'} Metrics: ['ELUC: -3.788780802958937', 'NSGA-II_crowding_distance: 0.17421097913068395', 'NSGA-II_rank: 1', 'change: 0.05473324707588939', 'is_elite: False']\n", + "Id: 91_65 Identity: {'ancestor_count': 85, 'ancestor_ids': ['90_31', '90_100'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_65', 'origin': '90_31~CUW~90_100#MGNP'} Metrics: ['ELUC: -3.845671170556613', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.27299952646182324', 'is_elite: False']\n", + "Id: 91_23 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_92', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_23', 'origin': '89_92~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.107997912384128', 'NSGA-II_crowding_distance: 0.1283360058111348', 'NSGA-II_rank: 1', 'change: 0.07998157125787127', 'is_elite: False']\n", + "Id: 91_17 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_31', '89_92'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_17', 'origin': '90_31~CUW~89_92#MGNP'} Metrics: ['ELUC: -4.259212092628692', 'NSGA-II_crowding_distance: 0.26237478968499706', 'NSGA-II_rank: 1', 'change: 0.08504248720405806', 'is_elite: True']\n", + "Id: 91_66 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_92', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_66', 'origin': '89_92~CUW~90_71#MGNP'} Metrics: ['ELUC: -4.360039134177781', 'NSGA-II_crowding_distance: 0.6821059624205164', 'NSGA-II_rank: 5', 'change: 0.1586145048401623', 'is_elite: False']\n", + "Id: 91_46 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '89_92'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_46', 'origin': '90_71~CUW~89_92#MGNP'} Metrics: ['ELUC: -5.014054264679423', 'NSGA-II_crowding_distance: 0.5733500360434216', 'NSGA-II_rank: 5', 'change: 0.20319510960326695', 'is_elite: False']\n", + "Id: 91_97 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_97', 'origin': '89_33~CUW~90_71#MGNP'} Metrics: ['ELUC: -6.230802269270011', 'NSGA-II_crowding_distance: 0.4039120406569696', 'NSGA-II_rank: 4', 'change: 0.1431912600125457', 'is_elite: False']\n", + "Id: 91_67 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_34', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_67', 'origin': '90_34~CUW~88_88#MGNP'} Metrics: ['ELUC: -6.2799648499793', 'NSGA-II_crowding_distance: 0.5472581495464726', 'NSGA-II_rank: 3', 'change: 0.12943633065493937', 'is_elite: False']\n", + "Id: 91_94 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_94', 'origin': '88_79~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.333289538239416', 'NSGA-II_crowding_distance: 0.1437469476822062', 'NSGA-II_rank: 4', 'change: 0.14554004316650695', 'is_elite: False']\n", + "Id: 91_81 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_36', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_81', 'origin': '90_36~CUW~90_71#MGNP'} Metrics: ['ELUC: -6.5037231604238235', 'NSGA-II_crowding_distance: 0.2978831749804511', 'NSGA-II_rank: 4', 'change: 0.1727436809625857', 'is_elite: False']\n", + "Id: 91_55 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_55', 'origin': '90_71~CUW~88_88#MGNP'} Metrics: ['ELUC: -6.873931113894127', 'NSGA-II_crowding_distance: 1.5470865265147125', 'NSGA-II_rank: 6', 'change: 0.2219838884191516', 'is_elite: False']\n", + "Id: 90_46 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_17', '89_33'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_46', 'origin': '88_17~CUW~89_33#MGNP'} Metrics: ['ELUC: -7.40133983869486', 'NSGA-II_crowding_distance: 0.29643846072703983', 'NSGA-II_rank: 1', 'change: 0.10237933392156229', 'is_elite: True']\n", + "Id: 91_21 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_21', 'origin': '90_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.511831337915038', 'NSGA-II_crowding_distance: 0.4357768790415885', 'NSGA-II_rank: 5', 'change: 0.2198683815556519', 'is_elite: False']\n", + "Id: 91_91 Identity: {'ancestor_count': 86, 'ancestor_ids': ['90_17', '2_49'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_91', 'origin': '90_17~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.766854179845248', 'NSGA-II_crowding_distance: 0.6069221177541155', 'NSGA-II_rank: 6', 'change: 0.30343152260761674', 'is_elite: False']\n", + "Id: 91_98 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_98', 'origin': '89_33~CUW~90_71#MGNP'} Metrics: ['ELUC: -7.879288106026154', 'NSGA-II_crowding_distance: 0.44317138972545456', 'NSGA-II_rank: 4', 'change: 0.19088457100552986', 'is_elite: False']\n", + "Id: 91_73 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_73', 'origin': '90_46~CUW~89_33#MGNP'} Metrics: ['ELUC: -8.056977424401634', 'NSGA-II_crowding_distance: 0.25292983012558135', 'NSGA-II_rank: 1', 'change: 0.10904386953865561', 'is_elite: True']\n", + "Id: 91_22 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '88_39'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_22', 'origin': '88_79~CUW~88_39#MGNP'} Metrics: ['ELUC: -8.12258471233199', 'NSGA-II_crowding_distance: 0.36292837815424817', 'NSGA-II_rank: 5', 'change: 0.23722856903409092', 'is_elite: False']\n", + "Id: 91_60 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_100', '90_46'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_60', 'origin': '90_100~CUW~90_46#MGNP'} Metrics: ['ELUC: -9.020776195041007', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.3038962134903066', 'is_elite: False']\n", + "Id: 91_36 Identity: {'ancestor_count': 88, 'ancestor_ids': ['1_1', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_36', 'origin': '1_1~CUW~90_71#MGNP'} Metrics: ['ELUC: -9.423611466642502', 'NSGA-II_crowding_distance: 0.5063560500587091', 'NSGA-II_rank: 5', 'change: 0.2601047582422521', 'is_elite: False']\n", + "Id: 91_76 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '88_39'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_76', 'origin': '89_33~CUW~88_39#MGNP'} Metrics: ['ELUC: -9.567480353432957', 'NSGA-II_crowding_distance: 0.8619211679248524', 'NSGA-II_rank: 4', 'change: 0.2278217835372155', 'is_elite: False']\n", + "Id: 91_62 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_31', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_62', 'origin': '90_31~CUW~89_33#MGNP'} Metrics: ['ELUC: -9.577560251730905', 'NSGA-II_crowding_distance: 0.7657013464582353', 'NSGA-II_rank: 3', 'change: 0.13061543948226423', 'is_elite: False']\n", + "Id: 91_49 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_49', 'origin': '89_33~CUW~89_33#MGNP'} Metrics: ['ELUC: -9.836908173662684', 'NSGA-II_crowding_distance: 0.6115321381998214', 'NSGA-II_rank: 2', 'change: 0.12850341465780574', 'is_elite: False']\n", + "Id: 91_87 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_87', 'origin': '89_33~CUW~89_33#MGNP'} Metrics: ['ELUC: -10.373427107846275', 'NSGA-II_crowding_distance: 0.203776451089803', 'NSGA-II_rank: 1', 'change: 0.12741072167191855', 'is_elite: False']\n", + "Id: 91_42 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_42', 'origin': '89_33~CUW~89_33#MGNP'} Metrics: ['ELUC: -10.43015684856338', 'NSGA-II_crowding_distance: 0.199033074903502', 'NSGA-II_rank: 2', 'change: 0.1305414062037719', 'is_elite: False']\n", + "Id: 89_33 Identity: {'ancestor_count': 87, 'ancestor_ids': ['85_17', '88_79'], 'birth_generation': 89, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '89_33', 'origin': '85_17~CUW~88_79#MGNP'} Metrics: ['ELUC: -10.450862547553172', 'NSGA-II_crowding_distance: 0.04590303789680904', 'NSGA-II_rank: 1', 'change: 0.1292212529995411', 'is_elite: False']\n", + "Id: 91_20 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_20', 'origin': '89_33~CUW~89_33#MGNP'} Metrics: ['ELUC: -10.809913272234352', 'NSGA-II_crowding_distance: 0.10068471316458419', 'NSGA-II_rank: 1', 'change: 0.1336998604816719', 'is_elite: False']\n", + "Id: 91_88 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '90_100'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_88', 'origin': '88_39~CUW~90_100#MGNP'} Metrics: ['ELUC: -10.871915377230003', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.29192555737424997', 'is_elite: False']\n", + "Id: 91_63 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '90_36'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_63', 'origin': '90_46~CUW~90_36#MGNP'} Metrics: ['ELUC: -11.3383956790324', 'NSGA-II_crowding_distance: 0.2788496251264039', 'NSGA-II_rank: 2', 'change: 0.1559794144904778', 'is_elite: False']\n", + "Id: 91_41 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_79', '90_36'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_41', 'origin': '88_79~CUW~90_36#MGNP'} Metrics: ['ELUC: -11.352615553633612', 'NSGA-II_crowding_distance: 0.08942419631534704', 'NSGA-II_rank: 1', 'change: 0.14396030118140854', 'is_elite: False']\n", + "Id: 91_30 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '88_39'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_30', 'origin': '88_79~CUW~88_39#MGNP'} Metrics: ['ELUC: -11.522917468959147', 'NSGA-II_crowding_distance: 0.7668021371290148', 'NSGA-II_rank: 3', 'change: 0.24377545687085758', 'is_elite: False']\n", + "Id: 91_72 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '90_36'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_72', 'origin': '89_33~CUW~90_36#MGNP'} Metrics: ['ELUC: -11.546619881149038', 'NSGA-II_crowding_distance: 0.12564633611534856', 'NSGA-II_rank: 1', 'change: 0.14787990960530217', 'is_elite: False']\n", + "Id: 91_19 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '90_17'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_19', 'origin': '88_79~CUW~90_17#MGNP'} Metrics: ['ELUC: -12.35824584058461', 'NSGA-II_crowding_distance: 0.22376378695790852', 'NSGA-II_rank: 2', 'change: 0.17183785541766902', 'is_elite: False']\n", + "Id: 88_79 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_85', '86_15'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_79', 'origin': '87_85~CUW~86_15#MGNP'} Metrics: ['ELUC: -12.48983153313787', 'NSGA-II_crowding_distance: 0.11758764746009231', 'NSGA-II_rank: 1', 'change: 0.16215146214524234', 'is_elite: False']\n", + "Id: 91_89 Identity: {'ancestor_count': 87, 'ancestor_ids': ['90_25', '88_79'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_89', 'origin': '90_25~CUW~88_79#MGNP'} Metrics: ['ELUC: -12.605451941949042', 'NSGA-II_crowding_distance: 0.34211308106645666', 'NSGA-II_rank: 2', 'change: 0.1935899006061941', 'is_elite: False']\n", + "Id: 91_80 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_79', '88_79'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_80', 'origin': '88_79~CUW~88_79#MGNP'} Metrics: ['ELUC: -12.627918971639424', 'NSGA-II_crowding_distance: 0.1977204442485864', 'NSGA-II_rank: 1', 'change: 0.16461546430569102', 'is_elite: False']\n", + "Id: 91_40 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_24', '88_39'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_40', 'origin': '90_24~CUW~88_39#MGNP'} Metrics: ['ELUC: -13.38201982270813', 'NSGA-II_crowding_distance: 0.3202806943817861', 'NSGA-II_rank: 2', 'change: 0.24392194719892588', 'is_elite: False']\n", + "Id: 91_38 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_24', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_38', 'origin': '90_24~CUW~89_33#MGNP'} Metrics: ['ELUC: -13.44985255868881', 'NSGA-II_crowding_distance: 0.2366776481202505', 'NSGA-II_rank: 1', 'change: 0.20485498373370215', 'is_elite: True']\n", + "Id: 91_83 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '90_25'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_83', 'origin': '90_71~CUW~90_25#MGNP'} Metrics: ['ELUC: -13.980478310262543', 'NSGA-II_crowding_distance: 0.1415731804232718', 'NSGA-II_rank: 1', 'change: 0.2122814512032139', 'is_elite: False']\n", + "Id: 91_61 Identity: {'ancestor_count': 88, 'ancestor_ids': ['2_49', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_61', 'origin': '2_49~CUW~90_71#MGNP'} Metrics: ['ELUC: -14.435377927490592', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28831954742504934', 'is_elite: False']\n", + "Id: 90_71 Identity: {'ancestor_count': 87, 'ancestor_ids': ['86_83', '88_39'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_71', 'origin': '86_83~CUW~88_39#MGNP'} Metrics: ['ELUC: -14.608341521601725', 'NSGA-II_crowding_distance: 0.4087575214302089', 'NSGA-II_rank: 3', 'change: 0.24848118149412177', 'is_elite: False']\n", + "Id: 91_15 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_15', 'origin': '90_71~CUW~90_71#MGNP'} Metrics: ['ELUC: -14.612286165641295', 'NSGA-II_crowding_distance: 0.14776506804244652', 'NSGA-II_rank: 2', 'change: 0.24433811413423373', 'is_elite: False']\n", + "Id: 91_24 Identity: {'ancestor_count': 87, 'ancestor_ids': ['90_100', '88_79'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_24', 'origin': '90_100~CUW~88_79#MGNP'} Metrics: ['ELUC: -14.78642739795622', 'NSGA-II_crowding_distance: 0.2760785145968378', 'NSGA-II_rank: 3', 'change: 0.29770308064746676', 'is_elite: False']\n", + "Id: 91_13 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '90_71'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_13', 'origin': '90_71~CUW~90_71#MGNP'} Metrics: ['ELUC: -14.791491969947005', 'NSGA-II_crowding_distance: 0.17503803844745763', 'NSGA-II_rank: 2', 'change: 0.2596154388764234', 'is_elite: False']\n", + "Id: 91_47 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '88_79'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_47', 'origin': '88_39~CUW~88_79#MGNP'} Metrics: ['ELUC: -14.814924376656817', 'NSGA-II_crowding_distance: 0.297312155118301', 'NSGA-II_rank: 1', 'change: 0.22393157630273408', 'is_elite: True']\n", + "Id: 91_71 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_100', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_71', 'origin': '90_100~CUW~89_33#MGNP'} Metrics: ['ELUC: -15.614940372846736', 'NSGA-II_crowding_distance: 0.16029484671309818', 'NSGA-II_rank: 2', 'change: 0.2735750427144297', 'is_elite: False']\n", + "Id: 91_92 Identity: {'ancestor_count': 89, 'ancestor_ids': ['2_49', '90_46'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_92', 'origin': '2_49~CUW~90_46#MGNP'} Metrics: ['ELUC: -15.924725685457982', 'NSGA-II_crowding_distance: 0.1398234402982274', 'NSGA-II_rank: 3', 'change: 0.2984908383497933', 'is_elite: False']\n", + "Id: 91_58 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '90_25'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_58', 'origin': '90_71~CUW~90_25#MGNP'} Metrics: ['ELUC: -16.249426891716848', 'NSGA-II_crowding_distance: 0.25942477274869713', 'NSGA-II_rank: 1', 'change: 0.26248801585839765', 'is_elite: True']\n", + "Id: 91_33 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_24', '88_39'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_33', 'origin': '90_24~CUW~88_39#MGNP'} Metrics: ['ELUC: -16.437949441751275', 'NSGA-II_crowding_distance: 0.18607258207329946', 'NSGA-II_rank: 2', 'change: 0.274764484830993', 'is_elite: False']\n", + "Id: 88_39 Identity: {'ancestor_count': 86, 'ancestor_ids': ['87_27', '87_85'], 'birth_generation': 88, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '88_39', 'origin': '87_27~CUW~87_85#MGNP'} Metrics: ['ELUC: -16.538662252728123', 'NSGA-II_crowding_distance: 0.17821697154167054', 'NSGA-II_rank: 1', 'change: 0.27208578408966216', 'is_elite: False']\n", + "Id: 91_68 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_68', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.890102746594625', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30104082037815505', 'is_elite: False']\n", + "Id: 91_64 Identity: {'ancestor_count': 85, 'ancestor_ids': ['90_96', '90_100'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_64', 'origin': '90_96~CUW~90_100#MGNP'} Metrics: ['ELUC: -17.042334637116532', 'NSGA-II_crowding_distance: 0.17608635966426114', 'NSGA-II_rank: 2', 'change: 0.2988838783550948', 'is_elite: False']\n", + "Id: 91_50 Identity: {'ancestor_count': 87, 'ancestor_ids': ['2_49', '88_79'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_50', 'origin': '2_49~CUW~88_79#MGNP'} Metrics: ['ELUC: -17.286631078263223', 'NSGA-II_crowding_distance: 0.141385428640234', 'NSGA-II_rank: 1', 'change: 0.2980623138107755', 'is_elite: False']\n", + "Id: 91_48 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_100', '90_24'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_48', 'origin': '90_100~CUW~90_24#MGNP'} Metrics: ['ELUC: -17.36914709236018', 'NSGA-II_crowding_distance: 0.02135156492089803', 'NSGA-II_rank: 1', 'change: 0.3001784614756768', 'is_elite: False']\n", + "Id: 91_90 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_100', '89_92'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_90', 'origin': '90_100~CUW~89_92#MGNP'} Metrics: ['ELUC: -17.454030698369476', 'NSGA-II_crowding_distance: 0.022112135824298596', 'NSGA-II_rank: 1', 'change: 0.30159232180977286', 'is_elite: False']\n", + "Id: 91_69 Identity: {'ancestor_count': 85, 'ancestor_ids': ['2_49', '88_88'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_69', 'origin': '2_49~CUW~88_88#MGNP'} Metrics: ['ELUC: -17.5139020393717', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3031022972834587', 'is_elite: False']\n", + "Id: 91_56 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_65', '90_100'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_56', 'origin': '90_65~CUW~90_100#MGNP'} Metrics: ['ELUC: -17.594800678124397', 'NSGA-II_crowding_distance: 0.01293976730913873', 'NSGA-II_rank: 1', 'change: 0.30294681913323485', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 90_100 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_100', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 91_27 Identity: {'ancestor_count': 3, 'ancestor_ids': ['90_100', '2_49'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_27', 'origin': '90_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 91_31 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '2_49'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_31', 'origin': '89_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 91_79 Identity: {'ancestor_count': 3, 'ancestor_ids': ['90_100', '2_49'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_79', 'origin': '90_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 91_85 Identity: {'ancestor_count': 88, 'ancestor_ids': ['89_33', '90_100'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_85', 'origin': '89_33~CUW~90_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 91_100 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '2_49'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_100', 'origin': '88_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 91.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 92...:\n", + "PopulationResponse:\n", + " Generation: 92\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/92/20240220-064611\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 92 and asking ESP for generation 93...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 92 data persisted.\n", + "Evaluated candidates:\n", + "Id: 92_47 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_50', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_47', 'origin': '91_50~CUW~91_70#MGNP'} Metrics: ['ELUC: 23.406451926251183', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.30106232720218323', 'is_elite: False']\n", + "Id: 92_70 Identity: {'ancestor_count': 89, 'ancestor_ids': ['2_49', '91_87'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_70', 'origin': '2_49~CUW~91_87#MGNP'} Metrics: ['ELUC: 21.800955277056886', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.30222955591780787', 'is_elite: False']\n", + "Id: 92_25 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_47', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_25', 'origin': '91_47~CUW~1_1#MGNP'} Metrics: ['ELUC: 17.826637356065497', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2470121326199706', 'is_elite: False']\n", + "Id: 92_13 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_80', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_13', 'origin': '91_80~CUW~1_1#MGNP'} Metrics: ['ELUC: 5.137473022857198', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.13359212059341538', 'is_elite: False']\n", + "Id: 92_77 Identity: {'ancestor_count': 87, 'ancestor_ids': ['91_70', '88_39'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_77', 'origin': '91_70~CUW~88_39#MGNP'} Metrics: ['ELUC: 3.7848391322020665', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3083873218879096', 'is_elite: False']\n", + "Id: 92_75 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_100', '91_23'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_75', 'origin': '91_100~CUW~91_23#MGNP'} Metrics: ['ELUC: 2.5698339720869674', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2566130472979577', 'is_elite: False']\n", + "Id: 92_64 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_64', 'origin': '91_58~CUW~91_17#MGNP'} Metrics: ['ELUC: 1.4713098495805914', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.17290101621209267', 'is_elite: False']\n", + "Id: 92_66 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_66', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.374817988781355', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03251281706371109', 'is_elite: False']\n", + "Id: 92_55 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_55', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.1466621719212584', 'NSGA-II_crowding_distance: 0.1024563361770296', 'NSGA-II_rank: 3', 'change: 0.04299502401405043', 'is_elite: False']\n", + "Id: 92_76 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_76', 'origin': '90_46~CUW~91_47#MGNP'} Metrics: ['ELUC: 1.0363190088858065', 'NSGA-II_crowding_distance: 0.7064108048586853', 'NSGA-II_rank: 5', 'change: 0.15487018572266834', 'is_elite: False']\n", + "Id: 92_89 Identity: {'ancestor_count': 86, 'ancestor_ids': ['91_70', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_89', 'origin': '91_70~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.8793515855721808', 'NSGA-II_crowding_distance: 0.13706110706389257', 'NSGA-II_rank: 3', 'change: 0.050379954694927336', 'is_elite: False']\n", + "Id: 92_44 Identity: {'ancestor_count': 88, 'ancestor_ids': ['2_49', '91_80'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_44', 'origin': '2_49~CUW~91_80#MGNP'} Metrics: ['ELUC: 0.32566057690747535', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23874692099952924', 'is_elite: False']\n", + "Id: 92_68 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_68', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.11813081111160029', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03114828850607855', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 92_71 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_71', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.22913993621062675', 'NSGA-II_crowding_distance: 0.21054752424229822', 'NSGA-II_rank: 1', 'change: 0.02478794634506252', 'is_elite: True']\n", + "Id: 92_81 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_23', '91_87'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_81', 'origin': '91_23~CUW~91_87#MGNP'} Metrics: ['ELUC: -0.3658414020511772', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.11731579479087467', 'is_elite: False']\n", + "Id: 92_38 Identity: {'ancestor_count': 86, 'ancestor_ids': ['1_1', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_38', 'origin': '1_1~CUW~91_70#MGNP'} Metrics: ['ELUC: -0.4478537181617632', 'NSGA-II_crowding_distance: 0.23333144880310885', 'NSGA-II_rank: 3', 'change: 0.05139069632304427', 'is_elite: False']\n", + "Id: 92_37 Identity: {'ancestor_count': 86, 'ancestor_ids': ['91_70', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_37', 'origin': '91_70~CUW~91_70#MGNP'} Metrics: ['ELUC: -0.5070647186439362', 'NSGA-II_crowding_distance: 0.1709234119293881', 'NSGA-II_rank: 2', 'change: 0.041998490397838206', 'is_elite: False']\n", + "Id: 92_51 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_17', '2_49'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_51', 'origin': '91_17~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.7024971962512263', 'NSGA-II_crowding_distance: 1.1049696040034802', 'NSGA-II_rank: 9', 'change: 0.239646313774104', 'is_elite: False']\n", + "Id: 92_43 Identity: {'ancestor_count': 88, 'ancestor_ids': ['1_1', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_43', 'origin': '1_1~CUW~91_47#MGNP'} Metrics: ['ELUC: -0.8274658565282196', 'NSGA-II_crowding_distance: 0.9308365407364823', 'NSGA-II_rank: 6', 'change: 0.17743517072524534', 'is_elite: False']\n", + "Id: 92_19 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_17', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_19', 'origin': '91_17~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.9896309400118659', 'NSGA-II_crowding_distance: 0.4316263641331012', 'NSGA-II_rank: 3', 'change: 0.0787441796188092', 'is_elite: False']\n", + "Id: 92_74 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_70', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_74', 'origin': '91_70~CUW~91_17#MGNP'} Metrics: ['ELUC: -1.4583906081423605', 'NSGA-II_crowding_distance: 0.20596214378735825', 'NSGA-II_rank: 2', 'change: 0.05339453639391141', 'is_elite: False']\n", + "Id: 91_70 Identity: {'ancestor_count': 85, 'ancestor_ids': ['90_96', '1_1'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_70', 'origin': '90_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.6637054409234922', 'NSGA-II_crowding_distance: 0.1800379593354565', 'NSGA-II_rank: 1', 'change: 0.03948720599796149', 'is_elite: False']\n", + "Id: 92_49 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_70', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_49', 'origin': '91_70~CUW~91_17#MGNP'} Metrics: ['ELUC: -1.721221426259055', 'NSGA-II_crowding_distance: 0.21969136630200498', 'NSGA-II_rank: 1', 'change: 0.053186178454265536', 'is_elite: True']\n", + "Id: 92_35 Identity: {'ancestor_count': 90, 'ancestor_ids': ['1_1', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_35', 'origin': '1_1~CUW~91_73#MGNP'} Metrics: ['ELUC: -1.850172185999919', 'NSGA-II_crowding_distance: 0.20478793014182037', 'NSGA-II_rank: 2', 'change: 0.07735279859288555', 'is_elite: False']\n", + "Id: 92_27 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_27', 'origin': '2_49~CUW~91_70#MGNP'} Metrics: ['ELUC: -2.0223839794781613', 'NSGA-II_crowding_distance: 1.6443870928381572', 'NSGA-II_rank: 9', 'change: 0.2489024112285754', 'is_elite: False']\n", + "Id: 92_65 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_73', '91_78'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_65', 'origin': '91_73~CUW~91_78#MGNP'} Metrics: ['ELUC: -2.8406607618524844', 'NSGA-II_crowding_distance: 0.24983036160121125', 'NSGA-II_rank: 2', 'change: 0.08782827129267624', 'is_elite: False']\n", + "Id: 92_34 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_100', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_34', 'origin': '91_100~CUW~91_17#MGNP'} Metrics: ['ELUC: -2.8564767915203193', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2664120160258213', 'is_elite: False']\n", + "Id: 92_20 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '91_83'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_20', 'origin': '90_46~CUW~91_83#MGNP'} Metrics: ['ELUC: -3.26472492352399', 'NSGA-II_crowding_distance: 0.747733615663568', 'NSGA-II_rank: 5', 'change: 0.16039922257527783', 'is_elite: False']\n", + "Id: 92_73 Identity: {'ancestor_count': 89, 'ancestor_ids': ['1_1', '90_46'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_73', 'origin': '1_1~CUW~90_46#MGNP'} Metrics: ['ELUC: -3.344015810782628', 'NSGA-II_crowding_distance: 0.23071864115501842', 'NSGA-II_rank: 1', 'change: 0.07652282894846213', 'is_elite: True']\n", + "Id: 92_22 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_17', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_22', 'origin': '91_17~CUW~91_47#MGNP'} Metrics: ['ELUC: -3.6123411105914363', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.18411543190878657', 'is_elite: False']\n", + "Id: 92_79 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_79', 'origin': '90_46~CUW~91_70#MGNP'} Metrics: ['ELUC: -3.773633957471076', 'NSGA-II_crowding_distance: 0.5572818604618506', 'NSGA-II_rank: 3', 'change: 0.1060492640453846', 'is_elite: False']\n", + "Id: 92_96 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_47', '91_87'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_96', 'origin': '91_47~CUW~91_87#MGNP'} Metrics: ['ELUC: -3.818691890951441', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2221696295448083', 'is_elite: False']\n", + "Id: 92_21 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_78', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_21', 'origin': '91_78~CUW~91_73#MGNP'} Metrics: ['ELUC: -3.9253681969509624', 'NSGA-II_crowding_distance: 0.08060528663523418', 'NSGA-II_rank: 1', 'change: 0.08462242931950502', 'is_elite: False']\n", + "Id: 92_17 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '90_96'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_17', 'origin': '88_39~CUW~90_96#MGNP'} Metrics: ['ELUC: -3.9885427922310104', 'NSGA-II_crowding_distance: 0.5275217033352636', 'NSGA-II_rank: 4', 'change: 0.1313660100153653', 'is_elite: False']\n", + "Id: 91_17 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_31', '89_92'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_17', 'origin': '90_31~CUW~89_92#MGNP'} Metrics: ['ELUC: -4.259212092628692', 'NSGA-II_crowding_distance: 0.09542922589484443', 'NSGA-II_rank: 1', 'change: 0.08504248720405806', 'is_elite: False']\n", + "Id: 92_100 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_38', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_100', 'origin': '91_38~CUW~91_47#MGNP'} Metrics: ['ELUC: -4.561785361640639', 'NSGA-II_crowding_distance: 1.5434657508164729', 'NSGA-II_rank: 7', 'change: 0.20411521850227665', 'is_elite: False']\n", + "Id: 92_11 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_78', '91_87'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_11', 'origin': '91_78~CUW~91_87#MGNP'} Metrics: ['ELUC: -4.752320387378157', 'NSGA-II_crowding_distance: 0.3626223048986001', 'NSGA-II_rank: 2', 'change: 0.10068824487259269', 'is_elite: False']\n", + "Id: 92_60 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_83', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_60', 'origin': '91_83~CUW~91_17#MGNP'} Metrics: ['ELUC: -4.877449531063331', 'NSGA-II_crowding_distance: 0.8449218056173871', 'NSGA-II_rank: 4', 'change: 0.13389485694057637', 'is_elite: False']\n", + "Id: 92_57 Identity: {'ancestor_count': 89, 'ancestor_ids': ['1_1', '90_46'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_57', 'origin': '1_1~CUW~90_46#MGNP'} Metrics: ['ELUC: -5.409866066540391', 'NSGA-II_crowding_distance: 0.1099712822853369', 'NSGA-II_rank: 1', 'change: 0.08790399730493949', 'is_elite: False']\n", + "Id: 92_91 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_80', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_91', 'origin': '91_80~CUW~91_73#MGNP'} Metrics: ['ELUC: -5.512029350153876', 'NSGA-II_crowding_distance: 0.1617790401663333', 'NSGA-II_rank: 1', 'change: 0.09659477212081155', 'is_elite: False']\n", + "Id: 92_78 Identity: {'ancestor_count': 86, 'ancestor_ids': ['91_100', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_78', 'origin': '91_100~CUW~91_70#MGNP'} Metrics: ['ELUC: -6.444358821936835', 'NSGA-II_crowding_distance: 1.4996142160904327', 'NSGA-II_rank: 7', 'change: 0.24754971941515008', 'is_elite: False']\n", + "Id: 92_72 Identity: {'ancestor_count': 88, 'ancestor_ids': ['1_1', '91_50'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_72', 'origin': '1_1~CUW~91_50#MGNP'} Metrics: ['ELUC: -6.8332749017480365', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2604984209482044', 'is_elite: False']\n", + "Id: 92_30 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_83', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_30', 'origin': '91_83~CUW~91_70#MGNP'} Metrics: ['ELUC: -7.214455415984354', 'NSGA-II_crowding_distance: 1.7289253253288288', 'NSGA-II_rank: 6', 'change: 0.18294415620631693', 'is_elite: False']\n", + "Id: 90_46 Identity: {'ancestor_count': 88, 'ancestor_ids': ['88_17', '89_33'], 'birth_generation': 90, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '90_46', 'origin': '88_17~CUW~89_33#MGNP'} Metrics: ['ELUC: -7.40133983869486', 'NSGA-II_crowding_distance: 0.1864671784417029', 'NSGA-II_rank: 1', 'change: 0.10237933392156229', 'is_elite: False']\n", + "Id: 92_45 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_73', '90_46'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_45', 'origin': '91_73~CUW~90_46#MGNP'} Metrics: ['ELUC: -7.526152226124753', 'NSGA-II_crowding_distance: 0.5645030475756636', 'NSGA-II_rank: 3', 'change: 0.1119930703509357', 'is_elite: False']\n", + "Id: 92_85 Identity: {'ancestor_count': 89, 'ancestor_ids': ['2_49', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_85', 'origin': '2_49~CUW~91_17#MGNP'} Metrics: ['ELUC: -7.528816659263761', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.28299617639528135', 'is_elite: False']\n", + "Id: 92_26 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_47', '2_49'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_26', 'origin': '91_47~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.723556094226726', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2583410926213564', 'is_elite: False']\n", + "Id: 92_61 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_17', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_61', 'origin': '91_17~CUW~91_73#MGNP'} Metrics: ['ELUC: -7.802490575023233', 'NSGA-II_crowding_distance: 0.5137194877887443', 'NSGA-II_rank: 2', 'change: 0.11018994710375174', 'is_elite: False']\n", + "Id: 91_73 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_73', 'origin': '90_46~CUW~89_33#MGNP'} Metrics: ['ELUC: -8.056977424401634', 'NSGA-II_crowding_distance: 0.11754146707480825', 'NSGA-II_rank: 1', 'change: 0.10904386953865561', 'is_elite: False']\n", + "Id: 92_80 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_80', 'origin': '91_58~CUW~91_70#MGNP'} Metrics: ['ELUC: -8.059647018282948', 'NSGA-II_crowding_distance: 0.8121807425648415', 'NSGA-II_rank: 5', 'change: 0.18115555585222376', 'is_elite: False']\n", + "Id: 92_97 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_73', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_97', 'origin': '91_73~CUW~91_73#MGNP'} Metrics: ['ELUC: -8.539552537695469', 'NSGA-II_crowding_distance: 0.20444879258459664', 'NSGA-II_rank: 1', 'change: 0.118135267948779', 'is_elite: True']\n", + "Id: 92_56 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_50', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_56', 'origin': '91_50~CUW~91_70#MGNP'} Metrics: ['ELUC: -8.704520228031479', 'NSGA-II_crowding_distance: 0.4975516095682778', 'NSGA-II_rank: 5', 'change: 0.234826905294783', 'is_elite: False']\n", + "Id: 92_58 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '91_100'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_58', 'origin': '88_39~CUW~91_100#MGNP'} Metrics: ['ELUC: -9.406137404758022', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2487984409734588', 'is_elite: False']\n", + "Id: 92_16 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_73', '91_80'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_16', 'origin': '91_73~CUW~91_80#MGNP'} Metrics: ['ELUC: -9.91377320171743', 'NSGA-II_crowding_distance: 1.242078400824406', 'NSGA-II_rank: 4', 'change: 0.1702131659363943', 'is_elite: False']\n", + "Id: 92_92 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_72', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_92', 'origin': '91_72~CUW~91_47#MGNP'} Metrics: ['ELUC: -9.967331868867861', 'NSGA-II_crowding_distance: 0.4981834022606742', 'NSGA-II_rank: 3', 'change: 0.14684413635779878', 'is_elite: False']\n", + "Id: 92_99 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '91_100'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_99', 'origin': '90_46~CUW~91_100#MGNP'} Metrics: ['ELUC: -10.133346437545717', 'NSGA-II_crowding_distance: 0.17132576709946346', 'NSGA-II_rank: 5', 'change: 0.2397569195742568', 'is_elite: False']\n", + "Id: 92_48 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_80', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_48', 'origin': '91_80~CUW~91_70#MGNP'} Metrics: ['ELUC: -10.285536535788292', 'NSGA-II_crowding_distance: 0.26247222188700137', 'NSGA-II_rank: 3', 'change: 0.19304140901610592', 'is_elite: False']\n", + "Id: 92_24 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_47', '91_83'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_24', 'origin': '91_47~CUW~91_83#MGNP'} Metrics: ['ELUC: -10.360572093765672', 'NSGA-II_crowding_distance: 0.3589717029636247', 'NSGA-II_rank: 5', 'change: 0.245272589124514', 'is_elite: False']\n", + "Id: 92_87 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_47', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_87', 'origin': '91_47~CUW~91_38#MGNP'} Metrics: ['ELUC: -10.4153966302211', 'NSGA-II_crowding_distance: 0.25024712874623367', 'NSGA-II_rank: 3', 'change: 0.20628342391829513', 'is_elite: False']\n", + "Id: 92_23 Identity: {'ancestor_count': 88, 'ancestor_ids': ['2_49', '91_80'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_23', 'origin': '2_49~CUW~91_80#MGNP'} Metrics: ['ELUC: -10.42953750472059', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2944344389419864', 'is_elite: False']\n", + "Id: 92_14 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_87', '91_87'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_14', 'origin': '91_87~CUW~91_87#MGNP'} Metrics: ['ELUC: -10.522260905656585', 'NSGA-II_crowding_distance: 0.23380647962877757', 'NSGA-II_rank: 1', 'change: 0.12821021257834295', 'is_elite: True']\n", + "Id: 92_84 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_58', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_84', 'origin': '91_58~CUW~91_73#MGNP'} Metrics: ['ELUC: -10.701448566129985', 'NSGA-II_crowding_distance: 0.5458670333571202', 'NSGA-II_rank: 4', 'change: 0.21827635948005977', 'is_elite: False']\n", + "Id: 92_29 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_47', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_29', 'origin': '91_47~CUW~91_38#MGNP'} Metrics: ['ELUC: -10.807692370296907', 'NSGA-II_crowding_distance: 0.23039989584033063', 'NSGA-II_rank: 4', 'change: 0.22303571720332557', 'is_elite: False']\n", + "Id: 92_93 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_70', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_93', 'origin': '91_70~CUW~91_38#MGNP'} Metrics: ['ELUC: -10.904000124066572', 'NSGA-II_crowding_distance: 0.35758040147433656', 'NSGA-II_rank: 2', 'change: 0.14584553017071702', 'is_elite: False']\n", + "Id: 92_62 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '90_46'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_62', 'origin': '91_58~CUW~90_46#MGNP'} Metrics: ['ELUC: -11.012287472288689', 'NSGA-II_crowding_distance: 0.2719335669796597', 'NSGA-II_rank: 2', 'change: 0.15808725067508808', 'is_elite: False']\n", + "Id: 92_59 Identity: {'ancestor_count': 90, 'ancestor_ids': ['90_46', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_59', 'origin': '90_46~CUW~91_38#MGNP'} Metrics: ['ELUC: -11.172578558551619', 'NSGA-II_crowding_distance: 0.3524229129279779', 'NSGA-II_rank: 1', 'change: 0.1432146479580922', 'is_elite: True']\n", + "Id: 92_88 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_88', 'origin': '88_39~CUW~91_70#MGNP'} Metrics: ['ELUC: -12.24430937125371', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.22955814167249913', 'is_elite: False']\n", + "Id: 92_50 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_70', '91_58'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_50', 'origin': '91_70~CUW~91_58#MGNP'} Metrics: ['ELUC: -12.66224950096009', 'NSGA-II_crowding_distance: 0.5483112855705754', 'NSGA-II_rank: 3', 'change: 0.21726691298867387', 'is_elite: False']\n", + "Id: 92_90 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_17', '91_80'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_90', 'origin': '91_17~CUW~91_80#MGNP'} Metrics: ['ELUC: -12.95906196170855', 'NSGA-II_crowding_distance: 0.5054209994007743', 'NSGA-II_rank: 2', 'change: 0.18819734813965297', 'is_elite: False']\n", + "Id: 92_33 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_50', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_33', 'origin': '91_50~CUW~91_73#MGNP'} Metrics: ['ELUC: -13.24999093352758', 'NSGA-II_crowding_distance: 0.37664522157193014', 'NSGA-II_rank: 2', 'change: 0.26109604592812446', 'is_elite: False']\n", + "Id: 92_98 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_98', 'origin': '91_58~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.285454998453153', 'NSGA-II_crowding_distance: 0.27879060106500575', 'NSGA-II_rank: 1', 'change: 0.18647310054808064', 'is_elite: True']\n", + "Id: 92_94 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_73', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_94', 'origin': '91_73~CUW~91_38#MGNP'} Metrics: ['ELUC: -13.419907988900711', 'NSGA-II_crowding_distance: 0.07095623910574755', 'NSGA-II_rank: 1', 'change: 0.1882616773048043', 'is_elite: False']\n", + "Id: 91_38 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_24', '89_33'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_38', 'origin': '90_24~CUW~89_33#MGNP'} Metrics: ['ELUC: -13.44985255868881', 'NSGA-II_crowding_distance: 0.09326029162863432', 'NSGA-II_rank: 1', 'change: 0.20485498373370215', 'is_elite: False']\n", + "Id: 92_41 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '91_70'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_41', 'origin': '2_49~CUW~91_70#MGNP'} Metrics: ['ELUC: -13.939378375031236', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2873828693012325', 'is_elite: False']\n", + "Id: 92_15 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_80', '91_58'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_15', 'origin': '91_80~CUW~91_58#MGNP'} Metrics: ['ELUC: -13.973039018309786', 'NSGA-II_crowding_distance: 0.11225147318894957', 'NSGA-II_rank: 1', 'change: 0.20670166593642922', 'is_elite: False']\n", + "Id: 92_53 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_47', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_53', 'origin': '91_47~CUW~91_47#MGNP'} Metrics: ['ELUC: -14.737552916405113', 'NSGA-II_crowding_distance: 0.10562774235903394', 'NSGA-II_rank: 1', 'change: 0.2164956498405163', 'is_elite: False']\n", + "Id: 91_47 Identity: {'ancestor_count': 87, 'ancestor_ids': ['88_39', '88_79'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_47', 'origin': '88_39~CUW~88_79#MGNP'} Metrics: ['ELUC: -14.814924376656817', 'NSGA-II_crowding_distance: 0.173920979025807', 'NSGA-II_rank: 1', 'change: 0.22393157630273408', 'is_elite: False']\n", + "Id: 92_39 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_50', '91_87'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_39', 'origin': '91_50~CUW~91_87#MGNP'} Metrics: ['ELUC: -14.829955105375275', 'NSGA-II_crowding_distance: 0.23209234340269486', 'NSGA-II_rank: 2', 'change: 0.26183804382376075', 'is_elite: False']\n", + "Id: 92_63 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_100', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_63', 'origin': '91_100~CUW~91_17#MGNP'} Metrics: ['ELUC: -15.739825696017775', 'NSGA-II_crowding_distance: 0.2217617506954601', 'NSGA-II_rank: 2', 'change: 0.2859422128403845', 'is_elite: False']\n", + "Id: 92_83 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_83', 'origin': '91_58~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.852223634908047', 'NSGA-II_crowding_distance: 0.18265649858919109', 'NSGA-II_rank: 1', 'change: 0.2494734884450517', 'is_elite: False']\n", + "Id: 92_86 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '91_58'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_86', 'origin': '91_58~CUW~91_58#MGNP'} Metrics: ['ELUC: -16.025511580210615', 'NSGA-II_crowding_distance: 0.06620866148863666', 'NSGA-II_rank: 1', 'change: 0.25788816695876166', 'is_elite: False']\n", + "Id: 91_58 Identity: {'ancestor_count': 88, 'ancestor_ids': ['90_71', '90_25'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_58', 'origin': '90_71~CUW~90_25#MGNP'} Metrics: ['ELUC: -16.249426891716848', 'NSGA-II_crowding_distance: 0.15600311646940718', 'NSGA-II_rank: 1', 'change: 0.26248801585839765', 'is_elite: False']\n", + "Id: 92_69 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_100', '91_58'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_69', 'origin': '91_100~CUW~91_58#MGNP'} Metrics: ['ELUC: -16.526203082993522', 'NSGA-II_crowding_distance: 0.1354307438621537', 'NSGA-II_rank: 2', 'change: 0.2960634920359967', 'is_elite: False']\n", + "Id: 92_54 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_100', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_54', 'origin': '91_100~CUW~91_47#MGNP'} Metrics: ['ELUC: -17.040644491325693', 'NSGA-II_crowding_distance: 0.17581531670401557', 'NSGA-II_rank: 1', 'change: 0.28720890195299575', 'is_elite: False']\n", + "Id: 92_12 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_100', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_12', 'origin': '91_100~CUW~91_17#MGNP'} Metrics: ['ELUC: -17.10602547998962', 'NSGA-II_crowding_distance: 0.08414797011235735', 'NSGA-II_rank: 2', 'change: 0.30177147976958524', 'is_elite: False']\n", + "Id: 92_32 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_47', '88_39'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_32', 'origin': '91_47~CUW~88_39#MGNP'} Metrics: ['ELUC: -17.35636513696772', 'NSGA-II_crowding_distance: 0.08410155823743096', 'NSGA-II_rank: 1', 'change: 0.2961623050635942', 'is_elite: False']\n", + "Id: 92_52 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_38', '91_100'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_52', 'origin': '91_38~CUW~91_100#MGNP'} Metrics: ['ELUC: -17.567352209675693', 'NSGA-II_crowding_distance: 0.03114186489023196', 'NSGA-II_rank: 2', 'change: 0.3029459289334501', 'is_elite: False']\n", + "Id: 92_67 Identity: {'ancestor_count': 89, 'ancestor_ids': ['2_49', '91_58'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_67', 'origin': '2_49~CUW~91_58#MGNP'} Metrics: ['ELUC: -17.580587398962475', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30294796883972785', 'is_elite: False']\n", + "Id: 92_42 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_100', '91_80'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_42', 'origin': '91_100~CUW~91_80#MGNP'} Metrics: ['ELUC: -17.59372623914126', 'NSGA-II_crowding_distance: 0.03669298706769175', 'NSGA-II_rank: 1', 'change: 0.30291696497263254', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 91_100 Identity: {'ancestor_count': 85, 'ancestor_ids': ['88_88', '2_49'], 'birth_generation': 91, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '91_100', 'origin': '88_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 92_18 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_100', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_18', 'origin': '91_100~CUW~91_47#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 92_28 Identity: {'ancestor_count': 88, 'ancestor_ids': ['2_49', '91_47'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_28', 'origin': '2_49~CUW~91_47#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 92_31 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '91_100'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_31', 'origin': '2_49~CUW~91_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 92_36 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '2_49'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_36', 'origin': '91_58~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 92_40 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_40', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 92_46 Identity: {'ancestor_count': 86, 'ancestor_ids': ['91_100', '91_100'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_46', 'origin': '91_100~CUW~91_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 92_82 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_38', '91_100'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_82', 'origin': '91_38~CUW~91_100#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 92_95 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_95', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 92.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 93...:\n", + "PopulationResponse:\n", + " Generation: 93\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/93/20240220-065331\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 93 and asking ESP for generation 94...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 93 data persisted.\n", + "Evaluated candidates:\n", + "Id: 93_60 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_60', 'origin': '90_46~CUW~92_95#MGNP'} Metrics: ['ELUC: 23.829471743791824', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3037865044259215', 'is_elite: False']\n", + "Id: 93_76 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '92_71'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_76', 'origin': '91_58~CUW~92_71#MGNP'} Metrics: ['ELUC: 4.578552751005971', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.20872796420279308', 'is_elite: False']\n", + "Id: 93_100 Identity: {'ancestor_count': 3, 'ancestor_ids': ['1_1', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_100', 'origin': '1_1~CUW~92_95#MGNP'} Metrics: ['ELUC: 2.529175143626786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3517317879056728', 'is_elite: False']\n", + "Id: 93_99 Identity: {'ancestor_count': 90, 'ancestor_ids': ['1_1', '92_14'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_99', 'origin': '1_1~CUW~92_14#MGNP'} Metrics: ['ELUC: 1.8272691114001283', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07437247856582979', 'is_elite: False']\n", + "Id: 93_32 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_73', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_32', 'origin': '92_73~CUW~92_59#MGNP'} Metrics: ['ELUC: 1.2501957542242077', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10315574305831486', 'is_elite: False']\n", + "Id: 93_88 Identity: {'ancestor_count': 90, 'ancestor_ids': ['2_49', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_88', 'origin': '2_49~CUW~92_98#MGNP'} Metrics: ['ELUC: 0.7776445932799998', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2670273544488161', 'is_elite: False']\n", + "Id: 93_64 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_64', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.7692970831967529', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.03809776274947861', 'is_elite: False']\n", + "Id: 93_83 Identity: {'ancestor_count': 86, 'ancestor_ids': ['1_1', '91_70'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_83', 'origin': '1_1~CUW~91_70#MGNP'} Metrics: ['ELUC: 0.05308113920045845', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.03772432884185981', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 93_45 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_45', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.18042823419294327', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03487085713770255', 'is_elite: False']\n", + "Id: 92_71 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_71', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.22913993621062675', 'NSGA-II_crowding_distance: 0.10210013310895065', 'NSGA-II_rank: 1', 'change: 0.02478794634506252', 'is_elite: False']\n", + "Id: 93_34 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_34', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.3718496986340915', 'NSGA-II_crowding_distance: 0.12723621304736413', 'NSGA-II_rank: 2', 'change: 0.03553351657135562', 'is_elite: False']\n", + "Id: 93_21 Identity: {'ancestor_count': 2, 'ancestor_ids': ['92_71', '92_71'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_21', 'origin': '92_71~CUW~92_71#MGNP'} Metrics: ['ELUC: -0.4392764050796699', 'NSGA-II_crowding_distance: 0.1793155068625383', 'NSGA-II_rank: 1', 'change: 0.027907859369821847', 'is_elite: True']\n", + "Id: 93_35 Identity: {'ancestor_count': 86, 'ancestor_ids': ['91_70', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_35', 'origin': '91_70~CUW~92_95#MGNP'} Metrics: ['ELUC: -1.002596355275535', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.26903707152105044', 'is_elite: False']\n", + "Id: 93_23 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_23', 'origin': '91_58~CUW~92_95#MGNP'} Metrics: ['ELUC: -1.1158176595454903', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.271285374582128', 'is_elite: False']\n", + "Id: 93_90 Identity: {'ancestor_count': 90, 'ancestor_ids': ['1_1', '92_73'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_90', 'origin': '1_1~CUW~92_73#MGNP'} Metrics: ['ELUC: -1.3155149667622683', 'NSGA-II_crowding_distance: 0.26391697744249965', 'NSGA-II_rank: 3', 'change: 0.06444391992373893', 'is_elite: False']\n", + "Id: 93_72 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_49', '92_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_72', 'origin': '92_49~CUW~92_49#MGNP'} Metrics: ['ELUC: -1.3702051982656145', 'NSGA-II_crowding_distance: 0.14967146476218957', 'NSGA-II_rank: 2', 'change: 0.04916514967774672', 'is_elite: False']\n", + "Id: 93_22 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '1_1'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_22', 'origin': '90_46~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.4970525669819637', 'NSGA-II_crowding_distance: 0.5361844591624103', 'NSGA-II_rank: 4', 'change: 0.08761419928925025', 'is_elite: False']\n", + "Id: 92_49 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_70', '91_17'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_49', 'origin': '91_70~CUW~91_17#MGNP'} Metrics: ['ELUC: -1.721221426259055', 'NSGA-II_crowding_distance: 0.08013158456436308', 'NSGA-II_rank: 2', 'change: 0.053186178454265536', 'is_elite: False']\n", + "Id: 93_13 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_73', '92_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_13', 'origin': '92_73~CUW~92_49#MGNP'} Metrics: ['ELUC: -1.8004465055488392', 'NSGA-II_crowding_distance: 0.10962452416060041', 'NSGA-II_rank: 3', 'change: 0.07387373712244939', 'is_elite: False']\n", + "Id: 93_51 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_98', '92_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_51', 'origin': '92_98~CUW~92_49#MGNP'} Metrics: ['ELUC: -1.9385165609938506', 'NSGA-II_crowding_distance: 0.2557590507558524', 'NSGA-II_rank: 3', 'change: 0.08202206501593642', 'is_elite: False']\n", + "Id: 93_91 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_70', '92_73'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_91', 'origin': '91_70~CUW~92_73#MGNP'} Metrics: ['ELUC: -1.9426467529664002', 'NSGA-II_crowding_distance: 0.18784867512343562', 'NSGA-II_rank: 2', 'change: 0.061119784301774935', 'is_elite: False']\n", + "Id: 93_36 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_71', '92_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_36', 'origin': '92_71~CUW~92_49#MGNP'} Metrics: ['ELUC: -1.990831476650636', 'NSGA-II_crowding_distance: 0.224589836708236', 'NSGA-II_rank: 1', 'change: 0.048395249096361524', 'is_elite: True']\n", + "Id: 93_66 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_71', '92_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_66', 'origin': '92_71~CUW~92_49#MGNP'} Metrics: ['ELUC: -2.0574448762296553', 'NSGA-II_crowding_distance: 0.13905377668238725', 'NSGA-II_rank: 1', 'change: 0.06745964389528532', 'is_elite: False']\n", + "Id: 93_89 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_89', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -2.090389887316926', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 8', 'change: 0.2524402190165226', 'is_elite: False']\n", + "Id: 93_26 Identity: {'ancestor_count': 89, 'ancestor_ids': ['90_46', '91_70'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_26', 'origin': '90_46~CUW~91_70#MGNP'} Metrics: ['ELUC: -2.7428597614021366', 'NSGA-II_crowding_distance: 0.5463435614868712', 'NSGA-II_rank: 5', 'change: 0.09439449500488696', 'is_elite: False']\n", + "Id: 93_12 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_58', '91_73'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_12', 'origin': '91_58~CUW~91_73#MGNP'} Metrics: ['ELUC: -2.9080811011565233', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.15112510809648627', 'is_elite: False']\n", + "Id: 93_39 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_73', '92_73'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_39', 'origin': '92_73~CUW~92_73#MGNP'} Metrics: ['ELUC: -2.998024754308491', 'NSGA-II_crowding_distance: 0.09760044341787055', 'NSGA-II_rank: 1', 'change: 0.07279341685132575', 'is_elite: False']\n", + "Id: 92_73 Identity: {'ancestor_count': 89, 'ancestor_ids': ['1_1', '90_46'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_73', 'origin': '1_1~CUW~90_46#MGNP'} Metrics: ['ELUC: -3.344015810782628', 'NSGA-II_crowding_distance: 0.27912530655424705', 'NSGA-II_rank: 2', 'change: 0.07652282894846213', 'is_elite: False']\n", + "Id: 93_77 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_95', '92_73'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_77', 'origin': '92_95~CUW~92_73#MGNP'} Metrics: ['ELUC: -3.4405979678925376', 'NSGA-II_crowding_distance: 1.7501574343042199', 'NSGA-II_rank: 7', 'change: 0.2654179053012322', 'is_elite: False']\n", + "Id: 93_24 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_73', '1_1'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_24', 'origin': '92_73~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.452797073686286', 'NSGA-II_crowding_distance: 0.04249529122540839', 'NSGA-II_rank: 1', 'change: 0.07290188433056917', 'is_elite: False']\n", + "Id: 93_47 Identity: {'ancestor_count': 89, 'ancestor_ids': ['1_1', '90_46'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_47', 'origin': '1_1~CUW~90_46#MGNP'} Metrics: ['ELUC: -3.7175565927224477', 'NSGA-II_crowding_distance: 0.038670754866455076', 'NSGA-II_rank: 1', 'change: 0.07326238768431224', 'is_elite: False']\n", + "Id: 93_18 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_73', '91_70'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_18', 'origin': '92_73~CUW~91_70#MGNP'} Metrics: ['ELUC: -3.7992266341575442', 'NSGA-II_crowding_distance: 0.11348279646280246', 'NSGA-II_rank: 1', 'change: 0.07856135938104587', 'is_elite: False']\n", + "Id: 93_53 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '1_1'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_53', 'origin': '92_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.241985254390717', 'NSGA-II_crowding_distance: 1.4358425250725086', 'NSGA-II_rank: 6', 'change: 0.11017425545461955', 'is_elite: False']\n", + "Id: 93_50 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_91', '1_1'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_50', 'origin': '92_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.252729815539183', 'NSGA-II_crowding_distance: 0.23408433485817393', 'NSGA-II_rank: 4', 'change: 0.09119293238947858', 'is_elite: False']\n", + "Id: 93_17 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_73', '91_58'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_17', 'origin': '92_73~CUW~91_58#MGNP'} Metrics: ['ELUC: -4.329078629169261', 'NSGA-II_crowding_distance: 0.6357971426865225', 'NSGA-II_rank: 5', 'change: 0.10760907515236322', 'is_elite: False']\n", + "Id: 93_92 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_71', '92_97'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_92', 'origin': '92_71~CUW~92_97#MGNP'} Metrics: ['ELUC: -4.38382313801545', 'NSGA-II_crowding_distance: 0.20016608524737772', 'NSGA-II_rank: 4', 'change: 0.09945557298420798', 'is_elite: False']\n", + "Id: 93_75 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_91', '92_91'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_75', 'origin': '92_91~CUW~92_91#MGNP'} Metrics: ['ELUC: -4.700143991199513', 'NSGA-II_crowding_distance: 0.6045324540779844', 'NSGA-II_rank: 3', 'change: 0.08965744053318847', 'is_elite: False']\n", + "Id: 93_30 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '92_83'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_30', 'origin': '92_14~CUW~92_83#MGNP'} Metrics: ['ELUC: -4.718464040394519', 'NSGA-II_crowding_distance: 0.4445587014521839', 'NSGA-II_rank: 4', 'change: 0.13402623481580836', 'is_elite: False']\n", + "Id: 93_70 Identity: {'ancestor_count': 89, 'ancestor_ids': ['92_71', '90_46'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_70', 'origin': '92_71~CUW~90_46#MGNP'} Metrics: ['ELUC: -4.804463604265479', 'NSGA-II_crowding_distance: 0.3210635594328798', 'NSGA-II_rank: 2', 'change: 0.08827589184712326', 'is_elite: False']\n", + "Id: 93_97 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_49', '92_73'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_97', 'origin': '92_49~CUW~92_73#MGNP'} Metrics: ['ELUC: -5.047858327308384', 'NSGA-II_crowding_distance: 0.15210310228520252', 'NSGA-II_rank: 1', 'change: 0.0845474947213807', 'is_elite: False']\n", + "Id: 93_78 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_91', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_78', 'origin': '92_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.386135272812204', 'NSGA-II_crowding_distance: 1.279707031766903', 'NSGA-II_rank: 6', 'change: 0.257411918681691', 'is_elite: False']\n", + "Id: 93_73 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_49', '90_46'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_73', 'origin': '92_49~CUW~90_46#MGNP'} Metrics: ['ELUC: -5.929043942563515', 'NSGA-II_crowding_distance: 0.15603437491833938', 'NSGA-II_rank: 1', 'change: 0.08780187932506728', 'is_elite: False']\n", + "Id: 93_84 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_84', 'origin': '92_97~CUW~92_95#MGNP'} Metrics: ['ELUC: -5.950776648016206', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.313231226945366', 'is_elite: False']\n", + "Id: 93_56 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '91_70'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_56', 'origin': '92_14~CUW~91_70#MGNP'} Metrics: ['ELUC: -6.468495217662552', 'NSGA-II_crowding_distance: 0.12070005352213031', 'NSGA-II_rank: 1', 'change: 0.1069960290491897', 'is_elite: False']\n", + "Id: 93_63 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_14', '92_91'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_63', 'origin': '92_14~CUW~92_91#MGNP'} Metrics: ['ELUC: -6.5147704891588205', 'NSGA-II_crowding_distance: 0.3467164217635447', 'NSGA-II_rank: 2', 'change: 0.10977968333131499', 'is_elite: False']\n", + "Id: 93_71 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '92_73'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_71', 'origin': '92_59~CUW~92_73#MGNP'} Metrics: ['ELUC: -6.8989851310356585', 'NSGA-II_crowding_distance: 0.08516124083457645', 'NSGA-II_rank: 1', 'change: 0.10735588454662061', 'is_elite: False']\n", + "Id: 93_43 Identity: {'ancestor_count': 90, 'ancestor_ids': ['90_46', '92_14'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_43', 'origin': '90_46~CUW~92_14#MGNP'} Metrics: ['ELUC: -7.814519420946496', 'NSGA-II_crowding_distance: 0.12943432435787447', 'NSGA-II_rank: 1', 'change: 0.10956379991146212', 'is_elite: False']\n", + "Id: 93_16 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_49', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_16', 'origin': '92_49~CUW~92_59#MGNP'} Metrics: ['ELUC: -8.09548989888753', 'NSGA-II_crowding_distance: 0.5259564561162935', 'NSGA-II_rank: 3', 'change: 0.13148750656515168', 'is_elite: False']\n", + "Id: 93_14 Identity: {'ancestor_count': 91, 'ancestor_ids': ['91_70', '92_91'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_14', 'origin': '91_70~CUW~92_91#MGNP'} Metrics: ['ELUC: -8.126175104747121', 'NSGA-II_crowding_distance: 0.4387568721542624', 'NSGA-II_rank: 4', 'change: 0.15036105959741142', 'is_elite: False']\n", + "Id: 93_52 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_49', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_52', 'origin': '92_49~CUW~92_95#MGNP'} Metrics: ['ELUC: -8.192846761059995', 'NSGA-II_crowding_distance: 1.164715212609894', 'NSGA-II_rank: 7', 'change: 0.28636493706810107', 'is_elite: False']\n", + "Id: 93_94 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_73', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_94', 'origin': '91_73~CUW~92_98#MGNP'} Metrics: ['ELUC: -8.21528553679964', 'NSGA-II_crowding_distance: 0.6309089735278864', 'NSGA-II_rank: 5', 'change: 0.15671635210682727', 'is_elite: False']\n", + "Id: 93_81 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '90_46'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_81', 'origin': '92_14~CUW~90_46#MGNP'} Metrics: ['ELUC: -8.442935461740728', 'NSGA-II_crowding_distance: 0.2773744623934476', 'NSGA-II_rank: 2', 'change: 0.12061150340995806', 'is_elite: False']\n", + "Id: 93_48 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_91', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_48', 'origin': '92_91~CUW~92_98#MGNP'} Metrics: ['ELUC: -8.510406157596513', 'NSGA-II_crowding_distance: 0.753662317179168', 'NSGA-II_rank: 5', 'change: 0.18690613727082958', 'is_elite: False']\n", + "Id: 93_65 Identity: {'ancestor_count': 86, 'ancestor_ids': ['2_49', '91_70'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_65', 'origin': '2_49~CUW~91_70#MGNP'} Metrics: ['ELUC: -8.53104808010277', 'NSGA-II_crowding_distance: 0.5641574749274914', 'NSGA-II_rank: 6', 'change: 0.2779877186257608', 'is_elite: False']\n", + "Id: 92_97 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_73', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_97', 'origin': '91_73~CUW~91_73#MGNP'} Metrics: ['ELUC: -8.539552537695469', 'NSGA-II_crowding_distance: 0.19693784083919907', 'NSGA-II_rank: 1', 'change: 0.118135267948779', 'is_elite: True']\n", + "Id: 93_86 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_49', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_86', 'origin': '92_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 93_55 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_54', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_55', 'origin': '92_54~CUW~92_59#MGNP'} Metrics: ['ELUC: -9.129619302342883', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2968249881345467', 'is_elite: False']\n", + "Id: 93_25 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_25', 'origin': '92_97~CUW~92_59#MGNP'} Metrics: ['ELUC: -9.225624182428737', 'NSGA-II_crowding_distance: 0.2846586746178016', 'NSGA-II_rank: 3', 'change: 0.14719287592466665', 'is_elite: False']\n", + "Id: 93_68 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_98', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_68', 'origin': '92_98~CUW~92_59#MGNP'} Metrics: ['ELUC: -9.479776346963643', 'NSGA-II_crowding_distance: 0.23470354798924886', 'NSGA-II_rank: 2', 'change: 0.134743321578453', 'is_elite: False']\n", + "Id: 93_79 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_98', '92_73'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_79', 'origin': '92_98~CUW~92_73#MGNP'} Metrics: ['ELUC: -10.125526091843222', 'NSGA-II_crowding_distance: 0.49697376789264264', 'NSGA-II_rank: 4', 'change: 0.1562826869174129', 'is_elite: False']\n", + "Id: 93_85 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_14', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_85', 'origin': '92_14~CUW~92_59#MGNP'} Metrics: ['ELUC: -10.323145217691287', 'NSGA-II_crowding_distance: 0.12979770108679184', 'NSGA-II_rank: 1', 'change: 0.1257535098860232', 'is_elite: False']\n", + "Id: 93_15 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_14', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_15', 'origin': '92_14~CUW~92_59#MGNP'} Metrics: ['ELUC: -10.338333103501434', 'NSGA-II_crowding_distance: 0.019558288025663832', 'NSGA-II_rank: 1', 'change: 0.12633814880185043', 'is_elite: False']\n", + "Id: 92_14 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_87', '91_87'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_14', 'origin': '91_87~CUW~91_87#MGNP'} Metrics: ['ELUC: -10.522260905656585', 'NSGA-II_crowding_distance: 0.08232825014668033', 'NSGA-II_rank: 1', 'change: 0.12821021257834295', 'is_elite: False']\n", + "Id: 93_46 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '92_83'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_46', 'origin': '92_14~CUW~92_83#MGNP'} Metrics: ['ELUC: -10.910646197303784', 'NSGA-II_crowding_distance: 0.28355713907234736', 'NSGA-II_rank: 3', 'change: 0.1562448088130135', 'is_elite: False']\n", + "Id: 93_57 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_57', 'origin': '92_59~CUW~92_98#MGNP'} Metrics: ['ELUC: -11.048858012334483', 'NSGA-II_crowding_distance: 0.30855165581155813', 'NSGA-II_rank: 2', 'change: 0.1401147759611806', 'is_elite: False']\n", + "Id: 93_87 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '92_14'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_87', 'origin': '92_59~CUW~92_14#MGNP'} Metrics: ['ELUC: -11.084148093583948', 'NSGA-II_crowding_distance: 0.08727369740432331', 'NSGA-II_rank: 1', 'change: 0.13824635369103344', 'is_elite: False']\n", + "Id: 92_59 Identity: {'ancestor_count': 90, 'ancestor_ids': ['90_46', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_59', 'origin': '90_46~CUW~91_38#MGNP'} Metrics: ['ELUC: -11.172578558551619', 'NSGA-II_crowding_distance: 0.1987754496204611', 'NSGA-II_rank: 1', 'change: 0.1432146479580922', 'is_elite: True']\n", + "Id: 93_82 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_49', '91_47'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_82', 'origin': '92_49~CUW~91_47#MGNP'} Metrics: ['ELUC: -11.559472041755336', 'NSGA-II_crowding_distance: 0.19801118372091767', 'NSGA-II_rank: 3', 'change: 0.1800600609208665', 'is_elite: False']\n", + "Id: 93_54 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_54', 'origin': '92_97~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.589640113687873', 'NSGA-II_crowding_distance: 0.8227474649852424', 'NSGA-II_rank: 5', 'change: 0.2740876327140452', 'is_elite: False']\n", + "Id: 93_37 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_47', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_37', 'origin': '91_47~CUW~92_98#MGNP'} Metrics: ['ELUC: -11.980426417062702', 'NSGA-II_crowding_distance: 0.7694964632768877', 'NSGA-II_rank: 4', 'change: 0.2126470260281374', 'is_elite: False']\n", + "Id: 93_27 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_27', 'origin': '1_1~CUW~92_59#MGNP'} Metrics: ['ELUC: -12.045589982882499', 'NSGA-II_crowding_distance: 0.1254366831488255', 'NSGA-II_rank: 3', 'change: 0.18782754271819607', 'is_elite: False']\n", + "Id: 93_28 Identity: {'ancestor_count': 88, 'ancestor_ids': ['91_47', '1_1'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_28', 'origin': '91_47~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.06663654073968', 'NSGA-II_crowding_distance: 0.32464717430985535', 'NSGA-II_rank: 3', 'change: 0.20376176688858016', 'is_elite: False']\n", + "Id: 93_49 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_98', '92_97'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_49', 'origin': '92_98~CUW~92_97#MGNP'} Metrics: ['ELUC: -12.067571122073016', 'NSGA-II_crowding_distance: 0.23553171648818072', 'NSGA-II_rank: 2', 'change: 0.1743725984914637', 'is_elite: False']\n", + "Id: 93_67 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_98', '91_47'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_67', 'origin': '92_98~CUW~91_47#MGNP'} Metrics: ['ELUC: -12.379377299523833', 'NSGA-II_crowding_distance: 0.4425813784088325', 'NSGA-II_rank: 2', 'change: 0.18113001685752492', 'is_elite: False']\n", + "Id: 93_69 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_98', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_69', 'origin': '92_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.466570579795137', 'NSGA-II_crowding_distance: 0.45061271372495204', 'NSGA-II_rank: 3', 'change: 0.2647239375129613', 'is_elite: False']\n", + "Id: 93_95 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '91_47'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_95', 'origin': '92_14~CUW~91_47#MGNP'} Metrics: ['ELUC: -12.705791536996253', 'NSGA-II_crowding_distance: 0.22881892070050852', 'NSGA-II_rank: 1', 'change: 0.17003672904914616', 'is_elite: True']\n", + "Id: 93_74 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_47', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_74', 'origin': '91_47~CUW~92_98#MGNP'} Metrics: ['ELUC: -12.776731106815872', 'NSGA-II_crowding_distance: 0.08805429429849893', 'NSGA-II_rank: 1', 'change: 0.184266151429688', 'is_elite: False']\n", + "Id: 92_98 Identity: {'ancestor_count': 89, 'ancestor_ids': ['91_58', '1_1'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_98', 'origin': '91_58~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.285454998453153', 'NSGA-II_crowding_distance: 0.0926194239835871', 'NSGA-II_rank: 1', 'change: 0.18647310054808064', 'is_elite: False']\n", + "Id: 93_62 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_98', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_62', 'origin': '92_98~CUW~92_59#MGNP'} Metrics: ['ELUC: -13.699180221987774', 'NSGA-II_crowding_distance: 0.1340550845704316', 'NSGA-II_rank: 1', 'change: 0.1962474777108167', 'is_elite: False']\n", + "Id: 93_20 Identity: {'ancestor_count': 89, 'ancestor_ids': ['92_54', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_20', 'origin': '92_54~CUW~92_95#MGNP'} Metrics: ['ELUC: -13.794297561002427', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2926742282929295', 'is_elite: False']\n", + "Id: 93_40 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_40', 'origin': '92_14~CUW~92_95#MGNP'} Metrics: ['ELUC: -14.019377526488112', 'NSGA-II_crowding_distance: 0.48099701883544693', 'NSGA-II_rank: 4', 'change: 0.28659429855434215', 'is_elite: False']\n", + "Id: 93_80 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_80', 'origin': '92_59~CUW~92_98#MGNP'} Metrics: ['ELUC: -14.381192746179904', 'NSGA-II_crowding_distance: 0.14454947129234344', 'NSGA-II_rank: 1', 'change: 0.20787714303219912', 'is_elite: False']\n", + "Id: 93_41 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_49', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_41', 'origin': '92_49~CUW~92_95#MGNP'} Metrics: ['ELUC: -14.659826483981114', 'NSGA-II_crowding_distance: 0.2206588103614179', 'NSGA-II_rank: 3', 'change: 0.2754528633772293', 'is_elite: False']\n", + "Id: 93_93 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_95', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_93', 'origin': '92_95~CUW~92_98#MGNP'} Metrics: ['ELUC: -14.660349242560272', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2900854752314859', 'is_elite: False']\n", + "Id: 93_38 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_54', '92_98'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_38', 'origin': '92_54~CUW~92_98#MGNP'} Metrics: ['ELUC: -14.707180539573795', 'NSGA-II_crowding_distance: 0.5202202587301921', 'NSGA-II_rank: 2', 'change: 0.24911520993960487', 'is_elite: False']\n", + "Id: 93_58 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_95', '92_59'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_58', 'origin': '92_95~CUW~92_59#MGNP'} Metrics: ['ELUC: -14.723672698979552', 'NSGA-II_crowding_distance: 0.09476097973922955', 'NSGA-II_rank: 3', 'change: 0.2826089162271052', 'is_elite: False']\n", + "Id: 93_11 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '92_83'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_11', 'origin': '92_14~CUW~92_83#MGNP'} Metrics: ['ELUC: -14.762631428975546', 'NSGA-II_crowding_distance: 0.10383867364486032', 'NSGA-II_rank: 1', 'change: 0.22133072386477726', 'is_elite: False']\n", + "Id: 93_33 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_33', 'origin': '92_14~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.822420011034163', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2972053353810784', 'is_elite: False']\n", + "Id: 93_42 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_95', '92_83'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_42', 'origin': '92_95~CUW~92_83#MGNP'} Metrics: ['ELUC: -14.908867132000244', 'NSGA-II_crowding_distance: 0.2985367485358902', 'NSGA-II_rank: 2', 'change: 0.27855178072382525', 'is_elite: False']\n", + "Id: 93_29 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_98', '92_83'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_29', 'origin': '92_98~CUW~92_83#MGNP'} Metrics: ['ELUC: -15.116847466757036', 'NSGA-II_crowding_distance: 0.165168388611397', 'NSGA-II_rank: 1', 'change: 0.22637600182453427', 'is_elite: False']\n", + "Id: 93_19 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_83', '92_83'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_19', 'origin': '92_83~CUW~92_83#MGNP'} Metrics: ['ELUC: -15.920797885508158', 'NSGA-II_crowding_distance: 0.1774156115508956', 'NSGA-II_rank: 1', 'change: 0.25095884846826866', 'is_elite: False']\n", + "Id: 93_98 Identity: {'ancestor_count': 89, 'ancestor_ids': ['92_54', '92_71'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_98', 'origin': '92_54~CUW~92_71#MGNP'} Metrics: ['ELUC: -16.123031193021408', 'NSGA-II_crowding_distance: 0.2468475668511061', 'NSGA-II_rank: 1', 'change: 0.26223761858496875', 'is_elite: True']\n", + "Id: 93_31 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_98', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_31', 'origin': '92_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.261601626881202', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30330571884454044', 'is_elite: False']\n", + "Id: 93_44 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_98', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_44', 'origin': '92_98~CUW~92_95#MGNP'} Metrics: ['ELUC: -17.268532087555588', 'NSGA-II_crowding_distance: 0.21192588846253652', 'NSGA-II_rank: 1', 'change: 0.3017411965267025', 'is_elite: True']\n", + "Id: 93_96 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_95', '92_14'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_96', 'origin': '92_95~CUW~92_14#MGNP'} Metrics: ['ELUC: -17.4951884988309', 'NSGA-II_crowding_distance: 0.015692214009355825', 'NSGA-II_rank: 1', 'change: 0.3021856484665026', 'is_elite: False']\n", + "Id: 93_59 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_49', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_59', 'origin': '92_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.498338151790975', 'NSGA-II_crowding_distance: 0.008610398352124043', 'NSGA-II_rank: 1', 'change: 0.3025235237473499', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 92_95 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_95', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 93_61 Identity: {'ancestor_count': 3, 'ancestor_ids': ['92_95', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_61', 'origin': '92_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 93.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 94...:\n", + "PopulationResponse:\n", + " Generation: 94\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/94/20240220-070047\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 94 and asking ESP for generation 95...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 94 data persisted.\n", + "Evaluated candidates:\n", + "Id: 94_46 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_19', '93_61'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_46', 'origin': '93_19~CUW~93_61#MGNP'} Metrics: ['ELUC: 23.503358086242812', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 94_37 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '2_49'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_37', 'origin': '93_95~CUW~2_49#MGNP'} Metrics: ['ELUC: 21.83116870841676', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.29718316832949726', 'is_elite: False']\n", + "Id: 94_79 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '93_29'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_79', 'origin': '1_1~CUW~93_29#MGNP'} Metrics: ['ELUC: 14.51193564245509', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.21460887332038148', 'is_elite: False']\n", + "Id: 94_24 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_97', '93_29'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_24', 'origin': '93_97~CUW~93_29#MGNP'} Metrics: ['ELUC: 12.981817094850767', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.18323515284227235', 'is_elite: False']\n", + "Id: 94_88 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_61', '93_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_88', 'origin': '93_61~CUW~93_97#MGNP'} Metrics: ['ELUC: 10.516349303341173', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2777645715169722', 'is_elite: False']\n", + "Id: 94_15 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '93_85'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_15', 'origin': '1_1~CUW~93_85#MGNP'} Metrics: ['ELUC: 3.401755235847928', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.11369594444679516', 'is_elite: False']\n", + "Id: 94_56 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_56', 'origin': '93_95~CUW~93_36#MGNP'} Metrics: ['ELUC: 3.244802678914133', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.17229402507153518', 'is_elite: False']\n", + "Id: 94_26 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_26', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.6716964392226763', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.04754071190369488', 'is_elite: False']\n", + "Id: 94_99 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_43'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_99', 'origin': '2_49~CUW~93_43#MGNP'} Metrics: ['ELUC: 1.0953615758588928', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3447743884075391', 'is_elite: False']\n", + "Id: 94_82 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_19'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_82', 'origin': '2_49~CUW~93_19#MGNP'} Metrics: ['ELUC: 1.0906960570620956', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27913862288329633', 'is_elite: False']\n", + "Id: 94_28 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_36', '93_95'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_28', 'origin': '93_36~CUW~93_95#MGNP'} Metrics: ['ELUC: 0.7990508966126761', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.16139469897232206', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 93_21 Identity: {'ancestor_count': 2, 'ancestor_ids': ['92_71', '92_71'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_21', 'origin': '92_71~CUW~92_71#MGNP'} Metrics: ['ELUC: -0.4392764050796699', 'NSGA-II_crowding_distance: 0.259007821502797', 'NSGA-II_rank: 1', 'change: 0.027907859369821847', 'is_elite: True']\n", + "Id: 94_20 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_61', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_20', 'origin': '93_61~CUW~93_36#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.6967687604628916', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 94_29 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_43', '93_61'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_29', 'origin': '93_43~CUW~93_61#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 94_90 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_85', '93_44'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_90', 'origin': '93_85~CUW~93_44#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.5359823228825729', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 94_40 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_66'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_40', 'origin': '93_95~CUW~93_66#MGNP'} Metrics: ['ELUC: -0.6117434659150772', 'NSGA-II_crowding_distance: 0.6568445080279998', 'NSGA-II_rank: 7', 'change: 0.17789958529114508', 'is_elite: False']\n", + "Id: 94_23 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '1_1'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_23', 'origin': '92_97~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.311890623019456', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07969039594468484', 'is_elite: False']\n", + "Id: 94_91 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '93_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_91', 'origin': '1_1~CUW~93_97#MGNP'} Metrics: ['ELUC: -1.328423451485301', 'NSGA-II_crowding_distance: 0.5022568638776248', 'NSGA-II_rank: 2', 'change: 0.05107426660783883', 'is_elite: False']\n", + "Id: 94_11 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '92_59'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_11', 'origin': '93_95~CUW~92_59#MGNP'} Metrics: ['ELUC: -1.5699149149087641', 'NSGA-II_crowding_distance: 0.5266246672580346', 'NSGA-II_rank: 8', 'change: 0.246941672980549', 'is_elite: False']\n", + "Id: 93_36 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_71', '92_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_36', 'origin': '92_71~CUW~92_49#MGNP'} Metrics: ['ELUC: -1.990831476650636', 'NSGA-II_crowding_distance: 0.3210761874120228', 'NSGA-II_rank: 1', 'change: 0.048395249096361524', 'is_elite: True']\n", + "Id: 94_67 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_21'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_67', 'origin': '93_95~CUW~93_21#MGNP'} Metrics: ['ELUC: -2.4878202320734815', 'NSGA-II_crowding_distance: 0.9790219408919107', 'NSGA-II_rank: 7', 'change: 0.1788894891279788', 'is_elite: False']\n", + "Id: 94_84 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_97', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_84', 'origin': '93_97~CUW~93_36#MGNP'} Metrics: ['ELUC: -3.4313712040762807', 'NSGA-II_crowding_distance: 0.21467582781228955', 'NSGA-II_rank: 1', 'change: 0.07293306750298721', 'is_elite: True']\n", + "Id: 94_72 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_36', '92_59'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_72', 'origin': '93_36~CUW~92_59#MGNP'} Metrics: ['ELUC: -3.4415283836501724', 'NSGA-II_crowding_distance: 0.07508109759251551', 'NSGA-II_rank: 1', 'change: 0.0878309583601642', 'is_elite: False']\n", + "Id: 94_89 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_19', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_89', 'origin': '93_19~CUW~92_97#MGNP'} Metrics: ['ELUC: -3.484820931680556', 'NSGA-II_crowding_distance: 0.6408609518001352', 'NSGA-II_rank: 3', 'change: 0.11866008004534702', 'is_elite: False']\n", + "Id: 94_81 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_85', '1_1'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_81', 'origin': '93_85~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.6314984302488775', 'NSGA-II_crowding_distance: 0.11898870818239615', 'NSGA-II_rank: 1', 'change: 0.09193937309431792', 'is_elite: False']\n", + "Id: 94_85 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '1_1'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_85', 'origin': '93_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.6561499675043914', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.14645154786623615', 'is_elite: False']\n", + "Id: 94_42 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_19', '93_73'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_42', 'origin': '93_19~CUW~93_73#MGNP'} Metrics: ['ELUC: -3.8151461755266456', 'NSGA-II_crowding_distance: 0.6038289310579553', 'NSGA-II_rank: 2', 'change: 0.10310969348547272', 'is_elite: False']\n", + "Id: 94_31 Identity: {'ancestor_count': 90, 'ancestor_ids': ['93_61', '93_98'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_31', 'origin': '93_61~CUW~93_98#MGNP'} Metrics: ['ELUC: -4.122156898365474', 'NSGA-II_crowding_distance: 0.7672489166545357', 'NSGA-II_rank: 8', 'change: 0.2493589778058245', 'is_elite: False']\n", + "Id: 94_49 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_49', 'origin': '1_1~CUW~92_97#MGNP'} Metrics: ['ELUC: -4.920276891966144', 'NSGA-II_crowding_distance: 0.2492064016726645', 'NSGA-II_rank: 1', 'change: 0.09823971925494318', 'is_elite: True']\n", + "Id: 94_95 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_98', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_95', 'origin': '93_98~CUW~93_36#MGNP'} Metrics: ['ELUC: -4.943163662935623', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.28807573430767297', 'is_elite: False']\n", + "Id: 94_96 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_44', '93_29'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_96', 'origin': '93_44~CUW~93_29#MGNP'} Metrics: ['ELUC: -5.035612941684247', 'NSGA-II_crowding_distance: 1.3431554919720001', 'NSGA-II_rank: 7', 'change: 0.21625508433026533', 'is_elite: False']\n", + "Id: 94_54 Identity: {'ancestor_count': 4, 'ancestor_ids': ['93_61', '1_1'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_54', 'origin': '93_61~CUW~1_1#MGNP'} Metrics: ['ELUC: -5.235666159219262', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.31734176945705495', 'is_elite: False']\n", + "Id: 94_98 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_21', '92_59'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_98', 'origin': '93_21~CUW~92_59#MGNP'} Metrics: ['ELUC: -5.470918988430001', 'NSGA-II_crowding_distance: 0.6865127862664989', 'NSGA-II_rank: 4', 'change: 0.12630048375666675', 'is_elite: False']\n", + "Id: 94_93 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_29', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_93', 'origin': '93_29~CUW~92_97#MGNP'} Metrics: ['ELUC: -5.614556004669987', 'NSGA-II_crowding_distance: 1.0818724177071384', 'NSGA-II_rank: 6', 'change: 0.15275827396046535', 'is_elite: False']\n", + "Id: 94_61 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_66', '93_85'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_61', 'origin': '93_66~CUW~93_85#MGNP'} Metrics: ['ELUC: -6.062477024601536', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.13620277059160377', 'is_elite: False']\n", + "Id: 94_76 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_98', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_76', 'origin': '93_98~CUW~93_36#MGNP'} Metrics: ['ELUC: -6.082487073178775', 'NSGA-II_crowding_distance: 1.3381412490782296', 'NSGA-II_rank: 6', 'change: 0.22928263402996704', 'is_elite: False']\n", + "Id: 94_80 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '1_1'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_80', 'origin': '93_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.103468703151807', 'NSGA-II_crowding_distance: 0.36695457532986364', 'NSGA-II_rank: 4', 'change: 0.12850709380387815', 'is_elite: False']\n", + "Id: 94_75 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_62', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_75', 'origin': '93_62~CUW~93_36#MGNP'} Metrics: ['ELUC: -6.113093164756534', 'NSGA-II_crowding_distance: 0.5972931205460662', 'NSGA-II_rank: 3', 'change: 0.12206473759691501', 'is_elite: False']\n", + "Id: 94_47 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '93_95'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_47', 'origin': '1_1~CUW~93_95#MGNP'} Metrics: ['ELUC: -6.529255182695752', 'NSGA-II_crowding_distance: 0.6088508372283175', 'NSGA-II_rank: 5', 'change: 0.18074337075336058', 'is_elite: False']\n", + "Id: 94_34 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_36', '93_29'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_34', 'origin': '93_36~CUW~93_29#MGNP'} Metrics: ['ELUC: -6.60582524472121', 'NSGA-II_crowding_distance: 0.2725262907692369', 'NSGA-II_rank: 1', 'change: 0.11582176699901048', 'is_elite: True']\n", + "Id: 94_36 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_19', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_36', 'origin': '93_19~CUW~92_97#MGNP'} Metrics: ['ELUC: -6.924223984798016', 'NSGA-II_crowding_distance: 0.394793381298759', 'NSGA-II_rank: 4', 'change: 0.1732023326662535', 'is_elite: False']\n", + "Id: 94_21 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_19', '93_95'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_21', 'origin': '93_19~CUW~93_95#MGNP'} Metrics: ['ELUC: -7.405829034301894', 'NSGA-II_crowding_distance: 0.8316010582815323', 'NSGA-II_rank: 5', 'change: 0.19468772918735272', 'is_elite: False']\n", + "Id: 94_64 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_64', 'origin': '92_97~CUW~92_97#MGNP'} Metrics: ['ELUC: -7.880053395465896', 'NSGA-II_crowding_distance: 0.4040053471951285', 'NSGA-II_rank: 2', 'change: 0.11847533792688483', 'is_elite: False']\n", + "Id: 94_59 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_61'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_59', 'origin': '93_95~CUW~93_61#MGNP'} Metrics: ['ELUC: -7.9584762636728295', 'NSGA-II_crowding_distance: 0.9181275822928616', 'NSGA-II_rank: 6', 'change: 0.27756921312166083', 'is_elite: False']\n", + "Id: 94_13 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_44', '93_66'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_13', 'origin': '93_44~CUW~93_66#MGNP'} Metrics: ['ELUC: -8.149112487271022', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.29932103616573097', 'is_elite: False']\n", + "Id: 94_33 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_33', 'origin': '93_95~CUW~92_97#MGNP'} Metrics: ['ELUC: -8.186999490005613', 'NSGA-II_crowding_distance: 0.5535359324323998', 'NSGA-II_rank: 4', 'change: 0.17337883686048625', 'is_elite: False']\n", + "Id: 92_97 Identity: {'ancestor_count': 90, 'ancestor_ids': ['91_73', '91_73'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_97', 'origin': '91_73~CUW~91_73#MGNP'} Metrics: ['ELUC: -8.539552537695469', 'NSGA-II_crowding_distance: 0.14974499762106275', 'NSGA-II_rank: 1', 'change: 0.118135267948779', 'is_elite: False']\n", + "Id: 94_35 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '93_43'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_35', 'origin': '92_97~CUW~93_43#MGNP'} Metrics: ['ELUC: -8.76033099583349', 'NSGA-II_crowding_distance: 0.08425367138237216', 'NSGA-II_rank: 1', 'change: 0.12393971058218396', 'is_elite: False']\n", + "Id: 94_53 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '93_95'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_53', 'origin': '92_59~CUW~93_95#MGNP'} Metrics: ['ELUC: -8.787479426207724', 'NSGA-II_crowding_distance: 0.48569965585239433', 'NSGA-II_rank: 3', 'change: 0.14375457520677745', 'is_elite: False']\n", + "Id: 94_71 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '93_19'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_71', 'origin': '92_97~CUW~93_19#MGNP'} Metrics: ['ELUC: -8.812599609818728', 'NSGA-II_crowding_distance: 0.43031921194593803', 'NSGA-II_rank: 3', 'change: 0.17051638826985738', 'is_elite: False']\n", + "Id: 94_18 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_44', '92_59'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_18', 'origin': '93_44~CUW~92_59#MGNP'} Metrics: ['ELUC: -9.003449373258693', 'NSGA-II_crowding_distance: 0.8733555342405628', 'NSGA-II_rank: 5', 'change: 0.24467811255920416', 'is_elite: False']\n", + "Id: 94_92 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '92_59'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_92', 'origin': '92_97~CUW~92_59#MGNP'} Metrics: ['ELUC: -9.163342099981177', 'NSGA-II_crowding_distance: 0.3370856796236068', 'NSGA-II_rank: 2', 'change: 0.13541565562631974', 'is_elite: False']\n", + "Id: 94_65 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_65', 'origin': '92_59~CUW~92_97#MGNP'} Metrics: ['ELUC: -9.294967418182901', 'NSGA-II_crowding_distance: 0.10562196259225844', 'NSGA-II_rank: 1', 'change: 0.13045506252692363', 'is_elite: False']\n", + "Id: 94_83 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_83', 'origin': '93_95~CUW~92_97#MGNP'} Metrics: ['ELUC: -9.484850981470396', 'NSGA-II_crowding_distance: 0.1495528082464054', 'NSGA-II_rank: 1', 'change: 0.14315962293801285', 'is_elite: False']\n", + "Id: 94_30 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_98'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_30', 'origin': '93_95~CUW~93_98#MGNP'} Metrics: ['ELUC: -9.593687132223094', 'NSGA-II_crowding_distance: 0.6629535086568729', 'NSGA-II_rank: 4', 'change: 0.23882310881116142', 'is_elite: False']\n", + "Id: 94_50 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_98', '93_95'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_50', 'origin': '93_98~CUW~93_95#MGNP'} Metrics: ['ELUC: -9.76257457305296', 'NSGA-II_crowding_distance: 0.475375743430996', 'NSGA-II_rank: 5', 'change: 0.26786050513584647', 'is_elite: False']\n", + "Id: 94_97 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_44', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_97', 'origin': '93_44~CUW~92_97#MGNP'} Metrics: ['ELUC: -10.178347093879042', 'NSGA-II_crowding_distance: 0.30714576013118045', 'NSGA-II_rank: 4', 'change: 0.26492985746319603', 'is_elite: False']\n", + "Id: 94_12 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_61', '93_19'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_12', 'origin': '93_61~CUW~93_19#MGNP'} Metrics: ['ELUC: -10.25057520595622', 'NSGA-II_crowding_distance: 0.5177936285311199', 'NSGA-II_rank: 5', 'change: 0.28539650968406877', 'is_elite: False']\n", + "Id: 94_27 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_29', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_27', 'origin': '93_29~CUW~93_36#MGNP'} Metrics: ['ELUC: -10.467655965266857', 'NSGA-II_crowding_distance: 0.3477521027293974', 'NSGA-II_rank: 3', 'change: 0.19905740776673267', 'is_elite: False']\n", + "Id: 94_77 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_98', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_77', 'origin': '93_98~CUW~92_97#MGNP'} Metrics: ['ELUC: -10.550521875364248', 'NSGA-II_crowding_distance: 0.30499389047586556', 'NSGA-II_rank: 3', 'change: 0.2085963919615088', 'is_elite: False']\n", + "Id: 94_86 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '92_59'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_86', 'origin': '93_95~CUW~92_59#MGNP'} Metrics: ['ELUC: -10.738781573815864', 'NSGA-II_crowding_distance: 0.2877310969406983', 'NSGA-II_rank: 2', 'change: 0.1666913633529809', 'is_elite: False']\n", + "Id: 94_94 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '93_61'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_94', 'origin': '92_59~CUW~93_61#MGNP'} Metrics: ['ELUC: -10.825736698261569', 'NSGA-II_crowding_distance: 0.35321649275668776', 'NSGA-II_rank: 3', 'change: 0.25273840073981485', 'is_elite: False']\n", + "Id: 94_66 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_66', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -10.861404402008201', 'NSGA-II_crowding_distance: 0.17500586750667027', 'NSGA-II_rank: 4', 'change: 0.27752942396431135', 'is_elite: False']\n", + "Id: 92_59 Identity: {'ancestor_count': 90, 'ancestor_ids': ['90_46', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_59', 'origin': '90_46~CUW~91_38#MGNP'} Metrics: ['ELUC: -11.172578558551619', 'NSGA-II_crowding_distance: 0.2732692691211782', 'NSGA-II_rank: 1', 'change: 0.1432146479580922', 'is_elite: True']\n", + "Id: 94_87 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_44', '2_49'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_87', 'origin': '93_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.174985281739835', 'NSGA-II_crowding_distance: 0.20200908894488906', 'NSGA-II_rank: 3', 'change: 0.26711637679507355', 'is_elite: False']\n", + "Id: 94_73 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_95'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_73', 'origin': '93_95~CUW~93_95#MGNP'} Metrics: ['ELUC: -11.775238332285882', 'NSGA-II_crowding_distance: 0.39710862178360173', 'NSGA-II_rank: 2', 'change: 0.17429521438392181', 'is_elite: False']\n", + "Id: 94_16 Identity: {'ancestor_count': 90, 'ancestor_ids': ['93_98', '2_49'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_16', 'origin': '93_98~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.775414722578937', 'NSGA-II_crowding_distance: 0.12949968890129873', 'NSGA-II_rank: 4', 'change: 0.27758283034820713', 'is_elite: False']\n", + "Id: 94_55 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_29', '93_44'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_55', 'origin': '93_29~CUW~93_44#MGNP'} Metrics: ['ELUC: -12.06558151085342', 'NSGA-II_crowding_distance: 0.1724707968613854', 'NSGA-II_rank: 3', 'change: 0.2708536447662767', 'is_elite: False']\n", + "Id: 94_100 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_19'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_100', 'origin': '2_49~CUW~93_19#MGNP'} Metrics: ['ELUC: -12.120120619435754', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2872918086225342', 'is_elite: False']\n", + "Id: 94_78 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_44', '93_29'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_78', 'origin': '93_44~CUW~93_29#MGNP'} Metrics: ['ELUC: -12.31133749891473', 'NSGA-II_crowding_distance: 0.0807344562711988', 'NSGA-II_rank: 4', 'change: 0.284010448329199', 'is_elite: False']\n", + "Id: 94_41 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_73'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_41', 'origin': '2_49~CUW~93_73#MGNP'} Metrics: ['ELUC: -12.451339082702802', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28407383792376145', 'is_elite: False']\n", + "Id: 94_48 Identity: {'ancestor_count': 3, 'ancestor_ids': ['93_21', '2_49'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_48', 'origin': '93_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.605229767752247', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.27611782823151615', 'is_elite: False']\n", + "Id: 93_95 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '91_47'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_95', 'origin': '92_14~CUW~91_47#MGNP'} Metrics: ['ELUC: -12.705791536996253', 'NSGA-II_crowding_distance: 0.2551179260673905', 'NSGA-II_rank: 1', 'change: 0.17003672904914616', 'is_elite: True']\n", + "Id: 94_45 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_80', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_45', 'origin': '93_80~CUW~92_97#MGNP'} Metrics: ['ELUC: -13.000711913510594', 'NSGA-II_crowding_distance: 0.19999934673476177', 'NSGA-II_rank: 1', 'change: 0.18831216522804511', 'is_elite: False']\n", + "Id: 94_38 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '93_98'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_38', 'origin': '92_97~CUW~93_98#MGNP'} Metrics: ['ELUC: -13.010166034142694', 'NSGA-II_crowding_distance: 0.5257236076849295', 'NSGA-II_rank: 2', 'change: 0.23802934771810322', 'is_elite: False']\n", + "Id: 94_43 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_36', '93_19'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_43', 'origin': '93_36~CUW~93_19#MGNP'} Metrics: ['ELUC: -13.195855665690763', 'NSGA-II_crowding_distance: 0.1395279988808777', 'NSGA-II_rank: 1', 'change: 0.22139553771796436', 'is_elite: False']\n", + "Id: 94_51 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '93_29'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_51', 'origin': '1_1~CUW~93_29#MGNP'} Metrics: ['ELUC: -13.392624485557844', 'NSGA-II_crowding_distance: 0.06654725128227379', 'NSGA-II_rank: 1', 'change: 0.2232933335026371', 'is_elite: False']\n", + "Id: 94_17 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_29', '93_95'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_17', 'origin': '93_29~CUW~93_95#MGNP'} Metrics: ['ELUC: -14.027865956866389', 'NSGA-II_crowding_distance: 0.1239672991178857', 'NSGA-II_rank: 1', 'change: 0.22713228341329653', 'is_elite: False']\n", + "Id: 94_70 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_29', '93_19'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_70', 'origin': '93_29~CUW~93_19#MGNP'} Metrics: ['ELUC: -15.153853409904968', 'NSGA-II_crowding_distance: 0.15228666151249642', 'NSGA-II_rank: 1', 'change: 0.2303938152701165', 'is_elite: False']\n", + "Id: 94_68 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_19', '93_80'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_68', 'origin': '93_19~CUW~93_80#MGNP'} Metrics: ['ELUC: -15.541346036171547', 'NSGA-II_crowding_distance: 0.10654590893934801', 'NSGA-II_rank: 1', 'change: 0.2468870060531627', 'is_elite: False']\n", + "Id: 94_69 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_98', '93_80'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_69', 'origin': '93_98~CUW~93_80#MGNP'} Metrics: ['ELUC: -15.566307042491827', 'NSGA-II_crowding_distance: 0.2962853509067329', 'NSGA-II_rank: 2', 'change: 0.2583429417151821', 'is_elite: False']\n", + "Id: 94_52 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_44', '93_62'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_52', 'origin': '93_44~CUW~93_62#MGNP'} Metrics: ['ELUC: -15.753390185903722', 'NSGA-II_crowding_distance: 0.2788853958188481', 'NSGA-II_rank: 2', 'change: 0.2773531298433551', 'is_elite: False']\n", + "Id: 94_60 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_98', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_60', 'origin': '93_98~CUW~92_97#MGNP'} Metrics: ['ELUC: -15.800877761040223', 'NSGA-II_crowding_distance: 0.051308562592979015', 'NSGA-II_rank: 1', 'change: 0.2512045374243483', 'is_elite: False']\n", + "Id: 94_39 Identity: {'ancestor_count': 90, 'ancestor_ids': ['93_98', '1_1'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_39', 'origin': '93_98~CUW~1_1#MGNP'} Metrics: ['ELUC: -15.908585906625445', 'NSGA-II_crowding_distance: 0.055299452284340314', 'NSGA-II_rank: 1', 'change: 0.2559641639142886', 'is_elite: False']\n", + "Id: 93_98 Identity: {'ancestor_count': 89, 'ancestor_ids': ['92_54', '92_71'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_98', 'origin': '92_54~CUW~92_71#MGNP'} Metrics: ['ELUC: -16.123031193021408', 'NSGA-II_crowding_distance: 0.07242805245872441', 'NSGA-II_rank: 1', 'change: 0.26223761858496875', 'is_elite: False']\n", + "Id: 94_19 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_44'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_19', 'origin': '93_95~CUW~93_44#MGNP'} Metrics: ['ELUC: -16.263470923945057', 'NSGA-II_crowding_distance: 0.09374457450244608', 'NSGA-II_rank: 1', 'change: 0.271552572555332', 'is_elite: False']\n", + "Id: 94_63 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_29', '93_61'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_63', 'origin': '93_29~CUW~93_61#MGNP'} Metrics: ['ELUC: -16.269657449223622', 'NSGA-II_crowding_distance: 0.1090243943109438', 'NSGA-II_rank: 1', 'change: 0.2877206177066094', 'is_elite: False']\n", + "Id: 94_57 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_98', '93_19'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_57', 'origin': '93_98~CUW~93_19#MGNP'} Metrics: ['ELUC: -17.12250823192018', 'NSGA-II_crowding_distance: 0.10380061164665391', 'NSGA-II_rank: 1', 'change: 0.2895048942966996', 'is_elite: False']\n", + "Id: 93_44 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_98', '92_95'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_44', 'origin': '92_98~CUW~92_95#MGNP'} Metrics: ['ELUC: -17.268532087555588', 'NSGA-II_crowding_distance: 0.0652429496675287', 'NSGA-II_rank: 1', 'change: 0.3017411965267025', 'is_elite: False']\n", + "Id: 94_74 Identity: {'ancestor_count': 4, 'ancestor_ids': ['93_61', '93_61'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_74', 'origin': '93_61~CUW~93_61#MGNP'} Metrics: ['ELUC: -17.499530059708913', 'NSGA-II_crowding_distance: 0.021914060287874737', 'NSGA-II_rank: 1', 'change: 0.3025737598938585', 'is_elite: False']\n", + "Id: 94_25 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_44'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_25', 'origin': '2_49~CUW~93_44#MGNP'} Metrics: ['ELUC: -17.572232690963823', 'NSGA-II_crowding_distance: 0.19616433348004697', 'NSGA-II_rank: 2', 'change: 0.30299688206188347', 'is_elite: False']\n", + "Id: 94_62 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '93_61'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_62', 'origin': '92_59~CUW~93_61#MGNP'} Metrics: ['ELUC: -17.590279294855268', 'NSGA-II_crowding_distance: 0.007062732319639143', 'NSGA-II_rank: 1', 'change: 0.30281971448800876', 'is_elite: False']\n", + "Id: 94_14 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_61', '93_73'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_14', 'origin': '93_61~CUW~93_73#MGNP'} Metrics: ['ELUC: -17.597388119476616', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 93_61 Identity: {'ancestor_count': 3, 'ancestor_ids': ['92_95', '2_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_61', 'origin': '92_95~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 94_22 Identity: {'ancestor_count': 90, 'ancestor_ids': ['2_49', '93_98'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_22', 'origin': '2_49~CUW~93_98#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 94_32 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_61'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_32', 'origin': '93_95~CUW~93_61#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 94_44 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_61', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_44', 'origin': '93_61~CUW~93_36#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 94_58 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_80', '93_44'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_58', 'origin': '93_80~CUW~93_44#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 94.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 95...:\n", + "PopulationResponse:\n", + " Generation: 95\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/95/20240220-070803\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 95 and asking ESP for generation 96...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 95 data persisted.\n", + "Evaluated candidates:\n", + "Id: 95_79 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_79', 'origin': '93_95~CUW~1_1#MGNP'} Metrics: ['ELUC: 12.357427517936994', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2285195713029785', 'is_elite: False']\n", + "Id: 95_65 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_36', '94_34'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_65', 'origin': '93_36~CUW~94_34#MGNP'} Metrics: ['ELUC: 8.961557527000949', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.14113844759653169', 'is_elite: False']\n", + "Id: 95_35 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_70', '94_84'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_35', 'origin': '94_70~CUW~94_84#MGNP'} Metrics: ['ELUC: 7.909211200519573', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2142370936308714', 'is_elite: False']\n", + "Id: 95_39 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '94_70'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_39', 'origin': '1_1~CUW~94_70#MGNP'} Metrics: ['ELUC: 2.6589487472357347', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.07738216472609133', 'is_elite: False']\n", + "Id: 95_100 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_36', '94_34'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_100', 'origin': '93_36~CUW~94_34#MGNP'} Metrics: ['ELUC: 2.5957306155847606', 'NSGA-II_crowding_distance: 0.41011637657799666', 'NSGA-II_rank: 5', 'change: 0.09534277737112945', 'is_elite: False']\n", + "Id: 95_56 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_21', '93_95'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_56', 'origin': '93_21~CUW~93_95#MGNP'} Metrics: ['ELUC: 2.187047905771893', 'NSGA-II_crowding_distance: 1.4098915292211172', 'NSGA-II_rank: 8', 'change: 0.16005764671131625', 'is_elite: False']\n", + "Id: 95_19 Identity: {'ancestor_count': 92, 'ancestor_ids': ['2_49', '94_70'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_19', 'origin': '2_49~CUW~94_70#MGNP'} Metrics: ['ELUC: 2.071607398257584', 'NSGA-II_crowding_distance: 1.8244153207140783', 'NSGA-II_rank: 9', 'change: 0.24094827938873603', 'is_elite: False']\n", + "Id: 95_11 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_95', '94_84'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_11', 'origin': '93_95~CUW~94_84#MGNP'} Metrics: ['ELUC: 1.8712695978239835', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.12633660820626372', 'is_elite: False']\n", + "Id: 95_62 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_43', '94_84'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_62', 'origin': '94_43~CUW~94_84#MGNP'} Metrics: ['ELUC: 0.6571017341723164', 'NSGA-II_crowding_distance: 0.9803677962773454', 'NSGA-II_rank: 7', 'change: 0.14280629749242116', 'is_elite: False']\n", + "Id: 95_45 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_84', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_45', 'origin': '94_84~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.35294589143244454', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.04390174028552005', 'is_elite: False']\n", + "Id: 95_34 Identity: {'ancestor_count': 3, 'ancestor_ids': ['93_21', '93_21'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_34', 'origin': '93_21~CUW~93_21#MGNP'} Metrics: ['ELUC: 0.17272737815491385', 'NSGA-II_crowding_distance: 0.32018380987189354', 'NSGA-II_rank: 4', 'change: 0.05167152466923094', 'is_elite: False']\n", + "Id: 95_94 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_94', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.042214699406448786', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.032238419168333594', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 95_41 Identity: {'ancestor_count': 3, 'ancestor_ids': ['93_21', '93_21'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_41', 'origin': '93_21~CUW~93_21#MGNP'} Metrics: ['ELUC: -0.32132317567715313', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03072267791970483', 'is_elite: False']\n", + "Id: 93_21 Identity: {'ancestor_count': 2, 'ancestor_ids': ['92_71', '92_71'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_21', 'origin': '92_71~CUW~92_71#MGNP'} Metrics: ['ELUC: -0.4392764050796699', 'NSGA-II_crowding_distance: 0.16683263456905506', 'NSGA-II_rank: 1', 'change: 0.027907859369821847', 'is_elite: False']\n", + "Id: 95_20 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_58', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_20', 'origin': '94_58~CUW~92_59#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.6696593113112702', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 95_47 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_95'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_47', 'origin': '2_49~CUW~93_95#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.17630744786442482', 'NSGA-II_rank: 8', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 95_46 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_36'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_46', 'origin': '2_49~CUW~93_36#MGNP'} Metrics: ['ELUC: -0.608740615761724', 'NSGA-II_crowding_distance: 0.8516647412676855', 'NSGA-II_rank: 7', 'change: 0.2131592938234241', 'is_elite: False']\n", + "Id: 95_23 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_45', '2_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_23', 'origin': '94_45~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.612158122107039', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.30471970168174345', 'is_elite: False']\n", + "Id: 95_71 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_71', 'origin': '2_49~CUW~92_59#MGNP'} Metrics: ['ELUC: -0.6356046920231074', 'NSGA-II_crowding_distance: 0.5901084707788828', 'NSGA-II_rank: 8', 'change: 0.23960775133857462', 'is_elite: False']\n", + "Id: 95_52 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_58', '93_36'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_52', 'origin': '94_58~CUW~93_36#MGNP'} Metrics: ['ELUC: -0.7689351564932821', 'NSGA-II_crowding_distance: 1.0196322037226544', 'NSGA-II_rank: 7', 'change: 0.22715108692311586', 'is_elite: False']\n", + "Id: 95_76 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_36', '93_36'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_76', 'origin': '93_36~CUW~93_36#MGNP'} Metrics: ['ELUC: -0.8868893386594903', 'NSGA-II_crowding_distance: 0.23218856671876584', 'NSGA-II_rank: 2', 'change: 0.05757468253666669', 'is_elite: False']\n", + "Id: 95_44 Identity: {'ancestor_count': 3, 'ancestor_ids': ['93_21', '93_21'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_44', 'origin': '93_21~CUW~93_21#MGNP'} Metrics: ['ELUC: -1.0983233612405063', 'NSGA-II_crowding_distance: 0.15690768839384636', 'NSGA-II_rank: 1', 'change: 0.036038365257994864', 'is_elite: False']\n", + "Id: 95_72 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '94_83'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_72', 'origin': '1_1~CUW~94_83#MGNP'} Metrics: ['ELUC: -1.5893728463125945', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.10939307998601734', 'is_elite: False']\n", + "Id: 95_63 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_81', '93_36'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_63', 'origin': '94_81~CUW~93_36#MGNP'} Metrics: ['ELUC: -1.6311539981768948', 'NSGA-II_crowding_distance: 0.544552195552687', 'NSGA-II_rank: 5', 'change: 0.0980018878919789', 'is_elite: False']\n", + "Id: 93_36 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_71', '92_49'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_36', 'origin': '92_71~CUW~92_49#MGNP'} Metrics: ['ELUC: -1.990831476650636', 'NSGA-II_crowding_distance: 0.14798673890685396', 'NSGA-II_rank: 1', 'change: 0.048395249096361524', 'is_elite: False']\n", + "Id: 95_67 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_84', '93_36'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_67', 'origin': '94_84~CUW~93_36#MGNP'} Metrics: ['ELUC: -2.0025463980764355', 'NSGA-II_crowding_distance: 0.19589563932314172', 'NSGA-II_rank: 2', 'change: 0.06744810890530674', 'is_elite: False']\n", + "Id: 95_95 Identity: {'ancestor_count': 93, 'ancestor_ids': ['93_21', '94_81'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_95', 'origin': '93_21~CUW~94_81#MGNP'} Metrics: ['ELUC: -2.1163612635488773', 'NSGA-II_crowding_distance: 0.37352616762154167', 'NSGA-II_rank: 4', 'change: 0.07853109833165263', 'is_elite: False']\n", + "Id: 95_75 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '92_97'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_75', 'origin': '1_1~CUW~92_97#MGNP'} Metrics: ['ELUC: -2.168169343661236', 'NSGA-II_crowding_distance: 0.16416849901817643', 'NSGA-II_rank: 1', 'change: 0.062038694156699235', 'is_elite: False']\n", + "Id: 95_37 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '94_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_37', 'origin': '1_1~CUW~94_49#MGNP'} Metrics: ['ELUC: -2.496897207829848', 'NSGA-II_crowding_distance: 0.19785281025316223', 'NSGA-II_rank: 4', 'change: 0.09545347565891596', 'is_elite: False']\n", + "Id: 95_80 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_83', '93_21'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_80', 'origin': '94_83~CUW~93_21#MGNP'} Metrics: ['ELUC: -2.627397922415003', 'NSGA-II_crowding_distance: 0.6348563817889574', 'NSGA-II_rank: 5', 'change: 0.12963601732631339', 'is_elite: False']\n", + "Id: 95_24 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_24', 'origin': '1_1~CUW~92_59#MGNP'} Metrics: ['ELUC: -2.729472522273909', 'NSGA-II_crowding_distance: 0.42655263366443763', 'NSGA-II_rank: 3', 'change: 0.07832568213004157', 'is_elite: False']\n", + "Id: 95_31 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_81', '94_34'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_31', 'origin': '94_81~CUW~94_34#MGNP'} Metrics: ['ELUC: -2.7830915687518307', 'NSGA-II_crowding_distance: 0.09304742171150962', 'NSGA-II_rank: 3', 'change: 0.09207773835403417', 'is_elite: False']\n", + "Id: 95_40 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '93_36'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_40', 'origin': '92_97~CUW~93_36#MGNP'} Metrics: ['ELUC: -3.0814834064591525', 'NSGA-II_crowding_distance: 0.4645252856813995', 'NSGA-II_rank: 4', 'change: 0.10891851333129218', 'is_elite: False']\n", + "Id: 95_60 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_58', '94_84'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_60', 'origin': '94_58~CUW~94_84#MGNP'} Metrics: ['ELUC: -3.1712108900677016', 'NSGA-II_crowding_distance: 0.7191023755277202', 'NSGA-II_rank: 5', 'change: 0.20444601415669938', 'is_elite: False']\n", + "Id: 95_48 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_83', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_48', 'origin': '94_83~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.2379315917250246', 'NSGA-II_crowding_distance: 0.13062443559620798', 'NSGA-II_rank: 3', 'change: 0.09327057623562979', 'is_elite: False']\n", + "Id: 95_61 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_84', '94_84'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_61', 'origin': '94_84~CUW~94_84#MGNP'} Metrics: ['ELUC: -3.252362294394342', 'NSGA-II_crowding_distance: 0.28197144884894365', 'NSGA-II_rank: 2', 'change: 0.07363257287987227', 'is_elite: False']\n", + "Id: 94_84 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_97', '93_36'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_84', 'origin': '93_97~CUW~93_36#MGNP'} Metrics: ['ELUC: -3.4313712040762807', 'NSGA-II_crowding_distance: 0.1521085828675565', 'NSGA-II_rank: 1', 'change: 0.07293306750298721', 'is_elite: False']\n", + "Id: 95_81 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_34', '94_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_81', 'origin': '94_34~CUW~94_49#MGNP'} Metrics: ['ELUC: -4.046733037136125', 'NSGA-II_crowding_distance: 0.3201029008866568', 'NSGA-II_rank: 3', 'change: 0.1034138824316653', 'is_elite: False']\n", + "Id: 95_97 Identity: {'ancestor_count': 93, 'ancestor_ids': ['93_36', '94_81'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_97', 'origin': '93_36~CUW~94_81#MGNP'} Metrics: ['ELUC: -4.168751552080916', 'NSGA-II_crowding_distance: 0.10427971352147396', 'NSGA-II_rank: 1', 'change: 0.07347400885722569', 'is_elite: False']\n", + "Id: 95_38 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_38', 'origin': '2_49~CUW~92_59#MGNP'} Metrics: ['ELUC: -4.378881190100318', 'NSGA-II_crowding_distance: 1.0332795257049687', 'NSGA-II_rank: 9', 'change: 0.26019399515509944', 'is_elite: False']\n", + "Id: 95_21 Identity: {'ancestor_count': 93, 'ancestor_ids': ['93_36', '94_81'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_21', 'origin': '93_36~CUW~94_81#MGNP'} Metrics: ['ELUC: -4.546278165647868', 'NSGA-II_crowding_distance: 0.2030164129577463', 'NSGA-II_rank: 1', 'change: 0.08512749536263417', 'is_elite: True']\n", + "Id: 94_49 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '92_97'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_49', 'origin': '1_1~CUW~92_97#MGNP'} Metrics: ['ELUC: -4.920276891966144', 'NSGA-II_crowding_distance: 0.3490505114061814', 'NSGA-II_rank: 2', 'change: 0.09823971925494318', 'is_elite: False']\n", + "Id: 95_59 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_58', '92_97'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_59', 'origin': '94_58~CUW~92_97#MGNP'} Metrics: ['ELUC: -6.017352698068005', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2630201886591361', 'is_elite: False']\n", + "Id: 95_51 Identity: {'ancestor_count': 93, 'ancestor_ids': ['2_49', '94_45'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_51', 'origin': '2_49~CUW~94_45#MGNP'} Metrics: ['ELUC: -6.278435370726833', 'NSGA-II_crowding_distance: 0.6853345493161065', 'NSGA-II_rank: 5', 'change: 0.2223498855449697', 'is_elite: False']\n", + "Id: 95_50 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_34', '93_95'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_50', 'origin': '94_34~CUW~93_95#MGNP'} Metrics: ['ELUC: -6.3156894911106995', 'NSGA-II_crowding_distance: 0.5752100990665932', 'NSGA-II_rank: 4', 'change: 0.1419061604195372', 'is_elite: False']\n", + "Id: 95_89 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_21', '92_97'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_89', 'origin': '93_21~CUW~92_97#MGNP'} Metrics: ['ELUC: -6.39570303508331', 'NSGA-II_crowding_distance: 0.2627205530723352', 'NSGA-II_rank: 1', 'change: 0.09625752919434206', 'is_elite: True']\n", + "Id: 95_90 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_45', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_90', 'origin': '94_45~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.556367664389114', 'NSGA-II_crowding_distance: 0.2879139054628151', 'NSGA-II_rank: 3', 'change: 0.11715996277390119', 'is_elite: False']\n", + "Id: 94_34 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_36', '93_29'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_34', 'origin': '93_36~CUW~93_29#MGNP'} Metrics: ['ELUC: -6.60582524472121', 'NSGA-II_crowding_distance: 0.30501444729092575', 'NSGA-II_rank: 2', 'change: 0.11582176699901048', 'is_elite: False']\n", + "Id: 95_42 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_95', '94_34'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_42', 'origin': '93_95~CUW~94_34#MGNP'} Metrics: ['ELUC: -6.806568327022374', 'NSGA-II_crowding_distance: 0.20118200989671664', 'NSGA-II_rank: 3', 'change: 0.12884581269567774', 'is_elite: False']\n", + "Id: 95_84 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_21', '94_17'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_84', 'origin': '93_21~CUW~94_17#MGNP'} Metrics: ['ELUC: -7.232732933462432', 'NSGA-II_crowding_distance: 0.31536576834319574', 'NSGA-II_rank: 4', 'change: 0.17569639930960199', 'is_elite: False']\n", + "Id: 95_49 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_58', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_49', 'origin': '94_58~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.325922698002675', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2593995893654742', 'is_elite: False']\n", + "Id: 95_22 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_49', '92_97'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_22', 'origin': '94_49~CUW~92_97#MGNP'} Metrics: ['ELUC: -7.670857183825684', 'NSGA-II_crowding_distance: 0.20662952125433737', 'NSGA-II_rank: 1', 'change: 0.11049238467386922', 'is_elite: True']\n", + "Id: 95_25 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_70', '2_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_25', 'origin': '94_70~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.890040494588388', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.24587727688074112', 'is_elite: False']\n", + "Id: 95_27 Identity: {'ancestor_count': 93, 'ancestor_ids': ['93_21', '94_68'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_27', 'origin': '93_21~CUW~94_68#MGNP'} Metrics: ['ELUC: -8.142006877108157', 'NSGA-II_crowding_distance: 0.21394338270966096', 'NSGA-II_rank: 3', 'change: 0.14094370592650887', 'is_elite: False']\n", + "Id: 95_58 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_84', '94_45'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_58', 'origin': '94_84~CUW~94_45#MGNP'} Metrics: ['ELUC: -8.291579047009616', 'NSGA-II_crowding_distance: 0.19547881773083509', 'NSGA-II_rank: 2', 'change: 0.12815678131863667', 'is_elite: False']\n", + "Id: 95_74 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_63', '94_34'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_74', 'origin': '94_63~CUW~94_34#MGNP'} Metrics: ['ELUC: -8.586293644831878', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.24444437235146024', 'is_elite: False']\n", + "Id: 95_55 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_43', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_55', 'origin': '94_43~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.633521622275921', 'NSGA-II_crowding_distance: 0.5290931261973286', 'NSGA-II_rank: 4', 'change: 0.17784691623233004', 'is_elite: False']\n", + "Id: 95_36 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_34', '94_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_36', 'origin': '94_34~CUW~94_49#MGNP'} Metrics: ['ELUC: -8.835620925021145', 'NSGA-II_crowding_distance: 0.12075976139437582', 'NSGA-II_rank: 1', 'change: 0.11650501497168478', 'is_elite: False']\n", + "Id: 95_26 Identity: {'ancestor_count': 93, 'ancestor_ids': ['92_59', '94_45'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_26', 'origin': '92_59~CUW~94_45#MGNP'} Metrics: ['ELUC: -8.839501745689068', 'NSGA-II_crowding_distance: 0.22620851670454076', 'NSGA-II_rank: 3', 'change: 0.14805685348914177', 'is_elite: False']\n", + "Id: 95_33 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_49', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_33', 'origin': '94_49~CUW~92_59#MGNP'} Metrics: ['ELUC: -9.196089703084132', 'NSGA-II_crowding_distance: 0.36465949070591436', 'NSGA-II_rank: 2', 'change: 0.12822303082252584', 'is_elite: False']\n", + "Id: 95_64 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_64', 'origin': '92_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.274720366509333', 'NSGA-II_crowding_distance: 0.07236981347268624', 'NSGA-II_rank: 1', 'change: 0.11930635379773295', 'is_elite: False']\n", + "Id: 95_73 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_34', '92_97'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_73', 'origin': '94_34~CUW~92_97#MGNP'} Metrics: ['ELUC: -9.290511690232787', 'NSGA-II_crowding_distance: 0.18806877938633867', 'NSGA-II_rank: 1', 'change: 0.13037891803690374', 'is_elite: False']\n", + "Id: 95_77 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_77', 'origin': '2_49~CUW~92_59#MGNP'} Metrics: ['ELUC: -9.502276527603568', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.28072523378592995', 'is_elite: False']\n", + "Id: 95_78 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_78', 'origin': '93_95~CUW~92_59#MGNP'} Metrics: ['ELUC: -9.691350805414737', 'NSGA-II_crowding_distance: 0.41019492208475405', 'NSGA-II_rank: 3', 'change: 0.17178244812818985', 'is_elite: False']\n", + "Id: 95_88 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_83', '94_58'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_88', 'origin': '94_83~CUW~94_58#MGNP'} Metrics: ['ELUC: -10.228637377641146', 'NSGA-II_crowding_distance: 0.6433690364360121', 'NSGA-II_rank: 5', 'change: 0.24053428099390425', 'is_elite: False']\n", + "Id: 92_59 Identity: {'ancestor_count': 90, 'ancestor_ids': ['90_46', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_59', 'origin': '90_46~CUW~91_38#MGNP'} Metrics: ['ELUC: -11.172578558551619', 'NSGA-II_crowding_distance: 0.23745443540236105', 'NSGA-II_rank: 1', 'change: 0.1432146479580922', 'is_elite: True']\n", + "Id: 95_69 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_97', '2_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_69', 'origin': '92_97~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.243088026948485', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28048990440750504', 'is_elite: False']\n", + "Id: 95_98 Identity: {'ancestor_count': 93, 'ancestor_ids': ['92_97', '94_58'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_98', 'origin': '92_97~CUW~94_58#MGNP'} Metrics: ['ELUC: -11.245548411248901', 'NSGA-II_crowding_distance: 0.551617245406613', 'NSGA-II_rank: 4', 'change: 0.23400440581034088', 'is_elite: False']\n", + "Id: 95_43 Identity: {'ancestor_count': 93, 'ancestor_ids': ['93_95', '94_58'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_43', 'origin': '93_95~CUW~94_58#MGNP'} Metrics: ['ELUC: -11.71416098298931', 'NSGA-II_crowding_distance: 0.32125173102794274', 'NSGA-II_rank: 4', 'change: 0.2563181731772559', 'is_elite: False']\n", + "Id: 95_70 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_45', '94_70'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_70', 'origin': '94_45~CUW~94_70#MGNP'} Metrics: ['ELUC: -11.872930307699637', 'NSGA-II_crowding_distance: 0.6256754959802993', 'NSGA-II_rank: 3', 'change: 0.2000505612340854', 'is_elite: False']\n", + "Id: 95_54 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_84', '94_45'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_54', 'origin': '94_84~CUW~94_45#MGNP'} Metrics: ['ELUC: -11.9457456172645', 'NSGA-II_crowding_distance: 0.41640588678230944', 'NSGA-II_rank: 2', 'change: 0.16985663590034153', 'is_elite: False']\n", + "Id: 95_29 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_29', 'origin': '92_59~CUW~92_59#MGNP'} Metrics: ['ELUC: -12.185847827856785', 'NSGA-II_crowding_distance: 0.1770949212251557', 'NSGA-II_rank: 1', 'change: 0.15209528323497956', 'is_elite: False']\n", + "Id: 93_95 Identity: {'ancestor_count': 90, 'ancestor_ids': ['92_14', '91_47'], 'birth_generation': 93, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '93_95', 'origin': '92_14~CUW~91_47#MGNP'} Metrics: ['ELUC: -12.705791536996253', 'NSGA-II_crowding_distance: 0.15481426244061933', 'NSGA-II_rank: 1', 'change: 0.17003672904914616', 'is_elite: False']\n", + "Id: 95_30 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '93_95'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_30', 'origin': '1_1~CUW~93_95#MGNP'} Metrics: ['ELUC: -12.72442867298119', 'NSGA-II_crowding_distance: 0.19743619966817527', 'NSGA-II_rank: 2', 'change: 0.18599662445719717', 'is_elite: False']\n", + "Id: 95_85 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_70', '1_1'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_85', 'origin': '94_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.846182030325991', 'NSGA-II_crowding_distance: 0.20828479139648998', 'NSGA-II_rank: 2', 'change: 0.20942568312512747', 'is_elite: False']\n", + "Id: 95_53 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_45', '94_45'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_53', 'origin': '94_45~CUW~94_45#MGNP'} Metrics: ['ELUC: -12.95146929998977', 'NSGA-II_crowding_distance: 0.10215939119212492', 'NSGA-II_rank: 1', 'change: 0.18529557669230814', 'is_elite: False']\n", + "Id: 95_68 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '94_63'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_68', 'origin': '1_1~CUW~94_63#MGNP'} Metrics: ['ELUC: -13.36268302456144', 'NSGA-II_crowding_distance: 0.2489792753027735', 'NSGA-II_rank: 4', 'change: 0.27452655315863117', 'is_elite: False']\n", + "Id: 95_82 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_95', '93_95'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_82', 'origin': '93_95~CUW~93_95#MGNP'} Metrics: ['ELUC: -13.527617844739133', 'NSGA-II_crowding_distance: 0.12357128083364671', 'NSGA-II_rank: 1', 'change: 0.18657216899193327', 'is_elite: False']\n", + "Id: 95_18 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_43', '94_34'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_18', 'origin': '94_43~CUW~94_34#MGNP'} Metrics: ['ELUC: -13.811636578604812', 'NSGA-II_crowding_distance: 0.23087516950561643', 'NSGA-II_rank: 2', 'change: 0.22557586525351794', 'is_elite: False']\n", + "Id: 95_28 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_43', '94_84'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_28', 'origin': '94_43~CUW~94_84#MGNP'} Metrics: ['ELUC: -13.85770476713698', 'NSGA-II_crowding_distance: 0.2565416847699386', 'NSGA-II_rank: 1', 'change: 0.20678739787945502', 'is_elite: True']\n", + "Id: 95_96 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_84', '94_58'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_96', 'origin': '94_84~CUW~94_58#MGNP'} Metrics: ['ELUC: -14.106291953090361', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2756809237781267', 'is_elite: False']\n", + "Id: 95_83 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_58', '94_83'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_83', 'origin': '94_58~CUW~94_83#MGNP'} Metrics: ['ELUC: -14.248157269409495', 'NSGA-II_crowding_distance: 0.5307707204821241', 'NSGA-II_rank: 3', 'change: 0.2523190175853961', 'is_elite: False']\n", + "Id: 95_91 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_36'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_91', 'origin': '2_49~CUW~93_36#MGNP'} Metrics: ['ELUC: -14.579437175964356', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2887017341968819', 'is_elite: False']\n", + "Id: 95_12 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_70', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_12', 'origin': '94_70~CUW~92_59#MGNP'} Metrics: ['ELUC: -14.76363046242635', 'NSGA-II_crowding_distance: 0.3322191999778499', 'NSGA-II_rank: 2', 'change: 0.24207013520241175', 'is_elite: False']\n", + "Id: 95_66 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_34', '94_17'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_66', 'origin': '94_34~CUW~94_17#MGNP'} Metrics: ['ELUC: -15.398390372665087', 'NSGA-II_crowding_distance: 0.2634502549377535', 'NSGA-II_rank: 1', 'change: 0.23137090422409945', 'is_elite: True']\n", + "Id: 95_13 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_83', '2_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_13', 'origin': '94_83~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.872001860397914', 'NSGA-II_crowding_distance: 0.38785467726165873', 'NSGA-II_rank: 2', 'change: 0.2835635112339914', 'is_elite: False']\n", + "Id: 95_16 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_70', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_16', 'origin': '94_70~CUW~92_59#MGNP'} Metrics: ['ELUC: -15.92119232791008', 'NSGA-II_crowding_distance: 0.21878270844464714', 'NSGA-II_rank: 1', 'change: 0.2503770629918865', 'is_elite: True']\n", + "Id: 95_14 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_43', '2_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_14', 'origin': '94_43~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.544194641954597', 'NSGA-II_crowding_distance: 0.19637937529061222', 'NSGA-II_rank: 1', 'change: 0.27720613716423126', 'is_elite: False']\n", + "Id: 95_17 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_63', '93_95'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_17', 'origin': '94_63~CUW~93_95#MGNP'} Metrics: ['ELUC: -16.678959472436954', 'NSGA-II_crowding_distance: 0.1422308861733376', 'NSGA-II_rank: 1', 'change: 0.29611275017896954', 'is_elite: False']\n", + "Id: 95_15 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_95'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_15', 'origin': '2_49~CUW~93_95#MGNP'} Metrics: ['ELUC: -17.558116517741606', 'NSGA-II_crowding_distance: 0.07478408661061765', 'NSGA-II_rank: 1', 'change: 0.302438097203628', 'is_elite: False']\n", + "Id: 95_87 Identity: {'ancestor_count': 3, 'ancestor_ids': ['93_21', '2_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_87', 'origin': '93_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.590285474670765', 'NSGA-II_crowding_distance: 0.004185280299298793', 'NSGA-II_rank: 1', 'change: 0.30296117191402927', 'is_elite: False']\n", + "Id: 95_99 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '93_36'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_99', 'origin': '2_49~CUW~93_36#MGNP'} Metrics: ['ELUC: -17.597133913929884', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30302116077528923', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 94_58 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_80', '93_44'], 'birth_generation': 94, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '94_58', 'origin': '93_80~CUW~93_44#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 95_32 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_17', '94_58'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_32', 'origin': '94_17~CUW~94_58#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 95_57 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_58', '94_58'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_57', 'origin': '94_58~CUW~94_58#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 95_86 Identity: {'ancestor_count': 93, 'ancestor_ids': ['94_45', '94_58'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_86', 'origin': '94_45~CUW~94_58#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 95_92 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_92', 'origin': '2_49~CUW~92_59#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 95_93 Identity: {'ancestor_count': 3, 'ancestor_ids': ['93_21', '2_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_93', 'origin': '93_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 95.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 96...:\n", + "PopulationResponse:\n", + " Generation: 96\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/96/20240220-071521\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 96 and asking ESP for generation 97...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 96 data persisted.\n", + "Evaluated candidates:\n", + "Id: 96_53 Identity: {'ancestor_count': 4, 'ancestor_ids': ['2_49', '95_93'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_53', 'origin': '2_49~CUW~95_93#MGNP'} Metrics: ['ELUC: 19.17418906471594', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2997604720434111', 'is_elite: False']\n", + "Id: 96_67 Identity: {'ancestor_count': 93, 'ancestor_ids': ['2_49', '95_22'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_67', 'origin': '2_49~CUW~95_22#MGNP'} Metrics: ['ELUC: 6.920764837635228', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.27606380651971196', 'is_elite: False']\n", + "Id: 96_17 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_21', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_17', 'origin': '95_21~CUW~2_49#MGNP'} Metrics: ['ELUC: 6.879714084931711', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.3276274160273982', 'is_elite: False']\n", + "Id: 96_86 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_21', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_86', 'origin': '95_21~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.6787102032164654', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.26569786178335525', 'is_elite: False']\n", + "Id: 96_30 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_30', 'origin': '92_59~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.063674002870988', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11558832583913518', 'is_elite: False']\n", + "Id: 96_55 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '93_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_55', 'origin': '95_28~CUW~93_21#MGNP'} Metrics: ['ELUC: 0.6265651231264397', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08391271945602691', 'is_elite: False']\n", + "Id: 96_14 Identity: {'ancestor_count': 4, 'ancestor_ids': ['95_93', '95_44'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_14', 'origin': '95_93~CUW~95_44#MGNP'} Metrics: ['ELUC: 0.6106394501716836', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2437531016405441', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 96_85 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_14', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_85', 'origin': '95_14~CUW~95_21#MGNP'} Metrics: ['ELUC: -0.540050933359924', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.23867759717639164', 'is_elite: False']\n", + "Id: 96_32 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_14', '92_59'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_32', 'origin': '95_14~CUW~92_59#MGNP'} Metrics: ['ELUC: -1.0544753232717226', 'NSGA-II_crowding_distance: 0.6369315140610207', 'NSGA-II_rank: 6', 'change: 0.2418327165142693', 'is_elite: False']\n", + "Id: 96_93 Identity: {'ancestor_count': 3, 'ancestor_ids': ['93_21', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_93', 'origin': '93_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.226560495938337', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2542746947188931', 'is_elite: False']\n", + "Id: 96_21 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '93_36'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_21', 'origin': '95_28~CUW~93_36#MGNP'} Metrics: ['ELUC: -1.2976262051336043', 'NSGA-II_crowding_distance: 0.45807290448308324', 'NSGA-II_rank: 5', 'change: 0.12601757000473612', 'is_elite: False']\n", + "Id: 96_83 Identity: {'ancestor_count': 91, 'ancestor_ids': ['2_49', '92_59'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_83', 'origin': '2_49~CUW~92_59#MGNP'} Metrics: ['ELUC: -1.3625520277228045', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.30547677959557773', 'is_elite: False']\n", + "Id: 96_75 Identity: {'ancestor_count': 94, 'ancestor_ids': ['1_1', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_75', 'origin': '1_1~CUW~95_21#MGNP'} Metrics: ['ELUC: -1.7760499245200525', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.07986591670131046', 'is_elite: False']\n", + "Id: 96_70 Identity: {'ancestor_count': 94, 'ancestor_ids': ['93_21', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_70', 'origin': '93_21~CUW~95_21#MGNP'} Metrics: ['ELUC: -1.834295376605558', 'NSGA-II_crowding_distance: 0.3450709428529857', 'NSGA-II_rank: 1', 'change: 0.06358565789382868', 'is_elite: True']\n", + "Id: 96_25 Identity: {'ancestor_count': 92, 'ancestor_ids': ['93_21', '95_75'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_25', 'origin': '93_21~CUW~95_75#MGNP'} Metrics: ['ELUC: -2.0572735906798227', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.07283082361269395', 'is_elite: False']\n", + "Id: 96_45 Identity: {'ancestor_count': 94, 'ancestor_ids': ['93_21', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_45', 'origin': '93_21~CUW~95_21#MGNP'} Metrics: ['ELUC: -2.4455746278259984', 'NSGA-II_crowding_distance: 0.1546944472564272', 'NSGA-II_rank: 1', 'change: 0.06635743512395802', 'is_elite: False']\n", + "Id: 96_58 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_44'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_58', 'origin': '95_66~CUW~95_44#MGNP'} Metrics: ['ELUC: -2.53659825323218', 'NSGA-II_crowding_distance: 0.429362266274277', 'NSGA-II_rank: 3', 'change: 0.0977828895597487', 'is_elite: False']\n", + "Id: 96_82 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '95_14'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_82', 'origin': '95_28~CUW~95_14#MGNP'} Metrics: ['ELUC: -2.5443649096511827', 'NSGA-II_crowding_distance: 1.0467230983559666', 'NSGA-II_rank: 7', 'change: 0.2528374679600245', 'is_elite: False']\n", + "Id: 96_73 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_73', 'origin': '95_28~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.937922765990745', 'NSGA-II_crowding_distance: 0.4201897821238283', 'NSGA-II_rank: 5', 'change: 0.1347085620018033', 'is_elite: False']\n", + "Id: 96_76 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_89', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_76', 'origin': '95_89~CUW~95_21#MGNP'} Metrics: ['ELUC: -3.0343397332842406', 'NSGA-II_crowding_distance: 0.1281744216010346', 'NSGA-II_rank: 2', 'change: 0.08159859181276778', 'is_elite: False']\n", + "Id: 96_33 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '95_29'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_33', 'origin': '1_1~CUW~95_29#MGNP'} Metrics: ['ELUC: -3.2407994395554054', 'NSGA-II_crowding_distance: 0.25027575747232966', 'NSGA-II_rank: 2', 'change: 0.08477950453291543', 'is_elite: False']\n", + "Id: 96_63 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_63', 'origin': '95_28~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.5992772241488318', 'NSGA-II_crowding_distance: 0.18238509118946172', 'NSGA-II_rank: 1', 'change: 0.07979074762891103', 'is_elite: True']\n", + "Id: 96_99 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_89', '95_66'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_99', 'origin': '95_89~CUW~95_66#MGNP'} Metrics: ['ELUC: -4.140400033912409', 'NSGA-II_crowding_distance: 0.9289868200035252', 'NSGA-II_rank: 4', 'change: 0.11805328594126663', 'is_elite: False']\n", + "Id: 96_15 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_21', '95_73'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_15', 'origin': '95_21~CUW~95_73#MGNP'} Metrics: ['ELUC: -4.2984134430080925', 'NSGA-II_crowding_distance: 0.7953204230610462', 'NSGA-II_rank: 5', 'change: 0.1511617224064014', 'is_elite: False']\n", + "Id: 95_21 Identity: {'ancestor_count': 93, 'ancestor_ids': ['93_36', '94_81'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_21', 'origin': '93_36~CUW~94_81#MGNP'} Metrics: ['ELUC: -4.546278165647868', 'NSGA-II_crowding_distance: 0.1393673944796281', 'NSGA-II_rank: 1', 'change: 0.08512749536263417', 'is_elite: False']\n", + "Id: 96_46 Identity: {'ancestor_count': 92, 'ancestor_ids': ['95_89', '95_93'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_46', 'origin': '95_89~CUW~95_93#MGNP'} Metrics: ['ELUC: -4.631293683878684', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26131792858904085', 'is_elite: False']\n", + "Id: 96_62 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_89', '95_28'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_62', 'origin': '95_89~CUW~95_28#MGNP'} Metrics: ['ELUC: -5.192550298738918', 'NSGA-II_crowding_distance: 0.34409290172232765', 'NSGA-II_rank: 2', 'change: 0.10719537172872033', 'is_elite: False']\n", + "Id: 96_41 Identity: {'ancestor_count': 92, 'ancestor_ids': ['95_89', '95_89'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_41', 'origin': '95_89~CUW~95_89#MGNP'} Metrics: ['ELUC: -5.2583092270908365', 'NSGA-II_crowding_distance: 0.14248833525876445', 'NSGA-II_rank: 1', 'change: 0.09322058790159926', 'is_elite: False']\n", + "Id: 96_91 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_16', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_91', 'origin': '95_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.319883454203901', 'NSGA-II_crowding_distance: 1.4395189607260837', 'NSGA-II_rank: 7', 'change: 0.26059998698256726', 'is_elite: False']\n", + "Id: 96_19 Identity: {'ancestor_count': 93, 'ancestor_ids': ['92_59', '95_14'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_19', 'origin': '92_59~CUW~95_14#MGNP'} Metrics: ['ELUC: -5.363550037675557', 'NSGA-II_crowding_distance: 0.9493590676987769', 'NSGA-II_rank: 6', 'change: 0.245395312690855', 'is_elite: False']\n", + "Id: 96_11 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_21', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_11', 'origin': '95_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.437650801576118', 'NSGA-II_crowding_distance: 0.5301204392997387', 'NSGA-II_rank: 6', 'change: 0.26183378703505816', 'is_elite: False']\n", + "Id: 96_65 Identity: {'ancestor_count': 94, 'ancestor_ids': ['94_84', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_65', 'origin': '94_84~CUW~95_21#MGNP'} Metrics: ['ELUC: -5.584188782525917', 'NSGA-II_crowding_distance: 0.3433964065056264', 'NSGA-II_rank: 3', 'change: 0.11413716050023552', 'is_elite: False']\n", + "Id: 96_12 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_16', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_12', 'origin': '95_16~CUW~95_21#MGNP'} Metrics: ['ELUC: -5.59525884715959', 'NSGA-II_crowding_distance: 0.6621516293912217', 'NSGA-II_rank: 4', 'change: 0.1363834242015486', 'is_elite: False']\n", + "Id: 96_49 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '95_22'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_49', 'origin': '95_28~CUW~95_22#MGNP'} Metrics: ['ELUC: -5.909928703203723', 'NSGA-II_crowding_distance: 0.3340167032184117', 'NSGA-II_rank: 3', 'change: 0.12020070504890706', 'is_elite: False']\n", + "Id: 96_57 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_93', '95_22'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_57', 'origin': '95_93~CUW~95_22#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.9176818423663022', 'NSGA-II_rank: 6', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 96_61 Identity: {'ancestor_count': 93, 'ancestor_ids': ['93_95', '95_28'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_61', 'origin': '93_95~CUW~95_28#MGNP'} Metrics: ['ELUC: -6.315624742741556', 'NSGA-II_crowding_distance: 0.9710662947673745', 'NSGA-II_rank: 5', 'change: 0.20843644905464656', 'is_elite: False']\n", + "Id: 95_89 Identity: {'ancestor_count': 91, 'ancestor_ids': ['93_21', '92_97'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_89', 'origin': '93_21~CUW~92_97#MGNP'} Metrics: ['ELUC: -6.39570303508331', 'NSGA-II_crowding_distance: 0.13725564259020204', 'NSGA-II_rank: 1', 'change: 0.09625752919434206', 'is_elite: False']\n", + "Id: 96_34 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '92_59'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_34', 'origin': '1_1~CUW~92_59#MGNP'} Metrics: ['ELUC: -6.765029661232879', 'NSGA-II_crowding_distance: 0.198371428506868', 'NSGA-II_rank: 2', 'change: 0.11171073970838771', 'is_elite: False']\n", + "Id: 96_36 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_73', '95_44'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_36', 'origin': '95_73~CUW~95_44#MGNP'} Metrics: ['ELUC: -6.893288276136248', 'NSGA-II_crowding_distance: 0.16746977419076503', 'NSGA-II_rank: 2', 'change: 0.1276302628122995', 'is_elite: False']\n", + "Id: 96_28 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_89', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_28', 'origin': '95_89~CUW~95_21#MGNP'} Metrics: ['ELUC: -7.008404358885165', 'NSGA-II_crowding_distance: 0.1202322178135708', 'NSGA-II_rank: 1', 'change: 0.10447495911284659', 'is_elite: False']\n", + "Id: 96_97 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '95_22'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_97', 'origin': '95_28~CUW~95_22#MGNP'} Metrics: ['ELUC: -7.249965787430594', 'NSGA-II_crowding_distance: 0.2660838246028951', 'NSGA-II_rank: 2', 'change: 0.14306415608440143', 'is_elite: False']\n", + "Id: 95_22 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_49', '92_97'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_22', 'origin': '94_49~CUW~92_97#MGNP'} Metrics: ['ELUC: -7.670857183825684', 'NSGA-II_crowding_distance: 0.1232931248442094', 'NSGA-II_rank: 1', 'change: 0.11049238467386922', 'is_elite: False']\n", + "Id: 96_98 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '93_95'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_98', 'origin': '1_1~CUW~93_95#MGNP'} Metrics: ['ELUC: -7.782816715333206', 'NSGA-II_crowding_distance: 0.33965894438366695', 'NSGA-II_rank: 3', 'change: 0.1524355027558135', 'is_elite: False']\n", + "Id: 96_37 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '95_73'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_37', 'origin': '95_28~CUW~95_73#MGNP'} Metrics: ['ELUC: -7.792845485401218', 'NSGA-II_crowding_distance: 0.5080349321487461', 'NSGA-II_rank: 4', 'change: 0.16377256283095734', 'is_elite: False']\n", + "Id: 96_84 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_44'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_84', 'origin': '95_66~CUW~95_44#MGNP'} Metrics: ['ELUC: -8.335277735077089', 'NSGA-II_crowding_distance: 0.144071540171775', 'NSGA-II_rank: 3', 'change: 0.15625770418569146', 'is_elite: False']\n", + "Id: 96_48 Identity: {'ancestor_count': 92, 'ancestor_ids': ['92_59', '95_89'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_48', 'origin': '92_59~CUW~95_89#MGNP'} Metrics: ['ELUC: -8.614004929316046', 'NSGA-II_crowding_distance: 0.20106246213618786', 'NSGA-II_rank: 1', 'change: 0.11401534342706965', 'is_elite: True']\n", + "Id: 96_43 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_43', 'origin': '95_66~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.625889879215524', 'NSGA-II_crowding_distance: 0.41606809753005924', 'NSGA-II_rank: 4', 'change: 0.16903340814257295', 'is_elite: False']\n", + "Id: 96_23 Identity: {'ancestor_count': 93, 'ancestor_ids': ['2_49', '95_28'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_23', 'origin': '2_49~CUW~95_28#MGNP'} Metrics: ['ELUC: -9.025590761633204', 'NSGA-II_crowding_distance: 0.7466066724558706', 'NSGA-II_rank: 5', 'change: 0.23433466769289035', 'is_elite: False']\n", + "Id: 96_50 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_89'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_50', 'origin': '95_66~CUW~95_89#MGNP'} Metrics: ['ELUC: -9.524566731094158', 'NSGA-II_crowding_distance: 0.3716306464911262', 'NSGA-II_rank: 3', 'change: 0.156867038376638', 'is_elite: False']\n", + "Id: 96_60 Identity: {'ancestor_count': 93, 'ancestor_ids': ['93_95', '95_22'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_60', 'origin': '93_95~CUW~95_22#MGNP'} Metrics: ['ELUC: -9.851305805065591', 'NSGA-II_crowding_distance: 0.3077696260563718', 'NSGA-II_rank: 2', 'change: 0.1450039445781764', 'is_elite: False']\n", + "Id: 96_79 Identity: {'ancestor_count': 92, 'ancestor_ids': ['92_59', '95_89'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_79', 'origin': '92_59~CUW~95_89#MGNP'} Metrics: ['ELUC: -9.89195152441378', 'NSGA-II_crowding_distance: 0.16406755872985815', 'NSGA-II_rank: 1', 'change: 0.1327922871426057', 'is_elite: False']\n", + "Id: 96_96 Identity: {'ancestor_count': 93, 'ancestor_ids': ['92_59', '95_66'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_96', 'origin': '92_59~CUW~95_66#MGNP'} Metrics: ['ELUC: -9.943434224693702', 'NSGA-II_crowding_distance: 0.10776607864452664', 'NSGA-II_rank: 1', 'change: 0.1404086217736949', 'is_elite: False']\n", + "Id: 96_29 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_44', '95_28'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_29', 'origin': '95_44~CUW~95_28#MGNP'} Metrics: ['ELUC: -9.976391229247758', 'NSGA-II_crowding_distance: 0.5629782478477288', 'NSGA-II_rank: 4', 'change: 0.19368645268840537', 'is_elite: False']\n", + "Id: 96_38 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_73', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_38', 'origin': '95_73~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.26938712432825', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.27733674457685287', 'is_elite: False']\n", + "Id: 96_44 Identity: {'ancestor_count': 92, 'ancestor_ids': ['95_89', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_44', 'origin': '95_89~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.076431572869518', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2761780694242146', 'is_elite: False']\n", + "Id: 96_95 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_21', '95_73'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_95', 'origin': '95_21~CUW~95_73#MGNP'} Metrics: ['ELUC: -11.123888928710409', 'NSGA-II_crowding_distance: 0.2017073540025767', 'NSGA-II_rank: 2', 'change: 0.15644902347474482', 'is_elite: False']\n", + "Id: 92_59 Identity: {'ancestor_count': 90, 'ancestor_ids': ['90_46', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_59', 'origin': '90_46~CUW~91_38#MGNP'} Metrics: ['ELUC: -11.172578558551619', 'NSGA-II_crowding_distance: 0.17517011765521812', 'NSGA-II_rank: 1', 'change: 0.1432146479580922', 'is_elite: True']\n", + "Id: 96_39 Identity: {'ancestor_count': 93, 'ancestor_ids': ['1_1', '95_14'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_39', 'origin': '1_1~CUW~95_14#MGNP'} Metrics: ['ELUC: -11.348606773816023', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.2565069924290205', 'is_elite: False']\n", + "Id: 96_90 Identity: {'ancestor_count': 93, 'ancestor_ids': ['92_59', '95_28'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_90', 'origin': '92_59~CUW~95_28#MGNP'} Metrics: ['ELUC: -11.381507011473577', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.21162526936573692', 'is_elite: False']\n", + "Id: 96_31 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_22', '95_28'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_31', 'origin': '95_22~CUW~95_28#MGNP'} Metrics: ['ELUC: -12.006825603326996', 'NSGA-II_crowding_distance: 0.43895658928997594', 'NSGA-II_rank: 3', 'change: 0.1802009167038734', 'is_elite: False']\n", + "Id: 96_27 Identity: {'ancestor_count': 93, 'ancestor_ids': ['92_59', '95_73'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_27', 'origin': '92_59~CUW~95_73#MGNP'} Metrics: ['ELUC: -12.026527426309402', 'NSGA-II_crowding_distance: 0.20769472284606671', 'NSGA-II_rank: 2', 'change: 0.15916982005080327', 'is_elite: False']\n", + "Id: 96_78 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '95_89'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_78', 'origin': '95_28~CUW~95_89#MGNP'} Metrics: ['ELUC: -12.217245233550306', 'NSGA-II_crowding_distance: 0.3248784510922115', 'NSGA-II_rank: 2', 'change: 0.1880375487182184', 'is_elite: False']\n", + "Id: 96_47 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_16', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_47', 'origin': '95_16~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.245871137298673', 'NSGA-II_crowding_distance: 0.47211099934351397', 'NSGA-II_rank: 3', 'change: 0.20975846773288795', 'is_elite: False']\n", + "Id: 96_40 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_40', 'origin': '92_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.274301100244193', 'NSGA-II_crowding_distance: 0.2111441433951211', 'NSGA-II_rank: 1', 'change: 0.15311995192977024', 'is_elite: True']\n", + "Id: 96_42 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_89', '95_66'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_42', 'origin': '95_89~CUW~95_66#MGNP'} Metrics: ['ELUC: -12.849983080032562', 'NSGA-II_crowding_distance: 0.14219149431667807', 'NSGA-II_rank: 1', 'change: 0.17774928321586908', 'is_elite: False']\n", + "Id: 96_16 Identity: {'ancestor_count': 92, 'ancestor_ids': ['95_75', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_16', 'origin': '95_75~CUW~2_49#MGNP'} Metrics: ['ELUC: -13.111764460717643', 'NSGA-II_crowding_distance: 0.46960571652498273', 'NSGA-II_rank: 3', 'change: 0.2648440255339428', 'is_elite: False']\n", + "Id: 96_22 Identity: {'ancestor_count': 92, 'ancestor_ids': ['95_75', '95_29'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_22', 'origin': '95_75~CUW~95_29#MGNP'} Metrics: ['ELUC: -13.15209040324083', 'NSGA-II_crowding_distance: 0.08790105935216427', 'NSGA-II_rank: 1', 'change: 0.1806503700289454', 'is_elite: False']\n", + "Id: 96_80 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_73', '95_66'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_80', 'origin': '95_73~CUW~95_66#MGNP'} Metrics: ['ELUC: -13.63094181408581', 'NSGA-II_crowding_distance: 0.09700673732251663', 'NSGA-II_rank: 1', 'change: 0.190723890013065', 'is_elite: False']\n", + "Id: 95_28 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_43', '94_84'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_28', 'origin': '94_43~CUW~94_84#MGNP'} Metrics: ['ELUC: -13.85770476713698', 'NSGA-II_crowding_distance: 0.36179806230610545', 'NSGA-II_rank: 2', 'change: 0.20678739787945502', 'is_elite: False']\n", + "Id: 96_71 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_21', '95_16'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_71', 'origin': '95_21~CUW~95_16#MGNP'} Metrics: ['ELUC: -13.962534118030758', 'NSGA-II_crowding_distance: 0.1487927053202733', 'NSGA-II_rank: 1', 'change: 0.1958415389973254', 'is_elite: False']\n", + "Id: 96_52 Identity: {'ancestor_count': 91, 'ancestor_ids': ['95_93', '92_59'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_52', 'origin': '95_93~CUW~92_59#MGNP'} Metrics: ['ELUC: -14.105420699454745', 'NSGA-II_crowding_distance: 0.27712637194420786', 'NSGA-II_rank: 3', 'change: 0.28236656794598086', 'is_elite: False']\n", + "Id: 96_77 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_75'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_77', 'origin': '95_66~CUW~95_75#MGNP'} Metrics: ['ELUC: -14.724253128393913', 'NSGA-II_crowding_distance: 0.1825375101932027', 'NSGA-II_rank: 1', 'change: 0.21656648741467732', 'is_elite: True']\n", + "Id: 96_81 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '95_66'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_81', 'origin': '95_28~CUW~95_66#MGNP'} Metrics: ['ELUC: -14.833783072729814', 'NSGA-II_crowding_distance: 0.2904128568941569', 'NSGA-II_rank: 2', 'change: 0.2325053609408146', 'is_elite: False']\n", + "Id: 96_20 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_16', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_20', 'origin': '95_16~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.198462602177713', 'NSGA-II_crowding_distance: 0.18398718452057758', 'NSGA-II_rank: 3', 'change: 0.292619451386383', 'is_elite: False']\n", + "Id: 96_87 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_73'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_87', 'origin': '95_66~CUW~95_73#MGNP'} Metrics: ['ELUC: -15.291305786880047', 'NSGA-II_crowding_distance: 0.08215985493685038', 'NSGA-II_rank: 1', 'change: 0.22775699937100533', 'is_elite: False']\n", + "Id: 96_100 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_66'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_100', 'origin': '95_66~CUW~95_66#MGNP'} Metrics: ['ELUC: -15.365627491384604', 'NSGA-II_crowding_distance: 0.018202308725732023', 'NSGA-II_rank: 1', 'change: 0.23019683655303055', 'is_elite: False']\n", + "Id: 95_66 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_34', '94_17'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_66', 'origin': '94_34~CUW~94_17#MGNP'} Metrics: ['ELUC: -15.398390372665087', 'NSGA-II_crowding_distance: 0.07176490401937498', 'NSGA-II_rank: 1', 'change: 0.23137090422409945', 'is_elite: False']\n", + "Id: 96_13 Identity: {'ancestor_count': 93, 'ancestor_ids': ['92_59', '95_16'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_13', 'origin': '92_59~CUW~95_16#MGNP'} Metrics: ['ELUC: -15.698242375533994', 'NSGA-II_crowding_distance: 0.38959898704872975', 'NSGA-II_rank: 2', 'change: 0.24633347314096002', 'is_elite: False']\n", + "Id: 96_69 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_16', '95_66'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_69', 'origin': '95_16~CUW~95_66#MGNP'} Metrics: ['ELUC: -15.745731134763558', 'NSGA-II_crowding_distance: 0.09343281255989974', 'NSGA-II_rank: 1', 'change: 0.24515940862265445', 'is_elite: False']\n", + "Id: 96_56 Identity: {'ancestor_count': 4, 'ancestor_ids': ['95_93', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_56', 'origin': '95_93~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.884513463810498', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2948087681209373', 'is_elite: False']\n", + "Id: 95_16 Identity: {'ancestor_count': 92, 'ancestor_ids': ['94_70', '92_59'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_16', 'origin': '94_70~CUW~92_59#MGNP'} Metrics: ['ELUC: -15.92119232791008', 'NSGA-II_crowding_distance: 0.048921270292672236', 'NSGA-II_rank: 1', 'change: 0.2503770629918865', 'is_elite: False']\n", + "Id: 96_51 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_16', '95_16'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_51', 'origin': '95_16~CUW~95_16#MGNP'} Metrics: ['ELUC: -16.055986065578235', 'NSGA-II_crowding_distance: 0.04812937684722146', 'NSGA-II_rank: 1', 'change: 0.2544913036502784', 'is_elite: False']\n", + "Id: 96_89 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_16', '95_16'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_89', 'origin': '95_16~CUW~95_16#MGNP'} Metrics: ['ELUC: -16.223543490949037', 'NSGA-II_crowding_distance: 0.16447724017022472', 'NSGA-II_rank: 1', 'change: 0.25960680403807107', 'is_elite: True']\n", + "Id: 96_66 Identity: {'ancestor_count': 91, 'ancestor_ids': ['95_93', '92_59'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_66', 'origin': '95_93~CUW~92_59#MGNP'} Metrics: ['ELUC: -16.960147555300022', 'NSGA-II_crowding_distance: 0.329019986272128', 'NSGA-II_rank: 2', 'change: 0.29064140821787154', 'is_elite: False']\n", + "Id: 96_88 Identity: {'ancestor_count': 93, 'ancestor_ids': ['2_49', '95_66'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_88', 'origin': '2_49~CUW~95_66#MGNP'} Metrics: ['ELUC: -16.99993903056183', 'NSGA-II_crowding_distance: 0.1610038764056466', 'NSGA-II_rank: 1', 'change: 0.2875484739268961', 'is_elite: False']\n", + "Id: 96_74 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_14'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_74', 'origin': '95_66~CUW~95_14#MGNP'} Metrics: ['ELUC: -17.105491022556922', 'NSGA-II_crowding_distance: 0.04278146551942365', 'NSGA-II_rank: 1', 'change: 0.2926798512858949', 'is_elite: False']\n", + "Id: 96_54 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_21', '2_49'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_54', 'origin': '95_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.21250107280458', 'NSGA-II_crowding_distance: 0.09340150422859897', 'NSGA-II_rank: 2', 'change: 0.29960433254045826', 'is_elite: False']\n", + "Id: 96_72 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_73', '95_14'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_72', 'origin': '95_73~CUW~95_14#MGNP'} Metrics: ['ELUC: -17.315004068492676', 'NSGA-II_crowding_distance: 0.04033198710513322', 'NSGA-II_rank: 1', 'change: 0.2949667590395013', 'is_elite: False']\n", + "Id: 96_24 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_17', '95_93'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_24', 'origin': '95_17~CUW~95_93#MGNP'} Metrics: ['ELUC: -17.435583205426376', 'NSGA-II_crowding_distance: 0.035700538101623464', 'NSGA-II_rank: 1', 'change: 0.29911225134734776', 'is_elite: False']\n", + "Id: 96_18 Identity: {'ancestor_count': 4, 'ancestor_ids': ['95_93', '93_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_18', 'origin': '95_93~CUW~93_21#MGNP'} Metrics: ['ELUC: -17.54940371765138', 'NSGA-II_crowding_distance: 0.021565612297182773', 'NSGA-II_rank: 1', 'change: 0.30164116971948557', 'is_elite: False']\n", + "Id: 96_35 Identity: {'ancestor_count': 93, 'ancestor_ids': ['2_49', '95_28'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_35', 'origin': '2_49~CUW~95_28#MGNP'} Metrics: ['ELUC: -17.576827614090863', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30299326494742956', 'is_elite: False']\n", + "Id: 96_68 Identity: {'ancestor_count': 4, 'ancestor_ids': ['95_93', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_68', 'origin': '95_93~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.592557258216', 'NSGA-II_crowding_distance: 0.00734791247315274', 'NSGA-II_rank: 1', 'change: 0.30288305140343613', 'is_elite: False']\n", + "Id: 96_94 Identity: {'ancestor_count': 4, 'ancestor_ids': ['2_49', '95_93'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_94', 'origin': '2_49~CUW~95_93#MGNP'} Metrics: ['ELUC: -17.597329365544535', 'NSGA-II_crowding_distance: 0.0007352097021997288', 'NSGA-II_rank: 1', 'change: 0.30302031003474594', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 95_93 Identity: {'ancestor_count': 3, 'ancestor_ids': ['93_21', '2_49'], 'birth_generation': 95, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '95_93', 'origin': '93_21~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 96_26 Identity: {'ancestor_count': 4, 'ancestor_ids': ['2_49', '95_93'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_26', 'origin': '2_49~CUW~95_93#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 96_59 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_93'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_59', 'origin': '95_66~CUW~95_93#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 96_64 Identity: {'ancestor_count': 92, 'ancestor_ids': ['95_89', '95_93'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_64', 'origin': '95_89~CUW~95_93#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 96_92 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_14', '95_89'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_92', 'origin': '95_14~CUW~95_89#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 96.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 97...:\n", + "PopulationResponse:\n", + " Generation: 97\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/97/20240220-072238\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 97 and asking ESP for generation 98...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 97 data persisted.\n", + "Evaluated candidates:\n", + "Id: 97_83 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_83', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 20.445756473320554', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.29574631709092875', 'is_elite: False']\n", + "Id: 97_81 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_89', '96_45'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_81', 'origin': '96_89~CUW~96_45#MGNP'} Metrics: ['ELUC: 11.696246240155538', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.19305555234956048', 'is_elite: False']\n", + "Id: 97_58 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_77', '96_45'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_58', 'origin': '96_77~CUW~96_45#MGNP'} Metrics: ['ELUC: 6.449231575884901', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.18150181075388422', 'is_elite: False']\n", + "Id: 97_65 Identity: {'ancestor_count': 92, 'ancestor_ids': ['96_40', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_65', 'origin': '96_40~CUW~1_1#MGNP'} Metrics: ['ELUC: 4.035804119737962', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.13424599306952098', 'is_elite: False']\n", + "Id: 97_24 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_79', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_24', 'origin': '96_79~CUW~1_1#MGNP'} Metrics: ['ELUC: 1.7758631870881698', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.06543971497037661', 'is_elite: False']\n", + "Id: 97_68 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_68', 'origin': '96_63~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.9161822181746132', 'NSGA-II_crowding_distance: 0.24083023360991931', 'NSGA-II_rank: 2', 'change: 0.06745328576608585', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 97_71 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '96_45'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_71', 'origin': '1_1~CUW~96_45#MGNP'} Metrics: ['ELUC: -0.3604240760913372', 'NSGA-II_crowding_distance: 0.25364188098122986', 'NSGA-II_rank: 1', 'change: 0.040741660381582154', 'is_elite: True']\n", + "Id: 97_53 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '2_49'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_53', 'origin': '96_63~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 1.4872449836389459', 'NSGA-II_rank: 7', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 97_33 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_40', '96_63'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_33', 'origin': '96_40~CUW~96_63#MGNP'} Metrics: ['ELUC: -1.722580811292325', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09364566482889687', 'is_elite: False']\n", + "Id: 97_60 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_70', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_60', 'origin': '96_70~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.8194897806146977', 'NSGA-II_crowding_distance: 0.1603874732478078', 'NSGA-II_rank: 1', 'change: 0.04970189341180609', 'is_elite: False']\n", + "Id: 96_70 Identity: {'ancestor_count': 94, 'ancestor_ids': ['93_21', '95_21'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_70', 'origin': '93_21~CUW~95_21#MGNP'} Metrics: ['ELUC: -1.834295376605558', 'NSGA-II_crowding_distance: 0.07157496114681336', 'NSGA-II_rank: 1', 'change: 0.06358565789382868', 'is_elite: False']\n", + "Id: 97_82 Identity: {'ancestor_count': 94, 'ancestor_ids': ['1_1', '96_63'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_82', 'origin': '1_1~CUW~96_63#MGNP'} Metrics: ['ELUC: -1.9540678964670375', 'NSGA-II_crowding_distance: 0.27962902320329497', 'NSGA-II_rank: 2', 'change: 0.07678687706493705', 'is_elite: False']\n", + "Id: 97_86 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_21', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_86', 'origin': '95_21~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.153314181107614', 'NSGA-II_crowding_distance: 0.0768926693530302', 'NSGA-II_rank: 1', 'change: 0.06539316377480398', 'is_elite: False']\n", + "Id: 97_79 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_70', '96_41'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_79', 'origin': '96_70~CUW~96_41#MGNP'} Metrics: ['ELUC: -2.3385134736206554', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0825496536523281', 'is_elite: False']\n", + "Id: 97_34 Identity: {'ancestor_count': 93, 'ancestor_ids': ['1_1', '96_79'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_34', 'origin': '1_1~CUW~96_79#MGNP'} Metrics: ['ELUC: -2.8755080041300056', 'NSGA-II_crowding_distance: 0.1195671317932128', 'NSGA-II_rank: 1', 'change: 0.06885901767007262', 'is_elite: False']\n", + "Id: 97_67 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_42', '96_70'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_67', 'origin': '96_42~CUW~96_70#MGNP'} Metrics: ['ELUC: -3.260684289697171', 'NSGA-II_crowding_distance: 0.2994763423619998', 'NSGA-II_rank: 2', 'change: 0.08252343573438138', 'is_elite: False']\n", + "Id: 97_36 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '96_63'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_36', 'origin': '96_63~CUW~96_63#MGNP'} Metrics: ['ELUC: -3.462895317893026', 'NSGA-II_crowding_distance: 0.07780177790339701', 'NSGA-II_rank: 1', 'change: 0.07884533581133457', 'is_elite: False']\n", + "Id: 96_63 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_28', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_63', 'origin': '95_28~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.5992772241488318', 'NSGA-II_crowding_distance: 0.07672762846702552', 'NSGA-II_rank: 1', 'change: 0.07979074762891103', 'is_elite: False']\n", + "Id: 97_16 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '96_40'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_16', 'origin': '1_1~CUW~96_40#MGNP'} Metrics: ['ELUC: -3.772562503803663', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.11155170658065264', 'is_elite: False']\n", + "Id: 97_64 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '96_40'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_64', 'origin': '1_1~CUW~96_40#MGNP'} Metrics: ['ELUC: -3.849353127455924', 'NSGA-II_crowding_distance: 0.5696728310333495', 'NSGA-II_rank: 4', 'change: 0.10763179496793349', 'is_elite: False']\n", + "Id: 97_54 Identity: {'ancestor_count': 92, 'ancestor_ids': ['96_40', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_54', 'origin': '96_40~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.9495402247211984', 'NSGA-II_crowding_distance: 0.3161302352189425', 'NSGA-II_rank: 3', 'change: 0.0980978790763968', 'is_elite: False']\n", + "Id: 97_42 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_42', 'origin': '96_63~CUW~96_77#MGNP'} Metrics: ['ELUC: -4.349691119897946', 'NSGA-II_crowding_distance: 1.6802936152780967', 'NSGA-II_rank: 6', 'change: 0.14398243564761115', 'is_elite: False']\n", + "Id: 97_75 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_48', '96_41'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_75', 'origin': '96_48~CUW~96_41#MGNP'} Metrics: ['ELUC: -4.418123200110141', 'NSGA-II_crowding_distance: 0.22008332746977366', 'NSGA-II_rank: 1', 'change: 0.08552863869083295', 'is_elite: True']\n", + "Id: 97_21 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_70', '92_59'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_21', 'origin': '96_70~CUW~92_59#MGNP'} Metrics: ['ELUC: -5.115833924811461', 'NSGA-II_crowding_distance: 0.3836781404482556', 'NSGA-II_rank: 3', 'change: 0.10991222626055332', 'is_elite: False']\n", + "Id: 97_85 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_45', '96_88'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_85', 'origin': '96_45~CUW~96_88#MGNP'} Metrics: ['ELUC: -6.063254538930989', 'NSGA-II_crowding_distance: 0.9032258086965109', 'NSGA-II_rank: 7', 'change: 0.24571076378038378', 'is_elite: False']\n", + "Id: 97_26 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_89', '96_79'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_26', 'origin': '95_89~CUW~96_79#MGNP'} Metrics: ['ELUC: -6.1096588972323636', 'NSGA-II_crowding_distance: 0.34183946253593095', 'NSGA-II_rank: 2', 'change: 0.09683701089446385', 'is_elite: False']\n", + "Id: 97_96 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '96_71'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_96', 'origin': '1_1~CUW~96_71#MGNP'} Metrics: ['ELUC: -6.190730467210028', 'NSGA-II_crowding_distance: 0.43600264282589596', 'NSGA-II_rank: 4', 'change: 0.12788154609113558', 'is_elite: False']\n", + "Id: 97_15 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_89', '96_48'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_15', 'origin': '95_89~CUW~96_48#MGNP'} Metrics: ['ELUC: -6.471381186534317', 'NSGA-II_crowding_distance: 0.2908377184550765', 'NSGA-II_rank: 1', 'change: 0.09671821851914533', 'is_elite: True']\n", + "Id: 97_59 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_63', '96_71'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_59', 'origin': '96_63~CUW~96_71#MGNP'} Metrics: ['ELUC: -6.482409542619115', 'NSGA-II_crowding_distance: 1.2471041496954376', 'NSGA-II_rank: 5', 'change: 0.1350829824943043', 'is_elite: False']\n", + "Id: 97_87 Identity: {'ancestor_count': 92, 'ancestor_ids': ['1_1', '96_40'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_87', 'origin': '1_1~CUW~96_40#MGNP'} Metrics: ['ELUC: -7.242465289497459', 'NSGA-II_crowding_distance: 0.44198388010167766', 'NSGA-II_rank: 4', 'change: 0.1341704739591662', 'is_elite: False']\n", + "Id: 97_76 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_48', '96_70'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_76', 'origin': '96_48~CUW~96_70#MGNP'} Metrics: ['ELUC: -7.408344266153449', 'NSGA-II_crowding_distance: 0.19144812207878803', 'NSGA-II_rank: 2', 'change: 0.1127418332735542', 'is_elite: False']\n", + "Id: 97_23 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_48', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_23', 'origin': '96_48~CUW~1_1#MGNP'} Metrics: ['ELUC: -7.882366433232153', 'NSGA-II_crowding_distance: 0.5425097103311649', 'NSGA-II_rank: 3', 'change: 0.12292863723167839', 'is_elite: False']\n", + "Id: 97_30 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_41', '96_79'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_30', 'origin': '96_41~CUW~96_79#MGNP'} Metrics: ['ELUC: -8.008409823480504', 'NSGA-II_crowding_distance: 0.19932936080837232', 'NSGA-II_rank: 2', 'change: 0.11898093057993987', 'is_elite: False']\n", + "Id: 97_35 Identity: {'ancestor_count': 92, 'ancestor_ids': ['95_89', '1_1'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_35', 'origin': '95_89~CUW~1_1#MGNP'} Metrics: ['ELUC: -8.270062079336231', 'NSGA-II_crowding_distance: 0.15505697681783717', 'NSGA-II_rank: 1', 'change: 0.10693954255270609', 'is_elite: False']\n", + "Id: 97_70 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_48', '96_48'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_70', 'origin': '96_48~CUW~96_48#MGNP'} Metrics: ['ELUC: -8.288230858015817', 'NSGA-II_crowding_distance: 0.04327607729615263', 'NSGA-II_rank: 1', 'change: 0.11215126603992684', 'is_elite: False']\n", + "Id: 96_48 Identity: {'ancestor_count': 92, 'ancestor_ids': ['92_59', '95_89'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_48', 'origin': '92_59~CUW~95_89#MGNP'} Metrics: ['ELUC: -8.614004929316046', 'NSGA-II_crowding_distance: 0.06546100370515312', 'NSGA-II_rank: 1', 'change: 0.11401534342706965', 'is_elite: False']\n", + "Id: 97_61 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_88', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_61', 'origin': '96_88~CUW~96_77#MGNP'} Metrics: ['ELUC: -8.723875487427549', 'NSGA-II_crowding_distance: 1.2495690669402433', 'NSGA-II_rank: 6', 'change: 0.24495035930190825', 'is_elite: False']\n", + "Id: 97_17 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_48', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_17', 'origin': '96_48~CUW~96_77#MGNP'} Metrics: ['ELUC: -8.797046682738637', 'NSGA-II_crowding_distance: 0.05440452963935545', 'NSGA-II_rank: 1', 'change: 0.12304860935979918', 'is_elite: False']\n", + "Id: 97_92 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_92', '96_40'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_92', 'origin': '96_92~CUW~96_40#MGNP'} Metrics: ['ELUC: -8.845601998386508', 'NSGA-II_crowding_distance: 1.1918938094276164', 'NSGA-II_rank: 5', 'change: 0.22096138138215407', 'is_elite: False']\n", + "Id: 97_88 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_48', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_88', 'origin': '96_48~CUW~96_77#MGNP'} Metrics: ['ELUC: -8.924287971251267', 'NSGA-II_crowding_distance: 0.13720501842559293', 'NSGA-II_rank: 1', 'change: 0.12498284379149154', 'is_elite: False']\n", + "Id: 97_90 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_40', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_90', 'origin': '96_40~CUW~96_92#MGNP'} Metrics: ['ELUC: -9.018266366672608', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.3038959118205821', 'is_elite: False']\n", + "Id: 97_38 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_38', 'origin': '96_63~CUW~96_77#MGNP'} Metrics: ['ELUC: -9.049129926625488', 'NSGA-II_crowding_distance: 1.1208833419844046', 'NSGA-II_rank: 4', 'change: 0.16212343318951788', 'is_elite: False']\n", + "Id: 97_14 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_79', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_14', 'origin': '96_79~CUW~96_92#MGNP'} Metrics: ['ELUC: -9.100675678560812', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.29869772394332156', 'is_elite: False']\n", + "Id: 97_37 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_45', '96_88'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_37', 'origin': '96_45~CUW~96_88#MGNP'} Metrics: ['ELUC: -9.291634703586194', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.27524119765969385', 'is_elite: False']\n", + "Id: 97_55 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_40', '96_79'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_55', 'origin': '96_40~CUW~96_79#MGNP'} Metrics: ['ELUC: -9.734338194534812', 'NSGA-II_crowding_distance: 0.1659193622690649', 'NSGA-II_rank: 2', 'change: 0.1315013006229356', 'is_elite: False']\n", + "Id: 97_99 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_70', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_99', 'origin': '96_70~CUW~96_92#MGNP'} Metrics: ['ELUC: -9.884727860019776', 'NSGA-II_crowding_distance: 0.3197063847219031', 'NSGA-II_rank: 6', 'change: 0.2578516583674727', 'is_elite: False']\n", + "Id: 97_13 Identity: {'ancestor_count': 91, 'ancestor_ids': ['1_1', '92_59'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_13', 'origin': '1_1~CUW~92_59#MGNP'} Metrics: ['ELUC: -10.032965398986345', 'NSGA-II_crowding_distance: 0.04431089625395912', 'NSGA-II_rank: 2', 'change: 0.1335078410004446', 'is_elite: False']\n", + "Id: 97_47 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_48', '96_79'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_47', 'origin': '96_48~CUW~96_79#MGNP'} Metrics: ['ELUC: -10.109191736400344', 'NSGA-II_crowding_distance: 0.09416332934334906', 'NSGA-II_rank: 2', 'change: 0.13742173717307835', 'is_elite: False']\n", + "Id: 97_41 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_89', '96_48'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_41', 'origin': '96_89~CUW~96_48#MGNP'} Metrics: ['ELUC: -10.189242120642373', 'NSGA-II_crowding_distance: 0.46516543250609954', 'NSGA-II_rank: 3', 'change: 0.15228890483999', 'is_elite: False']\n", + "Id: 97_12 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_48', '2_49'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_12', 'origin': '96_48~CUW~2_49#MGNP'} Metrics: ['ELUC: -10.317245574543218', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.29865780556211513', 'is_elite: False']\n", + "Id: 97_84 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '96_48'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_84', 'origin': '96_63~CUW~96_48#MGNP'} Metrics: ['ELUC: -10.612444034987991', 'NSGA-II_crowding_distance: 0.56794160666171', 'NSGA-II_rank: 3', 'change: 0.18341234335052492', 'is_elite: False']\n", + "Id: 97_93 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_48', '96_40'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_93', 'origin': '96_48~CUW~96_40#MGNP'} Metrics: ['ELUC: -10.738859096649621', 'NSGA-II_crowding_distance: 0.31447867252521844', 'NSGA-II_rank: 2', 'change: 0.14720526396960512', 'is_elite: False']\n", + "Id: 97_91 Identity: {'ancestor_count': 94, 'ancestor_ids': ['92_59', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_91', 'origin': '92_59~CUW~96_77#MGNP'} Metrics: ['ELUC: -10.913423093624301', 'NSGA-II_crowding_distance: 0.18897520011663105', 'NSGA-II_rank: 1', 'change: 0.1280719692662282', 'is_elite: True']\n", + "Id: 92_59 Identity: {'ancestor_count': 90, 'ancestor_ids': ['90_46', '91_38'], 'birth_generation': 92, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '92_59', 'origin': '90_46~CUW~91_38#MGNP'} Metrics: ['ELUC: -11.172578558551619', 'NSGA-II_crowding_distance: 0.10638001058769656', 'NSGA-II_rank: 1', 'change: 0.1432146479580922', 'is_elite: False']\n", + "Id: 97_72 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_70', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_72', 'origin': '96_70~CUW~96_92#MGNP'} Metrics: ['ELUC: -11.185154233556949', 'NSGA-II_crowding_distance: 0.7528958503045624', 'NSGA-II_rank: 5', 'change: 0.2417855778081032', 'is_elite: False']\n", + "Id: 97_51 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_48', '96_45'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_51', 'origin': '96_48~CUW~96_45#MGNP'} Metrics: ['ELUC: -11.366409988097082', 'NSGA-II_crowding_distance: 0.09585794662908978', 'NSGA-II_rank: 1', 'change: 0.1521260664851419', 'is_elite: False']\n", + "Id: 97_39 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '96_63'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_39', 'origin': '2_49~CUW~96_63#MGNP'} Metrics: ['ELUC: -11.564745047221894', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.26817691505763763', 'is_elite: False']\n", + "Id: 97_66 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_70', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_66', 'origin': '96_70~CUW~96_92#MGNP'} Metrics: ['ELUC: -11.65741694523842', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.26214593627868465', 'is_elite: False']\n", + "Id: 97_40 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_71', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_40', 'origin': '96_71~CUW~96_92#MGNP'} Metrics: ['ELUC: -11.816395658229807', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2607106038616307', 'is_elite: False']\n", + "Id: 97_48 Identity: {'ancestor_count': 94, 'ancestor_ids': ['95_89', '96_89'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_48', 'origin': '95_89~CUW~96_89#MGNP'} Metrics: ['ELUC: -12.196560527598908', 'NSGA-II_crowding_distance: 0.28942179821024233', 'NSGA-II_rank: 2', 'change: 0.186491477275196', 'is_elite: False']\n", + "Id: 96_40 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_40', 'origin': '92_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.274301100244193', 'NSGA-II_crowding_distance: 0.18349076683053772', 'NSGA-II_rank: 1', 'change: 0.15311995192977024', 'is_elite: True']\n", + "Id: 97_27 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '96_89'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_27', 'origin': '96_63~CUW~96_89#MGNP'} Metrics: ['ELUC: -12.689336604707693', 'NSGA-II_crowding_distance: 0.21781210306326737', 'NSGA-II_rank: 2', 'change: 0.19200312145748324', 'is_elite: False']\n", + "Id: 97_100 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_77', '96_71'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_100', 'origin': '96_77~CUW~96_71#MGNP'} Metrics: ['ELUC: -12.832583091971838', 'NSGA-II_crowding_distance: 0.2066666037337031', 'NSGA-II_rank: 1', 'change: 0.18199421270039506', 'is_elite: True']\n", + "Id: 97_74 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_74', 'origin': '96_63~CUW~96_92#MGNP'} Metrics: ['ELUC: -13.039435640868954', 'NSGA-II_crowding_distance: 0.9883432888649726', 'NSGA-II_rank: 4', 'change: 0.23934228291769327', 'is_elite: False']\n", + "Id: 97_49 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_49', 'origin': '2_49~CUW~96_77#MGNP'} Metrics: ['ELUC: -13.82336302187837', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.25893173831748967', 'is_elite: False']\n", + "Id: 97_77 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_71', '96_41'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_77', 'origin': '96_71~CUW~96_41#MGNP'} Metrics: ['ELUC: -13.885686531009341', 'NSGA-II_crowding_distance: 0.18107954141318955', 'NSGA-II_rank: 1', 'change: 0.1874389534517673', 'is_elite: True']\n", + "Id: 97_98 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_63', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_98', 'origin': '96_63~CUW~96_92#MGNP'} Metrics: ['ELUC: -14.32566449259358', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.25277533859233486', 'is_elite: False']\n", + "Id: 97_22 Identity: {'ancestor_count': 94, 'ancestor_ids': ['92_59', '96_89'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_22', 'origin': '92_59~CUW~96_89#MGNP'} Metrics: ['ELUC: -14.422103155565596', 'NSGA-II_crowding_distance: 0.11253378408067907', 'NSGA-II_rank: 1', 'change: 0.20904966706878483', 'is_elite: False']\n", + "Id: 97_46 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_71', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_46', 'origin': '96_71~CUW~96_77#MGNP'} Metrics: ['ELUC: -14.46520072286889', 'NSGA-II_crowding_distance: 0.7701056823762297', 'NSGA-II_rank: 3', 'change: 0.21208432227462173', 'is_elite: False']\n", + "Id: 97_19 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_79', '96_89'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_19', 'origin': '96_79~CUW~96_89#MGNP'} Metrics: ['ELUC: -14.479996816069114', 'NSGA-II_crowding_distance: 0.2086749894180547', 'NSGA-II_rank: 2', 'change: 0.21016845330068618', 'is_elite: False']\n", + "Id: 97_32 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_77', '96_45'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_32', 'origin': '96_77~CUW~96_45#MGNP'} Metrics: ['ELUC: -14.571133136422093', 'NSGA-II_crowding_distance: 0.041963367931908316', 'NSGA-II_rank: 1', 'change: 0.20938428660902686', 'is_elite: False']\n", + "Id: 97_73 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_88', '2_49'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_73', 'origin': '96_88~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.589211717020513', 'NSGA-II_crowding_distance: 0.44401567315933643', 'NSGA-II_rank: 3', 'change: 0.2916406604161868', 'is_elite: False']\n", + "Id: 96_77 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_66', '95_75'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_77', 'origin': '95_66~CUW~95_75#MGNP'} Metrics: ['ELUC: -14.724253128393913', 'NSGA-II_crowding_distance: 0.3784099774507762', 'NSGA-II_rank: 2', 'change: 0.21656648741467732', 'is_elite: False']\n", + "Id: 97_95 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_71', '96_89'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_95', 'origin': '96_71~CUW~96_89#MGNP'} Metrics: ['ELUC: -14.820804227202576', 'NSGA-II_crowding_distance: 0.055654595528287734', 'NSGA-II_rank: 1', 'change: 0.2148045208271645', 'is_elite: False']\n", + "Id: 97_97 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_89', '95_21'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_97', 'origin': '96_89~CUW~95_21#MGNP'} Metrics: ['ELUC: -15.027928158498295', 'NSGA-II_crowding_distance: 0.0848612063004127', 'NSGA-II_rank: 1', 'change: 0.218238425322931', 'is_elite: False']\n", + "Id: 97_78 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_89', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_78', 'origin': '96_89~CUW~96_77#MGNP'} Metrics: ['ELUC: -15.253559361852359', 'NSGA-II_crowding_distance: 0.1724690717181273', 'NSGA-II_rank: 1', 'change: 0.23278122560577721', 'is_elite: False']\n", + "Id: 97_94 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_94', 'origin': '2_49~CUW~96_92#MGNP'} Metrics: ['ELUC: -15.598430153330064', 'NSGA-II_crowding_distance: 0.19916349757396', 'NSGA-II_rank: 3', 'change: 0.29177075858618734', 'is_elite: False']\n", + "Id: 97_18 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_92', '96_88'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_18', 'origin': '96_92~CUW~96_88#MGNP'} Metrics: ['ELUC: -15.950716704912299', 'NSGA-II_crowding_distance: 0.39055869235985075', 'NSGA-II_rank: 2', 'change: 0.28202507078116684', 'is_elite: False']\n", + "Id: 97_31 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_89', '96_40'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_31', 'origin': '96_89~CUW~96_40#MGNP'} Metrics: ['ELUC: -15.98769399238258', 'NSGA-II_crowding_distance: 0.14507285878226478', 'NSGA-II_rank: 1', 'change: 0.2534118307722018', 'is_elite: False']\n", + "Id: 97_62 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_42', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_62', 'origin': '96_42~CUW~96_92#MGNP'} Metrics: ['ELUC: -16.197270755791955', 'NSGA-II_crowding_distance: 0.11736404779458402', 'NSGA-II_rank: 2', 'change: 0.29128284743790844', 'is_elite: False']\n", + "Id: 96_89 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_16', '95_16'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_89', 'origin': '95_16~CUW~95_16#MGNP'} Metrics: ['ELUC: -16.223543490949037', 'NSGA-II_crowding_distance: 0.06087740833721321', 'NSGA-II_rank: 1', 'change: 0.25960680403807107', 'is_elite: False']\n", + "Id: 97_20 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_89', '92_59'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_20', 'origin': '96_89~CUW~92_59#MGNP'} Metrics: ['ELUC: -16.369646965206343', 'NSGA-II_crowding_distance: 0.08316278890536141', 'NSGA-II_rank: 1', 'change: 0.2650944330743565', 'is_elite: False']\n", + "Id: 97_52 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_92', '96_79'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_52', 'origin': '96_92~CUW~96_79#MGNP'} Metrics: ['ELUC: -16.66389842443006', 'NSGA-II_crowding_distance: 0.0947622083356071', 'NSGA-II_rank: 1', 'change: 0.2769477679881177', 'is_elite: False']\n", + "Id: 97_45 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_92', '96_63'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_45', 'origin': '96_92~CUW~96_63#MGNP'} Metrics: ['ELUC: -16.751201320748496', 'NSGA-II_crowding_distance: 0.10573950762844077', 'NSGA-II_rank: 1', 'change: 0.2868942692101207', 'is_elite: False']\n", + "Id: 97_63 Identity: {'ancestor_count': 92, 'ancestor_ids': ['96_40', '2_49'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_63', 'origin': '96_40~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.93048070562138', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.30006148535247307', 'is_elite: False']\n", + "Id: 97_50 Identity: {'ancestor_count': 94, 'ancestor_ids': ['1_1', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_50', 'origin': '1_1~CUW~96_92#MGNP'} Metrics: ['ELUC: -16.95236819696315', 'NSGA-II_crowding_distance: 0.11950713034873098', 'NSGA-II_rank: 2', 'change: 0.29759798675320115', 'is_elite: False']\n", + "Id: 97_57 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_45', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_57', 'origin': '96_45~CUW~96_92#MGNP'} Metrics: ['ELUC: -17.36913192777438', 'NSGA-II_crowding_distance: 0.09572683349670255', 'NSGA-II_rank: 1', 'change: 0.2965300507111573', 'is_elite: False']\n", + "Id: 97_89 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '96_63'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_89', 'origin': '2_49~CUW~96_63#MGNP'} Metrics: ['ELUC: -17.530583172387193', 'NSGA-II_crowding_distance: 0.031241529570589836', 'NSGA-II_rank: 1', 'change: 0.30223067279028093', 'is_elite: False']\n", + "Id: 97_25 Identity: {'ancestor_count': 93, 'ancestor_ids': ['2_49', '96_48'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_25', 'origin': '2_49~CUW~96_48#MGNP'} Metrics: ['ELUC: -17.540457798131477', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3031620087579066', 'is_elite: False']\n", + "Id: 97_80 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '2_49'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_80', 'origin': '92_59~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.57448688993966', 'NSGA-II_crowding_distance: 0.006088845489812762', 'NSGA-II_rank: 1', 'change: 0.3023668899061998', 'is_elite: False']\n", + "Id: 97_56 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_92', '96_71'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_56', 'origin': '96_92~CUW~96_71#MGNP'} Metrics: ['ELUC: -17.595119262424816', 'NSGA-II_crowding_distance: 0.003486956506134109', 'NSGA-II_rank: 1', 'change: 0.3029522512548144', 'is_elite: False']\n", + "Id: 97_11 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_11', 'origin': '2_49~CUW~96_92#MGNP'} Metrics: ['ELUC: -17.597319895662338', 'NSGA-II_crowding_distance: 0.00035757475528009025', 'NSGA-II_rank: 1', 'change: 0.30301983687510553', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 96_92 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_14', '95_89'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_92', 'origin': '95_14~CUW~95_89#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 97_28 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '96_88'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_28', 'origin': '2_49~CUW~96_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 97_29 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_29', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 97_43 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_92', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_43', 'origin': '96_92~CUW~96_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 97_44 Identity: {'ancestor_count': 94, 'ancestor_ids': ['96_92', '96_92'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_44', 'origin': '96_92~CUW~96_92#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 97_69 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '96_88'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_69', 'origin': '2_49~CUW~96_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 97.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 98...:\n", + "PopulationResponse:\n", + " Generation: 98\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/98/20240220-072954\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 98 and asking ESP for generation 99...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 98 data persisted.\n", + "Evaluated candidates:\n", + "Id: 98_73 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '97_15'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_73', 'origin': '2_49~CUW~97_15#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 98_81 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_69', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_81', 'origin': '97_69~CUW~97_71#MGNP'} Metrics: ['ELUC: 10.01800184777827', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.2761269967420403', 'is_elite: False']\n", + "Id: 98_87 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '97_22'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_87', 'origin': '1_1~CUW~97_22#MGNP'} Metrics: ['ELUC: 8.89054091790573', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.17472526922481288', 'is_elite: False']\n", + "Id: 98_30 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_60', '97_77'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_30', 'origin': '97_60~CUW~97_77#MGNP'} Metrics: ['ELUC: 5.712015570888127', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.1594777158221917', 'is_elite: False']\n", + "Id: 98_17 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '96_40'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_17', 'origin': '97_71~CUW~96_40#MGNP'} Metrics: ['ELUC: 4.981388430171198', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.14218040522715916', 'is_elite: False']\n", + "Id: 98_26 Identity: {'ancestor_count': 92, 'ancestor_ids': ['96_40', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_26', 'origin': '96_40~CUW~1_1#MGNP'} Metrics: ['ELUC: 3.5081861258242895', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09915204869016317', 'is_elite: False']\n", + "Id: 98_38 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_69'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_38', 'origin': '97_91~CUW~97_69#MGNP'} Metrics: ['ELUC: 2.426090375960939', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.34874926060765', 'is_elite: False']\n", + "Id: 98_88 Identity: {'ancestor_count': 96, 'ancestor_ids': ['96_40', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_88', 'origin': '96_40~CUW~97_71#MGNP'} Metrics: ['ELUC: 2.1836323735958767', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1414424859159297', 'is_elite: False']\n", + "Id: 98_93 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_88', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_93', 'origin': '97_88~CUW~2_49#MGNP'} Metrics: ['ELUC: 1.8137457094654532', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.31491769109670065', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 98_44 Identity: {'ancestor_count': 94, 'ancestor_ids': ['1_1', '97_34'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_44', 'origin': '1_1~CUW~97_34#MGNP'} Metrics: ['ELUC: -0.1258676937803788', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.03736650941732167', 'is_elite: False']\n", + "Id: 97_71 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '96_45'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_71', 'origin': '1_1~CUW~96_45#MGNP'} Metrics: ['ELUC: -0.3604240760913372', 'NSGA-II_crowding_distance: 0.06439443078998963', 'NSGA-II_rank: 2', 'change: 0.040741660381582154', 'is_elite: False']\n", + "Id: 98_12 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '97_69'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_12', 'origin': '97_71~CUW~97_69#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.5057126820947284', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 98_61 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_51', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_61', 'origin': '97_51~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: 0.8297107846102525', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 98_98 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_77', '97_69'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_98', 'origin': '97_77~CUW~97_69#MGNP'} Metrics: ['ELUC: -0.5755881714630294', 'NSGA-II_crowding_distance: 0.667218803006349', 'NSGA-II_rank: 9', 'change: 0.23886407528335385', 'is_elite: False']\n", + "Id: 98_21 Identity: {'ancestor_count': 92, 'ancestor_ids': ['2_49', '96_40'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_21', 'origin': '2_49~CUW~96_40#MGNP'} Metrics: ['ELUC: -0.5992495123226738', 'NSGA-II_crowding_distance: 1.1859212312297247', 'NSGA-II_rank: 8', 'change: 0.237140773128997', 'is_elite: False']\n", + "Id: 98_92 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_92', 'origin': '97_71~CUW~97_71#MGNP'} Metrics: ['ELUC: -0.6058932756600052', 'NSGA-II_crowding_distance: 0.3163762773757961', 'NSGA-II_rank: 2', 'change: 0.044481951734658846', 'is_elite: False']\n", + "Id: 98_95 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_95', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.6513205168159917', 'NSGA-II_crowding_distance: 0.21494345018077698', 'NSGA-II_rank: 1', 'change: 0.03577040039430552', 'is_elite: False']\n", + "Id: 98_58 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_58', 'origin': '97_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5718506229939717', 'NSGA-II_crowding_distance: 0.2667570805722589', 'NSGA-II_rank: 1', 'change: 0.0423576568990015', 'is_elite: True']\n", + "Id: 98_22 Identity: {'ancestor_count': 96, 'ancestor_ids': ['2_49', '97_60'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_22', 'origin': '2_49~CUW~97_60#MGNP'} Metrics: ['ELUC: -1.6343378798432728', 'NSGA-II_crowding_distance: 0.9272658331165831', 'NSGA-II_rank: 8', 'change: 0.2410364599876382', 'is_elite: False']\n", + "Id: 98_80 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_80', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -1.858519454846362', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.3167135424471401', 'is_elite: False']\n", + "Id: 98_83 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_31', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_83', 'origin': '97_31~CUW~97_71#MGNP'} Metrics: ['ELUC: -1.9512278120984319', 'NSGA-II_crowding_distance: 1.5017320344801381', 'NSGA-II_rank: 7', 'change: 0.16731542198467028', 'is_elite: False']\n", + "Id: 98_75 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_60', '97_15'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_75', 'origin': '97_60~CUW~97_15#MGNP'} Metrics: ['ELUC: -2.229522932369151', 'NSGA-II_crowding_distance: 0.4459351855503905', 'NSGA-II_rank: 2', 'change: 0.08395045573252487', 'is_elite: False']\n", + "Id: 98_94 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_15', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_94', 'origin': '97_15~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.9679427883733043', 'NSGA-II_crowding_distance: 0.2985988215293388', 'NSGA-II_rank: 1', 'change: 0.07605097453140519', 'is_elite: True']\n", + "Id: 98_69 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_75', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_69', 'origin': '97_75~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.162145658024953', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.08772118599933826', 'is_elite: False']\n", + "Id: 98_34 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '97_15'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_34', 'origin': '97_71~CUW~97_15#MGNP'} Metrics: ['ELUC: -3.2232478116815386', 'NSGA-II_crowding_distance: 0.24479832606067542', 'NSGA-II_rank: 4', 'change: 0.08872212499794242', 'is_elite: False']\n", + "Id: 98_96 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_75', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_96', 'origin': '97_75~CUW~97_75#MGNP'} Metrics: ['ELUC: -3.6256801573648842', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.08762695435381505', 'is_elite: False']\n", + "Id: 98_97 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_51', '97_77'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_97', 'origin': '97_51~CUW~97_77#MGNP'} Metrics: ['ELUC: -4.226770558393278', 'NSGA-II_crowding_distance: 0.22457698910228813', 'NSGA-II_rank: 3', 'change: 0.09637835261553634', 'is_elite: False']\n", + "Id: 97_75 Identity: {'ancestor_count': 93, 'ancestor_ids': ['96_48', '96_41'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_75', 'origin': '96_48~CUW~96_41#MGNP'} Metrics: ['ELUC: -4.418123200110141', 'NSGA-II_crowding_distance: 0.31187211627941047', 'NSGA-II_rank: 2', 'change: 0.08552863869083295', 'is_elite: False']\n", + "Id: 98_76 Identity: {'ancestor_count': 96, 'ancestor_ids': ['1_1', '97_77'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_76', 'origin': '1_1~CUW~97_77#MGNP'} Metrics: ['ELUC: -4.484565408474026', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.13505144774182254', 'is_elite: False']\n", + "Id: 98_64 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_34'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_64', 'origin': '97_91~CUW~97_34#MGNP'} Metrics: ['ELUC: -4.502610343156271', 'NSGA-II_crowding_distance: 0.22993430550108346', 'NSGA-II_rank: 1', 'change: 0.08171699516428786', 'is_elite: False']\n", + "Id: 98_36 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_35', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_36', 'origin': '97_35~CUW~97_75#MGNP'} Metrics: ['ELUC: -4.9922189124163685', 'NSGA-II_crowding_distance: 0.3098994538270376', 'NSGA-II_rank: 4', 'change: 0.09846509375172335', 'is_elite: False']\n", + "Id: 98_45 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_45', 'origin': '97_71~CUW~97_75#MGNP'} Metrics: ['ELUC: -5.0657549384945755', 'NSGA-II_crowding_distance: 0.09413973219574931', 'NSGA-II_rank: 3', 'change: 0.09664005950362439', 'is_elite: False']\n", + "Id: 98_79 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_75', '97_15'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_79', 'origin': '97_75~CUW~97_15#MGNP'} Metrics: ['ELUC: -5.072643360111043', 'NSGA-II_crowding_distance: 0.06693587637621297', 'NSGA-II_rank: 3', 'change: 0.09689897391383132', 'is_elite: False']\n", + "Id: 98_20 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_15', '96_40'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_20', 'origin': '97_15~CUW~96_40#MGNP'} Metrics: ['ELUC: -5.621164919173318', 'NSGA-II_crowding_distance: 1.0588913447459072', 'NSGA-II_rank: 5', 'change: 0.10418861662607767', 'is_elite: False']\n", + "Id: 98_84 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '97_35'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_84', 'origin': '97_71~CUW~97_35#MGNP'} Metrics: ['ELUC: -5.66268858940424', 'NSGA-II_crowding_distance: 0.5649121222807667', 'NSGA-II_rank: 4', 'change: 0.09978522417275758', 'is_elite: False']\n", + "Id: 98_40 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_15', '97_35'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_40', 'origin': '97_15~CUW~97_35#MGNP'} Metrics: ['ELUC: -5.666333774588521', 'NSGA-II_crowding_distance: 0.19912274825956583', 'NSGA-II_rank: 3', 'change: 0.09702179383735017', 'is_elite: False']\n", + "Id: 98_70 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_15', '97_60'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_70', 'origin': '97_15~CUW~97_60#MGNP'} Metrics: ['ELUC: -5.898619883622811', 'NSGA-II_crowding_distance: 0.20312331221071367', 'NSGA-II_rank: 2', 'change: 0.09574723660689254', 'is_elite: False']\n", + "Id: 98_52 Identity: {'ancestor_count': 93, 'ancestor_ids': ['97_35', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_52', 'origin': '97_35~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.305008828084003', 'NSGA-II_crowding_distance: 0.16225029198512897', 'NSGA-II_rank: 1', 'change: 0.08802720799239075', 'is_elite: False']\n", + "Id: 97_15 Identity: {'ancestor_count': 93, 'ancestor_ids': ['95_89', '96_48'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_15', 'origin': '95_89~CUW~96_48#MGNP'} Metrics: ['ELUC: -6.471381186534317', 'NSGA-II_crowding_distance: 0.07932616490368971', 'NSGA-II_rank: 1', 'change: 0.09671821851914533', 'is_elite: False']\n", + "Id: 98_35 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_75', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_35', 'origin': '97_75~CUW~97_75#MGNP'} Metrics: ['ELUC: -6.5180492129431755', 'NSGA-II_crowding_distance: 0.10082817496421503', 'NSGA-II_rank: 2', 'change: 0.09809745925993414', 'is_elite: False']\n", + "Id: 98_68 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_35', '97_15'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_68', 'origin': '97_35~CUW~97_15#MGNP'} Metrics: ['ELUC: -6.576669577270496', 'NSGA-II_crowding_distance: 0.34439284271943', 'NSGA-II_rank: 3', 'change: 0.10183520606885813', 'is_elite: False']\n", + "Id: 98_53 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_69', '97_60'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_53', 'origin': '97_69~CUW~97_60#MGNP'} Metrics: ['ELUC: -6.670601996990825', 'NSGA-II_crowding_distance: 1.4756535891062994', 'NSGA-II_rank: 7', 'change: 0.2540642741410822', 'is_elite: False']\n", + "Id: 98_82 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_82', 'origin': '97_91~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.671687248383367', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.30209052617779936', 'is_elite: False']\n", + "Id: 98_90 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_90', 'origin': '2_49~CUW~97_75#MGNP'} Metrics: ['ELUC: -7.050825159954517', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.2475723776713392', 'is_elite: False']\n", + "Id: 98_86 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_15', '97_35'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_86', 'origin': '97_15~CUW~97_35#MGNP'} Metrics: ['ELUC: -7.0591602099345545', 'NSGA-II_crowding_distance: 0.14744812069649052', 'NSGA-II_rank: 2', 'change: 0.09999406365875342', 'is_elite: False']\n", + "Id: 98_48 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_35', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_48', 'origin': '97_35~CUW~97_75#MGNP'} Metrics: ['ELUC: -7.1157774334607815', 'NSGA-II_crowding_distance: 0.16844109982741604', 'NSGA-II_rank: 1', 'change: 0.09793737468025905', 'is_elite: False']\n", + "Id: 98_32 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_15'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_32', 'origin': '97_91~CUW~97_15#MGNP'} Metrics: ['ELUC: -7.614465187620102', 'NSGA-II_crowding_distance: 0.2938518664261696', 'NSGA-II_rank: 3', 'change: 0.1143436864608755', 'is_elite: False']\n", + "Id: 98_72 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_77', '97_35'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_72', 'origin': '97_77~CUW~97_35#MGNP'} Metrics: ['ELUC: -7.779896803567912', 'NSGA-II_crowding_distance: 0.15390958008367184', 'NSGA-II_rank: 2', 'change: 0.11164697653385326', 'is_elite: False']\n", + "Id: 98_100 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_15', '97_88'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_100', 'origin': '97_15~CUW~97_88#MGNP'} Metrics: ['ELUC: -8.263144155407335', 'NSGA-II_crowding_distance: 0.28414751100191327', 'NSGA-II_rank: 3', 'change: 0.11628905043754915', 'is_elite: False']\n", + "Id: 98_85 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_35', '97_15'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_85', 'origin': '97_35~CUW~97_15#MGNP'} Metrics: ['ELUC: -8.409950904711271', 'NSGA-II_crowding_distance: 0.15700171240853952', 'NSGA-II_rank: 2', 'change: 0.11357006172054744', 'is_elite: False']\n", + "Id: 98_71 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_88', '97_77'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_71', 'origin': '97_88~CUW~97_77#MGNP'} Metrics: ['ELUC: -8.575486259616525', 'NSGA-II_crowding_distance: 0.7737683332330458', 'NSGA-II_rank: 5', 'change: 0.13344717483507643', 'is_elite: False']\n", + "Id: 98_65 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_88'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_65', 'origin': '97_91~CUW~97_88#MGNP'} Metrics: ['ELUC: -8.6486991823518', 'NSGA-II_crowding_distance: 0.1840453555357024', 'NSGA-II_rank: 1', 'change: 0.11002753152368297', 'is_elite: False']\n", + "Id: 98_39 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_88', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_39', 'origin': '97_88~CUW~97_71#MGNP'} Metrics: ['ELUC: -8.826342536464724', 'NSGA-II_crowding_distance: 0.8858240034962055', 'NSGA-II_rank: 4', 'change: 0.13130740972509528', 'is_elite: False']\n", + "Id: 98_43 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_40', '97_88'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_43', 'origin': '96_40~CUW~97_88#MGNP'} Metrics: ['ELUC: -9.07697363152667', 'NSGA-II_crowding_distance: 0.3934643313985103', 'NSGA-II_rank: 3', 'change: 0.13058330138415158', 'is_elite: False']\n", + "Id: 98_27 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '97_91'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_27', 'origin': '1_1~CUW~97_91#MGNP'} Metrics: ['ELUC: -9.131990059329668', 'NSGA-II_crowding_distance: 0.12655275485746048', 'NSGA-II_rank: 2', 'change: 0.12593131609724492', 'is_elite: False']\n", + "Id: 98_89 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '97_22'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_89', 'origin': '1_1~CUW~97_22#MGNP'} Metrics: ['ELUC: -9.135923075950611', 'NSGA-II_crowding_distance: 0.423201654813703', 'NSGA-II_rank: 3', 'change: 0.15427494893323557', 'is_elite: False']\n", + "Id: 98_91 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_35', '97_15'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_91', 'origin': '97_35~CUW~97_15#MGNP'} Metrics: ['ELUC: -9.194112634374722', 'NSGA-II_crowding_distance: 0.18928189912116722', 'NSGA-II_rank: 1', 'change: 0.1175824183703507', 'is_elite: False']\n", + "Id: 98_54 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_54', 'origin': '97_91~CUW~97_75#MGNP'} Metrics: ['ELUC: -9.194633500072369', 'NSGA-II_crowding_distance: 0.07233146984619655', 'NSGA-II_rank: 2', 'change: 0.13022955882579584', 'is_elite: False']\n", + "Id: 98_67 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_31', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_67', 'origin': '97_31~CUW~97_71#MGNP'} Metrics: ['ELUC: -9.44300275647195', 'NSGA-II_crowding_distance: 0.9411086552540928', 'NSGA-II_rank: 5', 'change: 0.19247341418832176', 'is_elite: False']\n", + "Id: 98_49 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_15', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_49', 'origin': '97_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -9.529563093370895', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.2924480033651662', 'is_elite: False']\n", + "Id: 98_77 Identity: {'ancestor_count': 96, 'ancestor_ids': ['96_40', '97_60'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_77', 'origin': '96_40~CUW~97_60#MGNP'} Metrics: ['ELUC: -9.761635554911603', 'NSGA-II_crowding_distance: 0.1491391368662778', 'NSGA-II_rank: 2', 'change: 0.13239872364737415', 'is_elite: False']\n", + "Id: 98_31 Identity: {'ancestor_count': 96, 'ancestor_ids': ['2_49', '97_60'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_31', 'origin': '2_49~CUW~97_60#MGNP'} Metrics: ['ELUC: -10.099711894486086', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.2757684887489425', 'is_elite: False']\n", + "Id: 98_13 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_69', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_13', 'origin': '97_69~CUW~97_71#MGNP'} Metrics: ['ELUC: -10.46894228639326', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.27560405285838413', 'is_elite: False']\n", + "Id: 98_23 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '97_22'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_23', 'origin': '1_1~CUW~97_22#MGNP'} Metrics: ['ELUC: -10.78102332774043', 'NSGA-II_crowding_distance: 1.1902895516585579', 'NSGA-II_rank: 4', 'change: 0.16977630684070522', 'is_elite: False']\n", + "Id: 98_51 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_31', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_51', 'origin': '97_31~CUW~97_75#MGNP'} Metrics: ['ELUC: -10.804972957066441', 'NSGA-II_crowding_distance: 0.2671049802258564', 'NSGA-II_rank: 2', 'change: 0.13830284081526614', 'is_elite: False']\n", + "Id: 97_91 Identity: {'ancestor_count': 94, 'ancestor_ids': ['92_59', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_91', 'origin': '92_59~CUW~96_77#MGNP'} Metrics: ['ELUC: -10.913423093624301', 'NSGA-II_crowding_distance: 0.26698741824986927', 'NSGA-II_rank: 1', 'change: 0.1280719692662282', 'is_elite: True']\n", + "Id: 98_14 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_77', '97_100'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_14', 'origin': '97_77~CUW~97_100#MGNP'} Metrics: ['ELUC: -10.964595806716721', 'NSGA-II_crowding_distance: 0.4423811546568828', 'NSGA-II_rank: 3', 'change: 0.1586784555102801', 'is_elite: False']\n", + "Id: 98_41 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_75', '97_100'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_41', 'origin': '97_75~CUW~97_100#MGNP'} Metrics: ['ELUC: -11.180362034449475', 'NSGA-II_crowding_distance: 0.43541311934436383', 'NSGA-II_rank: 3', 'change: 0.18268485670464327', 'is_elite: False']\n", + "Id: 98_50 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_75', '97_31'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_50', 'origin': '97_75~CUW~97_31#MGNP'} Metrics: ['ELUC: -12.023443433771119', 'NSGA-II_crowding_distance: 0.44382104670930367', 'NSGA-II_rank: 3', 'change: 0.19946316207174342', 'is_elite: False']\n", + "Id: 98_42 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_100', '97_77'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_42', 'origin': '97_100~CUW~97_77#MGNP'} Metrics: ['ELUC: -12.054337810249573', 'NSGA-II_crowding_distance: 0.15294586210127833', 'NSGA-II_rank: 1', 'change: 0.1487066113300288', 'is_elite: False']\n", + "Id: 98_47 Identity: {'ancestor_count': 96, 'ancestor_ids': ['96_40', '97_77'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_47', 'origin': '96_40~CUW~97_77#MGNP'} Metrics: ['ELUC: -12.164021984138008', 'NSGA-II_crowding_distance: 0.030005941358321866', 'NSGA-II_rank: 1', 'change: 0.15248455745640707', 'is_elite: False']\n", + "Id: 96_40 Identity: {'ancestor_count': 91, 'ancestor_ids': ['92_59', '1_1'], 'birth_generation': 96, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '96_40', 'origin': '92_59~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.274301100244193', 'NSGA-II_crowding_distance: 0.20893679826276546', 'NSGA-II_rank: 2', 'change: 0.15311995192977024', 'is_elite: False']\n", + "Id: 98_66 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_88', '97_35'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_66', 'origin': '97_88~CUW~97_35#MGNP'} Metrics: ['ELUC: -12.305108275378556', 'NSGA-II_crowding_distance: 0.18368022843323406', 'NSGA-II_rank: 2', 'change: 0.16235725046028918', 'is_elite: False']\n", + "Id: 98_99 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_77', '92_59'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_99', 'origin': '97_77~CUW~92_59#MGNP'} Metrics: ['ELUC: -12.330875138419575', 'NSGA-II_crowding_distance: 0.13692491531695594', 'NSGA-II_rank: 1', 'change: 0.15296679185117282', 'is_elite: False']\n", + "Id: 98_55 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_69', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_55', 'origin': '97_69~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.759467597443587', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.2862687969066602', 'is_elite: False']\n", + "Id: 97_100 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_77', '96_71'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_100', 'origin': '96_77~CUW~96_71#MGNP'} Metrics: ['ELUC: -12.832583091971838', 'NSGA-II_crowding_distance: 0.18701603640405867', 'NSGA-II_rank: 1', 'change: 0.18199421270039506', 'is_elite: False']\n", + "Id: 98_57 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_22', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_57', 'origin': '97_22~CUW~97_71#MGNP'} Metrics: ['ELUC: -12.895600903931124', 'NSGA-II_crowding_distance: 0.16548414024265137', 'NSGA-II_rank: 2', 'change: 0.18602652855648055', 'is_elite: False']\n", + "Id: 98_74 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_31', '97_71'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_74', 'origin': '97_31~CUW~97_71#MGNP'} Metrics: ['ELUC: -13.02217063647316', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.21400194067716288', 'is_elite: False']\n", + "Id: 98_11 Identity: {'ancestor_count': 96, 'ancestor_ids': ['96_40', '97_100'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_11', 'origin': '96_40~CUW~97_100#MGNP'} Metrics: ['ELUC: -13.162842719635629', 'NSGA-II_crowding_distance: 0.11315720444053004', 'NSGA-II_rank: 2', 'change: 0.18697993624521708', 'is_elite: False']\n", + "Id: 98_25 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_100', '97_22'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_25', 'origin': '97_100~CUW~97_22#MGNP'} Metrics: ['ELUC: -13.677308864080963', 'NSGA-II_crowding_distance: 0.4358663294005032', 'NSGA-II_rank: 2', 'change: 0.19957240412261396', 'is_elite: False']\n", + "Id: 98_37 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_77', '97_77'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_37', 'origin': '97_77~CUW~97_77#MGNP'} Metrics: ['ELUC: -13.809540033032016', 'NSGA-II_crowding_distance: 0.0781433381962278', 'NSGA-II_rank: 1', 'change: 0.1836748104059344', 'is_elite: False']\n", + "Id: 97_77 Identity: {'ancestor_count': 95, 'ancestor_ids': ['96_71', '96_41'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_77', 'origin': '96_71~CUW~96_41#MGNP'} Metrics: ['ELUC: -13.885686531009341', 'NSGA-II_crowding_distance: 0.06219931969922328', 'NSGA-II_rank: 1', 'change: 0.1874389534517673', 'is_elite: False']\n", + "Id: 98_33 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_100', '92_59'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_33', 'origin': '97_100~CUW~92_59#MGNP'} Metrics: ['ELUC: -14.066458518245582', 'NSGA-II_crowding_distance: 0.24569655549039943', 'NSGA-II_rank: 1', 'change: 0.19787371538524193', 'is_elite: True']\n", + "Id: 98_16 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_22', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_16', 'origin': '97_22~CUW~2_49#MGNP'} Metrics: ['ELUC: -14.134114718078049', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.27354749507588455', 'is_elite: False']\n", + "Id: 98_28 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_31'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_28', 'origin': '97_91~CUW~97_31#MGNP'} Metrics: ['ELUC: -15.425246064135413', 'NSGA-II_crowding_distance: 0.2641684869575246', 'NSGA-II_rank: 1', 'change: 0.2346225303883741', 'is_elite: True']\n", + "Id: 98_62 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '97_31'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_62', 'origin': '97_71~CUW~97_31#MGNP'} Metrics: ['ELUC: -15.861830130850219', 'NSGA-II_crowding_distance: 0.2843505100288662', 'NSGA-II_rank: 1', 'change: 0.24622769519125323', 'is_elite: True']\n", + "Id: 98_63 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_69', '97_78'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_63', 'origin': '97_69~CUW~97_78#MGNP'} Metrics: ['ELUC: -16.832517138455348', 'NSGA-II_crowding_distance: 0.241637568597817', 'NSGA-II_rank: 1', 'change: 0.2955845618446266', 'is_elite: True']\n", + "Id: 98_29 Identity: {'ancestor_count': 92, 'ancestor_ids': ['96_40', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_29', 'origin': '96_40~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.989374678910277', 'NSGA-II_crowding_distance: 0.037669058627383664', 'NSGA-II_rank: 1', 'change: 0.29919218216252', 'is_elite: False']\n", + "Id: 98_19 Identity: {'ancestor_count': 92, 'ancestor_ids': ['2_49', '96_40'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_19', 'origin': '2_49~CUW~96_40#MGNP'} Metrics: ['ELUC: -17.191207161995894', 'NSGA-II_crowding_distance: 0.0397777843319226', 'NSGA-II_rank: 1', 'change: 0.30073708922422715', 'is_elite: False']\n", + "Id: 98_24 Identity: {'ancestor_count': 96, 'ancestor_ids': ['2_49', '97_100'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_24', 'origin': '2_49~CUW~97_100#MGNP'} Metrics: ['ELUC: -17.47907404279429', 'NSGA-II_crowding_distance: 0.030740238140361562', 'NSGA-II_rank: 1', 'change: 0.3027506374195861', 'is_elite: False']\n", + "Id: 98_56 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_15', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_56', 'origin': '97_15~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.59720300072105', 'NSGA-II_crowding_distance: 0.007633376094285607', 'NSGA-II_rank: 1', 'change: 0.3030194167217971', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 97_69 Identity: {'ancestor_count': 94, 'ancestor_ids': ['2_49', '96_88'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_69', 'origin': '2_49~CUW~96_88#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 98_15 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_69', '96_40'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_15', 'origin': '97_69~CUW~96_40#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 98_18 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '97_69'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_18', 'origin': '1_1~CUW~97_69#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 98_46 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_69', '97_75'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_46', 'origin': '97_69~CUW~97_75#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 98_59 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_59', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 98_60 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_69', '97_69'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_60', 'origin': '97_69~CUW~97_69#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 98_78 Identity: {'ancestor_count': 95, 'ancestor_ids': ['2_49', '97_91'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_78', 'origin': '2_49~CUW~97_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 98.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 99...:\n", + "PopulationResponse:\n", + " Generation: 99\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/99/20240220-073709\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 99 and asking ESP for generation 100...:\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 99 data persisted.\n", + "Evaluated candidates:\n", + "Id: 99_15 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_65', '2_49'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_15', 'origin': '98_65~CUW~2_49#MGNP'} Metrics: ['ELUC: 23.832803529634074', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 13', 'change: 0.3037879624628424', 'is_elite: False']\n", + "Id: 99_14 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_63', '98_65'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_14', 'origin': '98_63~CUW~98_65#MGNP'} Metrics: ['ELUC: 13.622884280026954', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.260141337801704', 'is_elite: False']\n", + "Id: 99_88 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_78', '98_58'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_88', 'origin': '98_78~CUW~98_58#MGNP'} Metrics: ['ELUC: 7.589980107120847', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.24935973448918144', 'is_elite: False']\n", + "Id: 99_60 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '97_100'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_60', 'origin': '98_78~CUW~97_100#MGNP'} Metrics: ['ELUC: 5.608767541584343', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 12', 'change: 0.26626986095399335', 'is_elite: False']\n", + "Id: 99_40 Identity: {'ancestor_count': 95, 'ancestor_ids': ['2_49', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_40', 'origin': '2_49~CUW~98_94#MGNP'} Metrics: ['ELUC: 1.9309640053433', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.3230614764402193', 'is_elite: False']\n", + "Id: 99_98 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '97_100'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_98', 'origin': '98_78~CUW~97_100#MGNP'} Metrics: ['ELUC: 0.2969717254157215', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 11', 'change: 0.26088269602327746', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 99_13 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_65', '98_63'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_13', 'origin': '98_65~CUW~98_63#MGNP'} Metrics: ['ELUC: -0.023067382463622766', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.24418230811155978', 'is_elite: False']\n", + "Id: 99_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['98_95', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_82', 'origin': '98_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.3864547913688045', 'NSGA-II_crowding_distance: 0.21494345018077698', 'NSGA-II_rank: 1', 'change: 0.03114810297658979', 'is_elite: True']\n", + "Id: 99_24 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '2_49'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_24', 'origin': '98_78~CUW~2_49#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 99_55 Identity: {'ancestor_count': 96, 'ancestor_ids': ['2_49', '98_64'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_55', 'origin': '2_49~CUW~98_64#MGNP'} Metrics: ['ELUC: -0.5624618806497016', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.23872124162360145', 'is_elite: False']\n", + "Id: 99_38 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '98_48'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_38', 'origin': '98_78~CUW~98_48#MGNP'} Metrics: ['ELUC: -0.6055317544265261', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 9', 'change: 0.2389952912777783', 'is_elite: False']\n", + "Id: 99_74 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_28', '98_64'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_74', 'origin': '98_28~CUW~98_64#MGNP'} Metrics: ['ELUC: -0.6088312070278469', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.11205365342754098', 'is_elite: False']\n", + "Id: 99_16 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_16', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.7279641695192447', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 10', 'change: 0.25580908388510454', 'is_elite: False']\n", + "Id: 99_51 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_64', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_51', 'origin': '98_64~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.8053276426715671', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.05322241030978737', 'is_elite: False']\n", + "Id: 99_71 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '98_58'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_71', 'origin': '98_58~CUW~98_58#MGNP'} Metrics: ['ELUC: -1.1903705086359848', 'NSGA-II_crowding_distance: 0.09036521376420364', 'NSGA-II_rank: 2', 'change: 0.054824102829289796', 'is_elite: False']\n", + "Id: 99_95 Identity: {'ancestor_count': 95, 'ancestor_ids': ['98_94', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_95', 'origin': '98_94~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.3185787863887133', 'NSGA-II_crowding_distance: 0.07980383301917607', 'NSGA-II_rank: 2', 'change: 0.06815673493730216', 'is_elite: False']\n", + "Id: 99_47 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_95', '98_64'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_47', 'origin': '98_95~CUW~98_64#MGNP'} Metrics: ['ELUC: -1.3716562602336273', 'NSGA-II_crowding_distance: 0.1298701219738994', 'NSGA-II_rank: 2', 'change: 0.07206072655211292', 'is_elite: False']\n", + "Id: 99_93 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_64', '98_33'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_93', 'origin': '98_64~CUW~98_33#MGNP'} Metrics: ['ELUC: -1.416201471502577', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 6', 'change: 0.14025026717798753', 'is_elite: False']\n", + "Id: 98_58 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_58', 'origin': '97_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5718506229939717', 'NSGA-II_crowding_distance: 0.2980821631785551', 'NSGA-II_rank: 1', 'change: 0.0423576568990015', 'is_elite: True']\n", + "Id: 99_89 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_33', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_89', 'origin': '98_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.9908954820480809', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.16561646229065732', 'is_elite: False']\n", + "Id: 99_39 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_95', '98_64'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_39', 'origin': '98_95~CUW~98_64#MGNP'} Metrics: ['ELUC: -2.512580458532411', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.09588883811480658', 'is_elite: False']\n", + "Id: 99_73 Identity: {'ancestor_count': 97, 'ancestor_ids': ['1_1', '98_62'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_73', 'origin': '1_1~CUW~98_62#MGNP'} Metrics: ['ELUC: -2.5433041306932878', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.0839825182935043', 'is_elite: False']\n", + "Id: 99_43 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_95', '98_62'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_43', 'origin': '98_95~CUW~98_62#MGNP'} Metrics: ['ELUC: -2.889339994928438', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.1588319173275827', 'is_elite: False']\n", + "Id: 99_19 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_94', '98_78'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_19', 'origin': '98_94~CUW~98_78#MGNP'} Metrics: ['ELUC: -2.9213072466790067', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.26708075936263204', 'is_elite: False']\n", + "Id: 98_94 Identity: {'ancestor_count': 94, 'ancestor_ids': ['97_15', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_94', 'origin': '97_15~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.9679427883733043', 'NSGA-II_crowding_distance: 0.11640917296748446', 'NSGA-II_rank: 2', 'change: 0.07605097453140519', 'is_elite: False']\n", + "Id: 99_70 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_62', '98_95'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_70', 'origin': '98_62~CUW~98_95#MGNP'} Metrics: ['ELUC: -2.9845497356303423', 'NSGA-II_crowding_distance: 0.045463646617269246', 'NSGA-II_rank: 2', 'change: 0.07713525934589402', 'is_elite: False']\n", + "Id: 99_81 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '98_42'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_81', 'origin': '98_58~CUW~98_42#MGNP'} Metrics: ['ELUC: -3.2095412321349532', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.09142660060707339', 'is_elite: False']\n", + "Id: 99_79 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_64', '98_48'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_79', 'origin': '98_64~CUW~98_48#MGNP'} Metrics: ['ELUC: -3.2511905341899685', 'NSGA-II_crowding_distance: 0.13879217999514998', 'NSGA-II_rank: 3', 'change: 0.0900450717541956', 'is_elite: False']\n", + "Id: 99_28 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_28', 'origin': '97_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.3586921049004776', 'NSGA-II_crowding_distance: 0.2892081449685779', 'NSGA-II_rank: 1', 'change: 0.06964939436251912', 'is_elite: True']\n", + "Id: 99_90 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_90', 'origin': '97_91~CUW~98_94#MGNP'} Metrics: ['ELUC: -3.4626629929206922', 'NSGA-II_crowding_distance: 0.14254431040309035', 'NSGA-II_rank: 2', 'change: 0.08004489148802364', 'is_elite: False']\n", + "Id: 99_87 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_94', '98_64'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_87', 'origin': '98_94~CUW~98_64#MGNP'} Metrics: ['ELUC: -3.6284853592319792', 'NSGA-II_crowding_distance: 0.13495600760226728', 'NSGA-II_rank: 4', 'change: 0.10989049469225541', 'is_elite: False']\n", + "Id: 99_17 Identity: {'ancestor_count': 95, 'ancestor_ids': ['1_1', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_17', 'origin': '1_1~CUW~98_94#MGNP'} Metrics: ['ELUC: -3.6645335021027905', 'NSGA-II_crowding_distance: 0.27657859889882064', 'NSGA-II_rank: 4', 'change: 0.1120509963962396', 'is_elite: False']\n", + "Id: 99_45 Identity: {'ancestor_count': 96, 'ancestor_ids': ['2_49', '98_64'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_45', 'origin': '2_49~CUW~98_64#MGNP'} Metrics: ['ELUC: -3.690203587952778', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.2636134505929092', 'is_elite: False']\n", + "Id: 99_34 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '98_52'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_34', 'origin': '98_58~CUW~98_52#MGNP'} Metrics: ['ELUC: -3.8452508517481414', 'NSGA-II_crowding_distance: 0.4046130415911404', 'NSGA-II_rank: 3', 'change: 0.09407132798609533', 'is_elite: False']\n", + "Id: 99_25 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_78', '98_58'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_25', 'origin': '98_78~CUW~98_58#MGNP'} Metrics: ['ELUC: -4.148131485015946', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.2500048672023431', 'is_elite: False']\n", + "Id: 99_66 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_42', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_66', 'origin': '98_42~CUW~98_94#MGNP'} Metrics: ['ELUC: -4.45155205790111', 'NSGA-II_crowding_distance: 0.3622231871849626', 'NSGA-II_rank: 2', 'change: 0.09090945105940862', 'is_elite: False']\n", + "Id: 99_78 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_94', '98_33'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_78', 'origin': '98_94~CUW~98_33#MGNP'} Metrics: ['ELUC: -4.523837090246218', 'NSGA-II_crowding_distance: 0.18340542997179377', 'NSGA-II_rank: 1', 'change: 0.07855480211615679', 'is_elite: False']\n", + "Id: 99_77 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_52', '98_99'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_77', 'origin': '98_52~CUW~98_99#MGNP'} Metrics: ['ELUC: -4.786621492362805', 'NSGA-II_crowding_distance: 0.2605973355328172', 'NSGA-II_rank: 1', 'change: 0.10014108561391086', 'is_elite: True']\n", + "Id: 99_30 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_95', '98_33'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_30', 'origin': '98_95~CUW~98_33#MGNP'} Metrics: ['ELUC: -5.926925289980629', 'NSGA-II_crowding_distance: 0.9008940814450166', 'NSGA-II_rank: 5', 'change: 0.12129129486315673', 'is_elite: False']\n", + "Id: 99_80 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_64', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_80', 'origin': '98_64~CUW~97_91#MGNP'} Metrics: ['ELUC: -6.859143861948201', 'NSGA-II_crowding_distance: 0.6197655594111902', 'NSGA-II_rank: 4', 'change: 0.11677564284941103', 'is_elite: False']\n", + "Id: 99_69 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_69', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -6.966865413620054', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.24275902093744645', 'is_elite: False']\n", + "Id: 99_33 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_33', 'origin': '97_91~CUW~98_94#MGNP'} Metrics: ['ELUC: -7.245663633353614', 'NSGA-II_crowding_distance: 0.22157586346270233', 'NSGA-II_rank: 1', 'change: 0.11012100424813916', 'is_elite: True']\n", + "Id: 99_83 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '98_28'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_83', 'origin': '98_58~CUW~98_28#MGNP'} Metrics: ['ELUC: -7.2555519164932845', 'NSGA-II_crowding_distance: 0.6462952001211981', 'NSGA-II_rank: 3', 'change: 0.11636336745420996', 'is_elite: False']\n", + "Id: 99_85 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_28', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_85', 'origin': '98_28~CUW~98_94#MGNP'} Metrics: ['ELUC: -7.335801867614322', 'NSGA-II_crowding_distance: 1.756639410889277', 'NSGA-II_rank: 7', 'change: 0.16504505672231037', 'is_elite: False']\n", + "Id: 99_68 Identity: {'ancestor_count': 95, 'ancestor_ids': ['98_91', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_68', 'origin': '98_91~CUW~98_94#MGNP'} Metrics: ['ELUC: -7.363402892801341', 'NSGA-II_crowding_distance: 0.5337630457417597', 'NSGA-II_rank: 2', 'change: 0.11247366210987726', 'is_elite: False']\n", + "Id: 99_65 Identity: {'ancestor_count': 95, 'ancestor_ids': ['98_94', '98_52'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_65', 'origin': '98_94~CUW~98_52#MGNP'} Metrics: ['ELUC: -8.072553485097833', 'NSGA-II_crowding_distance: 0.11044639796952649', 'NSGA-II_rank: 1', 'change: 0.11049110677881277', 'is_elite: False']\n", + "Id: 99_100 Identity: {'ancestor_count': 95, 'ancestor_ids': ['98_94', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_100', 'origin': '98_94~CUW~97_91#MGNP'} Metrics: ['ELUC: -8.273575238745465', 'NSGA-II_crowding_distance: 0.5076177465392331', 'NSGA-II_rank: 5', 'change: 0.14151247332037084', 'is_elite: False']\n", + "Id: 99_57 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_57', 'origin': '98_78~CUW~97_91#MGNP'} Metrics: ['ELUC: -8.4975502270179', 'NSGA-II_crowding_distance: 1.1944067284721398', 'NSGA-II_rank: 7', 'change: 0.25657094943333675', 'is_elite: False']\n", + "Id: 99_94 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_94', 'origin': '97_91~CUW~98_94#MGNP'} Metrics: ['ELUC: -8.549601057231694', 'NSGA-II_crowding_distance: 0.13074961387392256', 'NSGA-II_rank: 1', 'change: 0.12094752812020396', 'is_elite: False']\n", + "Id: 99_63 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_78', '98_62'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_63', 'origin': '98_78~CUW~98_62#MGNP'} Metrics: ['ELUC: -8.783275552197855', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.28022918059145513', 'is_elite: False']\n", + "Id: 99_32 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_62', '98_58'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_32', 'origin': '98_62~CUW~98_58#MGNP'} Metrics: ['ELUC: -8.88981604702701', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.15297289879164513', 'is_elite: False']\n", + "Id: 99_21 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_21', 'origin': '97_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -9.236142684307818', 'NSGA-II_crowding_distance: 1.0991059185549834', 'NSGA-II_rank: 5', 'change: 0.1456633784186249', 'is_elite: False']\n", + "Id: 99_46 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '98_52'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_46', 'origin': '97_91~CUW~98_52#MGNP'} Metrics: ['ELUC: -9.496242414322719', 'NSGA-II_crowding_distance: 0.09029454614272925', 'NSGA-II_rank: 1', 'change: 0.12534343785755045', 'is_elite: False']\n", + "Id: 99_23 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_42', '97_100'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_23', 'origin': '98_42~CUW~97_100#MGNP'} Metrics: ['ELUC: -9.810754988254903', 'NSGA-II_crowding_distance: 0.08812940668602091', 'NSGA-II_rank: 1', 'change: 0.12648723756205374', 'is_elite: False']\n", + "Id: 99_20 Identity: {'ancestor_count': 95, 'ancestor_ids': ['98_91', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_20', 'origin': '98_91~CUW~97_91#MGNP'} Metrics: ['ELUC: -10.432773708481694', 'NSGA-II_crowding_distance: 0.3871960890567214', 'NSGA-II_rank: 4', 'change: 0.13473261198189002', 'is_elite: False']\n", + "Id: 99_61 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_94', '98_33'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_61', 'origin': '98_94~CUW~98_33#MGNP'} Metrics: ['ELUC: -10.492061823295794', 'NSGA-II_crowding_distance: 0.06495976789722568', 'NSGA-II_rank: 4', 'change: 0.1401142598622259', 'is_elite: False']\n", + "Id: 99_99 Identity: {'ancestor_count': 95, 'ancestor_ids': ['98_94', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_99', 'origin': '98_94~CUW~97_91#MGNP'} Metrics: ['ELUC: -10.705455569363652', 'NSGA-II_crowding_distance: 0.596706459057927', 'NSGA-II_rank: 4', 'change: 0.14383358780973', 'is_elite: False']\n", + "Id: 99_59 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_59', 'origin': '97_91~CUW~97_91#MGNP'} Metrics: ['ELUC: -10.768319309983607', 'NSGA-II_crowding_distance: 0.35090328218668787', 'NSGA-II_rank: 3', 'change: 0.12830834105055133', 'is_elite: False']\n", + "Id: 99_27 Identity: {'ancestor_count': 95, 'ancestor_ids': ['98_94', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_27', 'origin': '98_94~CUW~97_91#MGNP'} Metrics: ['ELUC: -10.771747947727041', 'NSGA-II_crowding_distance: 0.3714708483622951', 'NSGA-II_rank: 3', 'change: 0.13854557285757227', 'is_elite: False']\n", + "Id: 97_91 Identity: {'ancestor_count': 94, 'ancestor_ids': ['92_59', '96_77'], 'birth_generation': 97, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '97_91', 'origin': '92_59~CUW~96_77#MGNP'} Metrics: ['ELUC: -10.913423093624301', 'NSGA-II_crowding_distance: 0.40998972540113593', 'NSGA-II_rank: 2', 'change: 0.1280719692662282', 'is_elite: False']\n", + "Id: 99_72 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_72', 'origin': '97_91~CUW~97_91#MGNP'} Metrics: ['ELUC: -10.965405254422661', 'NSGA-II_crowding_distance: 0.10612209374347147', 'NSGA-II_rank: 1', 'change: 0.1267071426483211', 'is_elite: False']\n", + "Id: 99_62 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_62', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_62', 'origin': '98_62~CUW~97_91#MGNP'} Metrics: ['ELUC: -11.091316281967083', 'NSGA-II_crowding_distance: 0.3138465956300302', 'NSGA-II_rank: 2', 'change: 0.15940637709340524', 'is_elite: False']\n", + "Id: 99_11 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_91', '98_65'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_11', 'origin': '97_91~CUW~98_65#MGNP'} Metrics: ['ELUC: -11.238520600422593', 'NSGA-II_crowding_distance: 0.13099048600834923', 'NSGA-II_rank: 1', 'change: 0.1339220829077558', 'is_elite: False']\n", + "Id: 99_54 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_100', '98_78'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_54', 'origin': '97_100~CUW~98_78#MGNP'} Metrics: ['ELUC: -11.302030623560778', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.28176649528980136', 'is_elite: False']\n", + "Id: 99_44 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_28', '98_52'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_44', 'origin': '98_28~CUW~98_52#MGNP'} Metrics: ['ELUC: -11.46569292226692', 'NSGA-II_crowding_distance: 0.194060797827979', 'NSGA-II_rank: 1', 'change: 0.15730174857218557', 'is_elite: False']\n", + "Id: 99_86 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_91', '98_63'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_86', 'origin': '97_91~CUW~98_63#MGNP'} Metrics: ['ELUC: -11.479716579748125', 'NSGA-II_crowding_distance: 0.7000095976173024', 'NSGA-II_rank: 4', 'change: 0.24707138672399412', 'is_elite: False']\n", + "Id: 99_26 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_26', 'origin': '98_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -11.815803658661432', 'NSGA-II_crowding_distance: 0.29532217154614654', 'NSGA-II_rank: 4', 'change: 0.270050853711192', 'is_elite: False']\n", + "Id: 99_36 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_42', '97_100'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_36', 'origin': '98_42~CUW~97_100#MGNP'} Metrics: ['ELUC: -12.005312450419634', 'NSGA-II_crowding_distance: 0.8466114386831222', 'NSGA-II_rank: 3', 'change: 0.18859429861686458', 'is_elite: False']\n", + "Id: 99_31 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_65', '98_28'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_31', 'origin': '98_65~CUW~98_28#MGNP'} Metrics: ['ELUC: -12.060249388945282', 'NSGA-II_crowding_distance: 0.1250444492086052', 'NSGA-II_rank: 1', 'change: 0.1778805094414115', 'is_elite: False']\n", + "Id: 99_52 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_91', '98_62'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_52', 'origin': '98_91~CUW~98_62#MGNP'} Metrics: ['ELUC: -12.31811570213323', 'NSGA-II_crowding_distance: 0.06563197082010738', 'NSGA-II_rank: 1', 'change: 0.18014634825843523', 'is_elite: False']\n", + "Id: 99_48 Identity: {'ancestor_count': 96, 'ancestor_ids': ['1_1', '98_28'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_48', 'origin': '1_1~CUW~98_28#MGNP'} Metrics: ['ELUC: -12.364758288328238', 'NSGA-II_crowding_distance: 0.21229125045538946', 'NSGA-II_rank: 2', 'change: 0.18486981118434592', 'is_elite: False']\n", + "Id: 99_42 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '98_62'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_42', 'origin': '98_58~CUW~98_62#MGNP'} Metrics: ['ELUC: -12.53644991752479', 'NSGA-II_crowding_distance: 0.45535975561348446', 'NSGA-II_rank: 2', 'change: 0.1909284788603326', 'is_elite: False']\n", + "Id: 99_29 Identity: {'ancestor_count': 97, 'ancestor_ids': ['97_91', '98_33'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_29', 'origin': '97_91~CUW~98_33#MGNP'} Metrics: ['ELUC: -12.905985368697309', 'NSGA-II_crowding_distance: 0.15884994493940147', 'NSGA-II_rank: 1', 'change: 0.1831112266794751', 'is_elite: False']\n", + "Id: 99_12 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_12', 'origin': '98_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -13.740250901737136', 'NSGA-II_crowding_distance: 0.18783797179096134', 'NSGA-II_rank: 4', 'change: 0.2727296532107757', 'is_elite: False']\n", + "Id: 99_53 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_63', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_53', 'origin': '98_63~CUW~98_94#MGNP'} Metrics: ['ELUC: -13.880708877140101', 'NSGA-II_crowding_distance: 0.32250453219052166', 'NSGA-II_rank: 4', 'change: 0.27671589875577235', 'is_elite: False']\n", + "Id: 99_22 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_91', '98_78'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_22', 'origin': '97_91~CUW~98_78#MGNP'} Metrics: ['ELUC: -14.054262095618915', 'NSGA-II_crowding_distance: 0.6442067797140727', 'NSGA-II_rank: 3', 'change: 0.26908111915594', 'is_elite: False']\n", + "Id: 98_33 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_100', '92_59'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_33', 'origin': '97_100~CUW~92_59#MGNP'} Metrics: ['ELUC: -14.066458518245582', 'NSGA-II_crowding_distance: 0.24335456421261759', 'NSGA-II_rank: 1', 'change: 0.19787371538524193', 'is_elite: True']\n", + "Id: 99_92 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_28', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_92', 'origin': '98_28~CUW~97_91#MGNP'} Metrics: ['ELUC: -14.956750920930611', 'NSGA-II_crowding_distance: 0.20044344973023936', 'NSGA-II_rank: 1', 'change: 0.2209206819300325', 'is_elite: False']\n", + "Id: 99_41 Identity: {'ancestor_count': 2, 'ancestor_ids': ['1_1', '2_49'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_41', 'origin': '1_1~CUW~2_49#MGNP'} Metrics: ['ELUC: -15.068694582168815', 'NSGA-II_crowding_distance: 0.3196815900461532', 'NSGA-II_rank: 3', 'change: 0.2795456254831237', 'is_elite: False']\n", + "Id: 98_28 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '97_31'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_28', 'origin': '97_91~CUW~97_31#MGNP'} Metrics: ['ELUC: -15.425246064135413', 'NSGA-II_crowding_distance: 0.12624395644708422', 'NSGA-II_rank: 1', 'change: 0.2346225303883741', 'is_elite: False']\n", + "Id: 99_67 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_62', '98_62'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_67', 'origin': '98_62~CUW~98_62#MGNP'} Metrics: ['ELUC: -15.80058049696163', 'NSGA-II_crowding_distance: 0.06372503722728524', 'NSGA-II_rank: 1', 'change: 0.24426901716170712', 'is_elite: False']\n", + "Id: 99_58 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_62', '98_28'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_58', 'origin': '98_62~CUW~98_28#MGNP'} Metrics: ['ELUC: -15.841395926636489', 'NSGA-II_crowding_distance: 0.6697919204526586', 'NSGA-II_rank: 2', 'change: 0.24687535665071086', 'is_elite: False']\n", + "Id: 98_62 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '97_31'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_62', 'origin': '97_71~CUW~97_31#MGNP'} Metrics: ['ELUC: -15.861830130850219', 'NSGA-II_crowding_distance: 0.11852265267500023', 'NSGA-II_rank: 1', 'change: 0.24622769519125323', 'is_elite: False']\n", + "Id: 99_18 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_63', '98_64'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_18', 'origin': '98_63~CUW~98_64#MGNP'} Metrics: ['ELUC: -15.932702757927515', 'NSGA-II_crowding_distance: 0.20397272161527166', 'NSGA-II_rank: 1', 'change: 0.27739137988384993', 'is_elite: True']\n", + "Id: 99_35 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_35', 'origin': '98_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -16.5072797240162', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.29615506727409535', 'is_elite: False']\n", + "Id: 98_63 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_69', '97_78'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_63', 'origin': '97_69~CUW~97_78#MGNP'} Metrics: ['ELUC: -16.832517138455348', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.2955845618446266', 'is_elite: False']\n", + "Id: 99_37 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_100', '2_49'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_37', 'origin': '97_100~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.840620544766956', 'NSGA-II_crowding_distance: 0.2721304964090802', 'NSGA-II_rank: 2', 'change: 0.294182369092148', 'is_elite: False']\n", + "Id: 99_84 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_63', '98_58'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_84', 'origin': '98_63~CUW~98_58#MGNP'} Metrics: ['ELUC: -16.85816675329435', 'NSGA-II_crowding_distance: 0.10927947030674921', 'NSGA-II_rank: 1', 'change: 0.2901804701394328', 'is_elite: False']\n", + "Id: 99_91 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_62', '98_78'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_91', 'origin': '98_62~CUW~98_78#MGNP'} Metrics: ['ELUC: -17.007750090197124', 'NSGA-II_crowding_distance: 0.04511867617618126', 'NSGA-II_rank: 1', 'change: 0.2917540539382175', 'is_elite: False']\n", + "Id: 99_75 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_33', '98_63'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_75', 'origin': '98_33~CUW~98_63#MGNP'} Metrics: ['ELUC: -17.115103409349448', 'NSGA-II_crowding_distance: 0.08000493415048103', 'NSGA-II_rank: 2', 'change: 0.29589626603981817', 'is_elite: False']\n", + "Id: 99_50 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_28', '98_78'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_50', 'origin': '98_28~CUW~98_78#MGNP'} Metrics: ['ELUC: -17.331430611211008', 'NSGA-II_crowding_distance: 0.06844123401844063', 'NSGA-II_rank: 1', 'change: 0.29561144409886136', 'is_elite: False']\n", + "Id: 99_97 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_63', '97_91'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_97', 'origin': '98_63~CUW~97_91#MGNP'} Metrics: ['ELUC: -17.56435066988366', 'NSGA-II_crowding_distance: 0.03986418402682077', 'NSGA-II_rank: 1', 'change: 0.30272970954981415', 'is_elite: False']\n", + "Id: 99_49 Identity: {'ancestor_count': 96, 'ancestor_ids': ['2_49', '98_63'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_49', 'origin': '2_49~CUW~98_63#MGNP'} Metrics: ['ELUC: -17.58979701936688', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.30301758283369556', 'is_elite: False']\n", + "Id: 99_64 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_63', '98_78'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_64', 'origin': '98_63~CUW~98_78#MGNP'} Metrics: ['ELUC: -17.596001165415032', 'NSGA-II_crowding_distance: 0.0028533851541223125', 'NSGA-II_rank: 1', 'change: 0.30301618437714184', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 98_78 Identity: {'ancestor_count': 95, 'ancestor_ids': ['2_49', '97_91'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_78', 'origin': '2_49~CUW~97_91#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 99_56 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_78', '98_28'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_56', 'origin': '98_78~CUW~98_28#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 99_76 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_76', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 99_96 Identity: {'ancestor_count': 97, 'ancestor_ids': ['2_49', '98_62'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_96', 'origin': '2_49~CUW~98_62#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 99.\n", + "--------\n", + "\n", + "Evaluating PopulationResponse for generation 100...:\n", + "PopulationResponse:\n", + " Generation: 100\n", + " Population size: 100\n", + " Checkpoint id: no-overlap/100/20240220-074426\n", + "Evaluating candidates synchronously because max_workers == 0\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "1218/1218 [==============================] - 4s 3ms/step\n", + "Evaluation done.\n", + "Reporting evaluated population for generation 100...\n", + "Sending NextPopulation request\n", + "NextPopulation response received.\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/964840/anaconda3/envs/leaf/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n", + " saving_api.save_model(\n", + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Generation 100 data persisted.\n", + "Evaluated candidates:\n", + "Id: 100_72 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_28', '99_18'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_72', 'origin': '99_28~CUW~99_18#MGNP'} Metrics: ['ELUC: 20.46884834262869', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.26952508652512125', 'is_elite: False']\n", + "Id: 100_38 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '99_82'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_38', 'origin': '2_49~CUW~99_82#MGNP'} Metrics: ['ELUC: 19.048462791590406', 'NSGA-II_crowding_distance: 2.0', 'NSGA-II_rank: 12', 'change: 0.28716060729692167', 'is_elite: False']\n", + "Id: 100_33 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_33', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 16.25505279716515', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 12', 'change: 0.300587474361278', 'is_elite: False']\n", + "Id: 100_79 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_33', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_79', 'origin': '98_33~CUW~1_1#MGNP'} Metrics: ['ELUC: 7.548052981446317', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.1653097835382949', 'is_elite: False']\n", + "Id: 100_74 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_74', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: 7.216359659195311', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 11', 'change: 0.28134598568752417', 'is_elite: False']\n", + "Id: 100_67 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_29', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_67', 'origin': '99_29~CUW~1_1#MGNP'} Metrics: ['ELUC: 4.913892863094018', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 10', 'change: 0.1647958358015015', 'is_elite: False']\n", + "Id: 100_64 Identity: {'ancestor_count': 97, 'ancestor_ids': ['1_1', '99_92'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_64', 'origin': '1_1~CUW~99_92#MGNP'} Metrics: ['ELUC: 4.86219190754713', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.13632668969784334', 'is_elite: False']\n", + "Id: 100_69 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_11', '99_82'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_69', 'origin': '99_11~CUW~99_82#MGNP'} Metrics: ['ELUC: 1.9937576197120912', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.10104315599346221', 'is_elite: False']\n", + "Id: 100_70 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_28', '99_29'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_70', 'origin': '99_28~CUW~99_29#MGNP'} Metrics: ['ELUC: 1.5162200215191481', 'NSGA-II_crowding_distance: 0.8046967539033953', 'NSGA-II_rank: 8', 'change: 0.1172500586674333', 'is_elite: False']\n", + "Id: 100_59 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_28', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_59', 'origin': '99_28~CUW~99_77#MGNP'} Metrics: ['ELUC: 1.1298884145346089', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.09622866586782633', 'is_elite: False']\n", + "Id: 100_83 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_83', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.9355681966909649', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.028227860037475676', 'is_elite: False']\n", + "Id: 100_81 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_81', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.6657633883822447', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.025167041853846533', 'is_elite: False']\n", + "Id: 100_32 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_82', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_32', 'origin': '99_82~CUW~99_77#MGNP'} Metrics: ['ELUC: 0.4645972798061161', 'NSGA-II_crowding_distance: 0.7312173933517608', 'NSGA-II_rank: 8', 'change: 0.1177913744528459', 'is_elite: False']\n", + "Id: 100_60 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_60', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.291688634496232', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.021874761823963435', 'is_elite: False']\n", + "Id: 100_71 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_71', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.2847820046868796', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.061961477188011226', 'is_elite: False']\n", + "Id: 100_87 Identity: {'ancestor_count': 97, 'ancestor_ids': ['1_1', '98_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_87', 'origin': '1_1~CUW~98_33#MGNP'} Metrics: ['ELUC: 0.18804333352539102', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 9', 'change: 0.15768086905980205', 'is_elite: False']\n", + "Id: 100_47 Identity: {'ancestor_count': 98, 'ancestor_ids': ['1_1', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_47', 'origin': '1_1~CUW~99_77#MGNP'} Metrics: ['ELUC: 0.18045909263439566', 'NSGA-II_crowding_distance: 0.1568984897942472', 'NSGA-II_rank: 4', 'change: 0.05144361422136925', 'is_elite: False']\n", + "Id: 100_88 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_77', '98_58'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_88', 'origin': '99_77~CUW~98_58#MGNP'} Metrics: ['ELUC: 0.1747695661700749', 'NSGA-II_crowding_distance: 0.2325106165483009', 'NSGA-II_rank: 4', 'change: 0.05395414684789398', 'is_elite: False']\n", + "Id: 100_11 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_77', '99_82'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_11', 'origin': '99_77~CUW~99_82#MGNP'} Metrics: ['ELUC: 0.1402930771167055', 'NSGA-II_crowding_distance: 1.1953032460966044', 'NSGA-II_rank: 8', 'change: 0.13360037971856242', 'is_elite: False']\n", + "Id: 100_34 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_34', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: 0.06190646145778704', 'NSGA-II_crowding_distance: 0.2848041165768499', 'NSGA-II_rank: 3', 'change: 0.04101454402221215', 'is_elite: False']\n", + "Id: 1_1 Identity: {'ancestor_count': 0, 'ancestor_ids': [], 'birth_generation': 1, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '1_1', 'origin': '(none)'} Metrics: ['ELUC: -0.015049002603192035', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.004642724768884137', 'is_elite: True']\n", + "Id: 100_68 Identity: {'ancestor_count': 97, 'ancestor_ids': ['1_1', '98_58'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_68', 'origin': '1_1~CUW~98_58#MGNP'} Metrics: ['ELUC: -0.14448251392531225', 'NSGA-II_crowding_distance: 0.18143366361588176', 'NSGA-II_rank: 2', 'change: 0.029145602280034235', 'is_elite: False']\n", + "Id: 100_96 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_78', '99_96'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_96', 'origin': '99_78~CUW~99_96#MGNP'} Metrics: ['ELUC: -0.15673108038401132', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 8', 'change: 0.2799369474470493', 'is_elite: False']\n", + "Id: 100_50 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_1', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_50', 'origin': '1_1~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.17347429521967983', 'NSGA-II_crowding_distance: 0.10995542668909955', 'NSGA-II_rank: 1', 'change: 0.02277727387084702', 'is_elite: False']\n", + "Id: 99_82 Identity: {'ancestor_count': 2, 'ancestor_ids': ['98_95', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_82', 'origin': '98_95~CUW~1_1#MGNP'} Metrics: ['ELUC: -0.3864547913688045', 'NSGA-II_crowding_distance: 0.08049399263127661', 'NSGA-II_rank: 1', 'change: 0.03114810297658979', 'is_elite: False']\n", + "Id: 100_77 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '99_82'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_77', 'origin': '98_58~CUW~99_82#MGNP'} Metrics: ['ELUC: -0.5946085983589181', 'NSGA-II_crowding_distance: 0.10498802349167742', 'NSGA-II_rank: 1', 'change: 0.03964810850858582', 'is_elite: False']\n", + "Id: 100_89 Identity: {'ancestor_count': 96, 'ancestor_ids': ['99_33', '99_82'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_89', 'origin': '99_33~CUW~99_82#MGNP'} Metrics: ['ELUC: -1.0331481393517594', 'NSGA-II_crowding_distance: 0.13410843915308385', 'NSGA-II_rank: 2', 'change: 0.05180085713443888', 'is_elite: False']\n", + "Id: 100_51 Identity: {'ancestor_count': 97, 'ancestor_ids': ['1_1', '98_58'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_51', 'origin': '1_1~CUW~98_58#MGNP'} Metrics: ['ELUC: -1.0709685637380821', 'NSGA-II_crowding_distance: 0.08524927382619207', 'NSGA-II_rank: 2', 'change: 0.052099720191663285', 'is_elite: False']\n", + "Id: 100_63 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_33', '98_58'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_63', 'origin': '99_33~CUW~98_58#MGNP'} Metrics: ['ELUC: -1.3368156287753892', 'NSGA-II_crowding_distance: 0.2360620882937288', 'NSGA-II_rank: 3', 'change: 0.07129060356070291', 'is_elite: False']\n", + "Id: 100_75 Identity: {'ancestor_count': 98, 'ancestor_ids': ['1_1', '99_78'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_75', 'origin': '1_1~CUW~99_78#MGNP'} Metrics: ['ELUC: -1.4445176174975336', 'NSGA-II_crowding_distance: 0.4027819346146718', 'NSGA-II_rank: 4', 'change: 0.0795604721577777', 'is_elite: False']\n", + "Id: 98_58 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_71', '1_1'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_58', 'origin': '97_71~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.5718506229939717', 'NSGA-II_crowding_distance: 0.1119005838362524', 'NSGA-II_rank: 1', 'change: 0.0423576568990015', 'is_elite: False']\n", + "Id: 100_53 Identity: {'ancestor_count': 96, 'ancestor_ids': ['99_33', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_53', 'origin': '99_33~CUW~1_1#MGNP'} Metrics: ['ELUC: -1.614412063512669', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 7', 'change: 0.10373050903398458', 'is_elite: False']\n", + "Id: 100_28 Identity: {'ancestor_count': 98, 'ancestor_ids': ['1_1', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_28', 'origin': '1_1~CUW~99_77#MGNP'} Metrics: ['ELUC: -1.9418675760836472', 'NSGA-II_crowding_distance: 0.07981112895501286', 'NSGA-II_rank: 3', 'change: 0.07367783426503156', 'is_elite: False']\n", + "Id: 100_18 Identity: {'ancestor_count': 98, 'ancestor_ids': ['1_1', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_18', 'origin': '1_1~CUW~99_77#MGNP'} Metrics: ['ELUC: -2.015570776404055', 'NSGA-II_crowding_distance: 0.17330869874218785', 'NSGA-II_rank: 3', 'change: 0.08231295474993425', 'is_elite: False']\n", + "Id: 100_97 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_82', '98_58'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_97', 'origin': '99_82~CUW~98_58#MGNP'} Metrics: ['ELUC: -2.1520035952797913', 'NSGA-II_crowding_distance: 0.1395144483853925', 'NSGA-II_rank: 2', 'change: 0.058019228335991636', 'is_elite: False']\n", + "Id: 100_41 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '98_58'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_41', 'origin': '98_58~CUW~98_58#MGNP'} Metrics: ['ELUC: -2.194059466449818', 'NSGA-II_crowding_distance: 0.07977821420595957', 'NSGA-II_rank: 1', 'change: 0.04589357481980645', 'is_elite: False']\n", + "Id: 100_17 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_78', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_17', 'origin': '99_78~CUW~1_1#MGNP'} Metrics: ['ELUC: -2.2562632711532817', 'NSGA-II_crowding_distance: 0.14585537800980547', 'NSGA-II_rank: 1', 'change: 0.05454700455728761', 'is_elite: False']\n", + "Id: 100_22 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_44', '99_82'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_22', 'origin': '99_44~CUW~99_82#MGNP'} Metrics: ['ELUC: -2.4045536008876685', 'NSGA-II_crowding_distance: 0.09972654392816739', 'NSGA-II_rank: 2', 'change: 0.07013681032288016', 'is_elite: False']\n", + "Id: 100_54 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_77', '99_28'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_54', 'origin': '99_77~CUW~99_28#MGNP'} Metrics: ['ELUC: -3.081111950482697', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 6', 'change: 0.0947948621246327', 'is_elite: False']\n", + "Id: 100_82 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_77', '99_78'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_82', 'origin': '99_77~CUW~99_78#MGNP'} Metrics: ['ELUC: -3.1423528720360387', 'NSGA-II_crowding_distance: 0.17606157809383402', 'NSGA-II_rank: 2', 'change: 0.0703263459108582', 'is_elite: False']\n", + "Id: 100_78 Identity: {'ancestor_count': 98, 'ancestor_ids': ['98_58', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_78', 'origin': '98_58~CUW~99_77#MGNP'} Metrics: ['ELUC: -3.300602452688267', 'NSGA-II_crowding_distance: 1.8332132585280803', 'NSGA-II_rank: 5', 'change: 0.08866009398216332', 'is_elite: False']\n", + "Id: 99_28 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '1_1'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_28', 'origin': '97_91~CUW~1_1#MGNP'} Metrics: ['ELUC: -3.3586921049004776', 'NSGA-II_crowding_distance: 0.14331992819997136', 'NSGA-II_rank: 1', 'change: 0.06964939436251912', 'is_elite: False']\n", + "Id: 100_65 Identity: {'ancestor_count': 98, 'ancestor_ids': ['1_1', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_65', 'origin': '1_1~CUW~99_77#MGNP'} Metrics: ['ELUC: -3.4266421596879733', 'NSGA-II_crowding_distance: 0.28577723393405724', 'NSGA-II_rank: 4', 'change: 0.08684311962995667', 'is_elite: False']\n", + "Id: 100_66 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_78', '98_58'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_66', 'origin': '99_78~CUW~98_58#MGNP'} Metrics: ['ELUC: -3.7638979799501704', 'NSGA-II_crowding_distance: 0.08363769385868366', 'NSGA-II_rank: 1', 'change: 0.07172545154485278', 'is_elite: False']\n", + "Id: 100_21 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_77', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_21', 'origin': '99_77~CUW~99_77#MGNP'} Metrics: ['ELUC: -3.8923137242437225', 'NSGA-II_crowding_distance: 0.30903463357741146', 'NSGA-II_rank: 4', 'change: 0.10505644222055043', 'is_elite: False']\n", + "Id: 100_93 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_77', '98_58'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_93', 'origin': '99_77~CUW~98_58#MGNP'} Metrics: ['ELUC: -4.095131446585787', 'NSGA-II_crowding_distance: 0.18585533860821657', 'NSGA-II_rank: 3', 'change: 0.08661688384231421', 'is_elite: False']\n", + "Id: 100_27 Identity: {'ancestor_count': 96, 'ancestor_ids': ['99_28', '99_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_27', 'origin': '99_28~CUW~99_33#MGNP'} Metrics: ['ELUC: -4.238005772808884', 'NSGA-II_crowding_distance: 0.05581399022805245', 'NSGA-II_rank: 3', 'change: 0.09759224272382551', 'is_elite: False']\n", + "Id: 100_58 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_31', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_58', 'origin': '99_31~CUW~1_1#MGNP'} Metrics: ['ELUC: -4.329185208886503', 'NSGA-II_crowding_distance: 0.0414443122896897', 'NSGA-II_rank: 3', 'change: 0.09821964346940285', 'is_elite: False']\n", + "Id: 100_100 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '98_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_100', 'origin': '98_58~CUW~98_33#MGNP'} Metrics: ['ELUC: -4.458890791245405', 'NSGA-II_crowding_distance: 0.6163795200389551', 'NSGA-II_rank: 4', 'change: 0.1468930400309775', 'is_elite: False']\n", + "Id: 100_57 Identity: {'ancestor_count': 96, 'ancestor_ids': ['99_28', '99_28'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_57', 'origin': '99_28~CUW~99_28#MGNP'} Metrics: ['ELUC: -4.516629714284427', 'NSGA-II_crowding_distance: 0.18053425648698831', 'NSGA-II_rank: 2', 'change: 0.08611809344999462', 'is_elite: False']\n", + "Id: 100_62 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_82', '99_78'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_62', 'origin': '99_82~CUW~99_78#MGNP'} Metrics: ['ELUC: -4.6956899135292804', 'NSGA-II_crowding_distance: 0.13927750519438833', 'NSGA-II_rank: 1', 'change: 0.07191575345932737', 'is_elite: False']\n", + "Id: 99_77 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_52', '98_99'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_77', 'origin': '98_52~CUW~98_99#MGNP'} Metrics: ['ELUC: -4.786621492362805', 'NSGA-II_crowding_distance: 0.12409552904968976', 'NSGA-II_rank: 3', 'change: 0.10014108561391086', 'is_elite: False']\n", + "Id: 100_29 Identity: {'ancestor_count': 96, 'ancestor_ids': ['1_1', '99_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_29', 'origin': '1_1~CUW~99_33#MGNP'} Metrics: ['ELUC: -4.803236512516223', 'NSGA-II_crowding_distance: 0.14783857456400196', 'NSGA-II_rank: 2', 'change: 0.09469055311685964', 'is_elite: False']\n", + "Id: 100_49 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_96', '99_78'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_49', 'origin': '99_96~CUW~99_78#MGNP'} Metrics: ['ELUC: -5.026417130024577', 'NSGA-II_crowding_distance: 0.8115911505439704', 'NSGA-II_rank: 4', 'change: 0.24342824308297398', 'is_elite: False']\n", + "Id: 100_14 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_28', '99_92'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_14', 'origin': '99_28~CUW~99_92#MGNP'} Metrics: ['ELUC: -5.156127313924989', 'NSGA-II_crowding_distance: 0.18107332262430317', 'NSGA-II_rank: 1', 'change: 0.08965619437043965', 'is_elite: False']\n", + "Id: 100_39 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '99_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_39', 'origin': '98_58~CUW~99_33#MGNP'} Metrics: ['ELUC: -5.755081103755628', 'NSGA-II_crowding_distance: 0.6638788942047011', 'NSGA-II_rank: 3', 'change: 0.10936075638104992', 'is_elite: False']\n", + "Id: 100_44 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_33', '2_49'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_44', 'origin': '98_33~CUW~2_49#MGNP'} Metrics: ['ELUC: -5.911078562692034', 'NSGA-II_crowding_distance: 1.3849415647856427', 'NSGA-II_rank: 5', 'change: 0.26824204079824226', 'is_elite: False']\n", + "Id: 100_13 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_82', '98_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_13', 'origin': '99_82~CUW~98_33#MGNP'} Metrics: ['ELUC: -5.9220888754356125', 'NSGA-II_crowding_distance: 0.5847305749087138', 'NSGA-II_rank: 2', 'change: 0.10535293958438562', 'is_elite: False']\n", + "Id: 100_26 Identity: {'ancestor_count': 98, 'ancestor_ids': ['98_33', '99_96'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_26', 'origin': '98_33~CUW~99_96#MGNP'} Metrics: ['ELUC: -6.0444157319966925', 'NSGA-II_crowding_distance: 0.831423843493029', 'NSGA-II_rank: 3', 'change: 0.26285178199273457', 'is_elite: False']\n", + "Id: 100_90 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_77', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_90', 'origin': '99_77~CUW~1_1#MGNP'} Metrics: ['ELUC: -6.102586120288507', 'NSGA-II_crowding_distance: 0.18742983290107584', 'NSGA-II_rank: 1', 'change: 0.10206853540898436', 'is_elite: True']\n", + "Id: 100_85 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_44', '2_49'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_85', 'origin': '99_44~CUW~2_49#MGNP'} Metrics: ['ELUC: -7.083005715844148', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 5', 'change: 0.26984813430572685', 'is_elite: False']\n", + "Id: 99_33 Identity: {'ancestor_count': 95, 'ancestor_ids': ['97_91', '98_94'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_33', 'origin': '97_91~CUW~98_94#MGNP'} Metrics: ['ELUC: -7.245663633353614', 'NSGA-II_crowding_distance: 0.12634205477480062', 'NSGA-II_rank: 1', 'change: 0.11012100424813916', 'is_elite: False']\n", + "Id: 100_45 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_33', '99_65'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_45', 'origin': '98_33~CUW~99_65#MGNP'} Metrics: ['ELUC: -7.648187493788322', 'NSGA-II_crowding_distance: 0.0796349647920418', 'NSGA-II_rank: 1', 'change: 0.11353685732892303', 'is_elite: False']\n", + "Id: 100_43 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '99_11'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_43', 'origin': '98_58~CUW~99_11#MGNP'} Metrics: ['ELUC: -7.6970353588338485', 'NSGA-II_crowding_distance: 0.21753284075932036', 'NSGA-II_rank: 1', 'change: 0.1262223857472967', 'is_elite: True']\n", + "Id: 100_19 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_96', '99_77'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_19', 'origin': '99_96~CUW~99_77#MGNP'} Metrics: ['ELUC: -9.057386476849961', 'NSGA-II_crowding_distance: 0.49252607413156696', 'NSGA-II_rank: 4', 'change: 0.26663024776750244', 'is_elite: False']\n", + "Id: 100_94 Identity: {'ancestor_count': 98, 'ancestor_ids': ['98_58', '99_96'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_94', 'origin': '98_58~CUW~99_96#MGNP'} Metrics: ['ELUC: -9.872499091950262', 'NSGA-II_crowding_distance: 0.15549740647727964', 'NSGA-II_rank: 4', 'change: 0.2747501304168125', 'is_elite: False']\n", + "Id: 100_46 Identity: {'ancestor_count': 96, 'ancestor_ids': ['99_28', '98_28'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_46', 'origin': '99_28~CUW~98_28#MGNP'} Metrics: ['ELUC: -9.934142274832222', 'NSGA-II_crowding_distance: 0.3167747389798797', 'NSGA-II_rank: 1', 'change: 0.13965045206364735', 'is_elite: True']\n", + "Id: 100_36 Identity: {'ancestor_count': 97, 'ancestor_ids': ['2_49', '99_92'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_36', 'origin': '2_49~CUW~99_92#MGNP'} Metrics: ['ELUC: -10.076702745003505', 'NSGA-II_crowding_distance: 0.1883793941896295', 'NSGA-II_rank: 4', 'change: 0.2867903596441608', 'is_elite: False']\n", + "Id: 100_40 Identity: {'ancestor_count': 97, 'ancestor_ids': ['2_49', '98_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_40', 'origin': '2_49~CUW~98_33#MGNP'} Metrics: ['ELUC: -10.29534482966264', 'NSGA-II_crowding_distance: 0.39906961086364234', 'NSGA-II_rank: 3', 'change: 0.26514420068346656', 'is_elite: False']\n", + "Id: 100_16 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_28', '99_31'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_16', 'origin': '99_28~CUW~99_31#MGNP'} Metrics: ['ELUC: -10.74130733897009', 'NSGA-II_crowding_distance: 0.6283768172320152', 'NSGA-II_rank: 2', 'change: 0.16477646539725765', 'is_elite: False']\n", + "Id: 100_35 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_44', '99_44'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_35', 'origin': '99_44~CUW~99_44#MGNP'} Metrics: ['ELUC: -11.326943320185316', 'NSGA-II_crowding_distance: 0.3007386195744487', 'NSGA-II_rank: 1', 'change: 0.159140251610121', 'is_elite: True']\n", + "Id: 100_37 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_78', '2_49'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_37', 'origin': '99_78~CUW~2_49#MGNP'} Metrics: ['ELUC: -11.673646906016488', 'NSGA-II_crowding_distance: 0.16419638499241956', 'NSGA-II_rank: 4', 'change: 0.2877832058648472', 'is_elite: False']\n", + "Id: 100_92 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_29', '99_28'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_92', 'origin': '99_29~CUW~99_28#MGNP'} Metrics: ['ELUC: -12.046908583137913', 'NSGA-II_crowding_distance: 0.1799918408276389', 'NSGA-II_rank: 2', 'change: 0.18472299008208842', 'is_elite: False']\n", + "Id: 100_31 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_31', 'origin': '2_49~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.065387458782244', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 4', 'change: 0.28972749279279475', 'is_elite: False']\n", + "Id: 100_86 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_96', '1_1'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_86', 'origin': '99_96~CUW~1_1#MGNP'} Metrics: ['ELUC: -12.196782375192399', 'NSGA-II_crowding_distance: 0.32669770873439297', 'NSGA-II_rank: 3', 'change: 0.27331784231601797', 'is_elite: False']\n", + "Id: 100_42 Identity: {'ancestor_count': 97, 'ancestor_ids': ['1_1', '98_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_42', 'origin': '1_1~CUW~98_33#MGNP'} Metrics: ['ELUC: -12.205913200271619', 'NSGA-II_crowding_distance: 0.3172470750392304', 'NSGA-II_rank: 2', 'change: 0.1920899438951008', 'is_elite: False']\n", + "Id: 100_61 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_92', '2_49'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_61', 'origin': '99_92~CUW~2_49#MGNP'} Metrics: ['ELUC: -12.45770717821082', 'NSGA-II_crowding_distance: 0.4712480092445426', 'NSGA-II_rank: 2', 'change: 0.2671626620341151', 'is_elite: False']\n", + "Id: 100_76 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_29', '99_29'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_76', 'origin': '99_29~CUW~99_29#MGNP'} Metrics: ['ELUC: -12.778409484185174', 'NSGA-II_crowding_distance: 0.28562414956435656', 'NSGA-II_rank: 1', 'change: 0.1811160629414977', 'is_elite: True']\n", + "Id: 98_33 Identity: {'ancestor_count': 96, 'ancestor_ids': ['97_100', '92_59'], 'birth_generation': 98, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '98_33', 'origin': '97_100~CUW~92_59#MGNP'} Metrics: ['ELUC: -14.066458518245582', 'NSGA-II_crowding_distance: 0.15189346668949472', 'NSGA-II_rank: 1', 'change: 0.19787371538524193', 'is_elite: False']\n", + "Id: 100_99 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_28', '99_44'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_99', 'origin': '98_28~CUW~99_44#MGNP'} Metrics: ['ELUC: -14.107568807967874', 'NSGA-II_crowding_distance: 0.07041093013887237', 'NSGA-II_rank: 1', 'change: 0.2038814450317184', 'is_elite: False']\n", + "Id: 100_30 Identity: {'ancestor_count': 97, 'ancestor_ids': ['99_44', '99_92'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_30', 'origin': '99_44~CUW~99_92#MGNP'} Metrics: ['ELUC: -14.50448878315128', 'NSGA-II_crowding_distance: 0.3501703223719818', 'NSGA-II_rank: 1', 'change: 0.2114492592046504', 'is_elite: True']\n", + "Id: 100_23 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_96', '99_92'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_23', 'origin': '99_96~CUW~99_92#MGNP'} Metrics: ['ELUC: -14.61210767200822', 'NSGA-II_crowding_distance: 0.3451365985018875', 'NSGA-II_rank: 3', 'change: 0.2853636553125429', 'is_elite: False']\n", + "Id: 100_84 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_28', '99_96'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_84', 'origin': '99_28~CUW~99_96#MGNP'} Metrics: ['ELUC: -15.163295640463579', 'NSGA-II_crowding_distance: 0.2117156481975479', 'NSGA-II_rank: 2', 'change: 0.27746135396767885', 'is_elite: False']\n", + "Id: 100_48 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_18', '99_29'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_48', 'origin': '99_18~CUW~99_29#MGNP'} Metrics: ['ELUC: -15.391189611490404', 'NSGA-II_crowding_distance: 0.035895203921226984', 'NSGA-II_rank: 2', 'change: 0.2801597063308284', 'is_elite: False']\n", + "Id: 100_24 Identity: {'ancestor_count': 98, 'ancestor_ids': ['98_33', '99_96'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_24', 'origin': '98_33~CUW~99_96#MGNP'} Metrics: ['ELUC: -15.509996801200487', 'NSGA-II_crowding_distance: 0.07014694015382963', 'NSGA-II_rank: 2', 'change: 0.28204537069391244', 'is_elite: False']\n", + "Id: 100_12 Identity: {'ancestor_count': 97, 'ancestor_ids': ['2_49', '99_92'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_12', 'origin': '2_49~CUW~99_92#MGNP'} Metrics: ['ELUC: -15.540884836970662', 'NSGA-II_crowding_distance: 0.12056587093990334', 'NSGA-II_rank: 2', 'change: 0.29745798168636445', 'is_elite: False']\n", + "Id: 99_18 Identity: {'ancestor_count': 96, 'ancestor_ids': ['98_63', '98_64'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_18', 'origin': '98_63~CUW~98_64#MGNP'} Metrics: ['ELUC: -15.932702757927515', 'NSGA-II_crowding_distance: 0.3578030850843226', 'NSGA-II_rank: 1', 'change: 0.27739137988384993', 'is_elite: True']\n", + "Id: 100_56 Identity: {'ancestor_count': 3, 'ancestor_ids': ['2_49', '99_82'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_56', 'origin': '2_49~CUW~99_82#MGNP'} Metrics: ['ELUC: -16.160157579122025', 'NSGA-II_crowding_distance: 0.10055092790179956', 'NSGA-II_rank: 1', 'change: 0.2901125162361418', 'is_elite: False']\n", + "Id: 100_20 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_96', '2_49'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_20', 'origin': '99_96~CUW~2_49#MGNP'} Metrics: ['ELUC: -16.37134724815696', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 3', 'change: 0.3009235044619721', 'is_elite: False']\n", + "Id: 100_73 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_28', '99_96'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_73', 'origin': '99_28~CUW~99_96#MGNP'} Metrics: ['ELUC: -16.49543613875838', 'NSGA-II_crowding_distance: 0.11903086557573778', 'NSGA-II_rank: 2', 'change: 0.3002717399702601', 'is_elite: False']\n", + "Id: 100_91 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_96', '98_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_91', 'origin': '99_96~CUW~98_33#MGNP'} Metrics: ['ELUC: -16.72042713619064', 'NSGA-II_crowding_distance: 0.11304085407884282', 'NSGA-II_rank: 1', 'change: 0.2940256104788066', 'is_elite: False']\n", + "Id: 100_95 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_58', '2_49'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_95', 'origin': '98_58~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.392068901048987', 'NSGA-II_crowding_distance: 0.060624762300744775', 'NSGA-II_rank: 2', 'change: 0.30157470951647747', 'is_elite: False']\n", + "Id: 100_80 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_96', '99_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_80', 'origin': '99_96~CUW~99_33#MGNP'} Metrics: ['ELUC: -17.449301059229764', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 2', 'change: 0.3021943399994233', 'is_elite: False']\n", + "Id: 100_55 Identity: {'ancestor_count': 97, 'ancestor_ids': ['98_33', '99_18'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_55', 'origin': '98_33~CUW~99_18#MGNP'} Metrics: ['ELUC: -17.52003533236243', 'NSGA-II_crowding_distance: 0.08002316157751259', 'NSGA-II_rank: 1', 'change: 0.30076384336385587', 'is_elite: False']\n", + "Id: 2_49 Identity: {'ancestor_count': 1, 'ancestor_ids': ['1_28', '1_35'], 'birth_generation': 2, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '2_49', 'origin': '1_28~CUW~1_35#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "Id: 99_96 Identity: {'ancestor_count': 97, 'ancestor_ids': ['2_49', '98_62'], 'birth_generation': 99, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '99_96', 'origin': '2_49~CUW~98_62#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 100_15 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_96', '2_49'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_15', 'origin': '99_96~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 100_25 Identity: {'ancestor_count': 98, 'ancestor_ids': ['99_29', '99_96'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_25', 'origin': '99_29~CUW~99_96#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 100_52 Identity: {'ancestor_count': 2, 'ancestor_ids': ['2_49', '2_49'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_52', 'origin': '2_49~CUW~2_49#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: 0.0', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: False']\n", + "Id: 100_98 Identity: {'ancestor_count': 97, 'ancestor_ids': ['2_49', '98_33'], 'birth_generation': 100, 'domain_name': None, 'experiment_version': 'no-overlap', 'unique_id': '100_98', 'origin': '2_49~CUW~98_33#MGNP'} Metrics: ['ELUC: -17.597388193016204', 'NSGA-II_crowding_distance: inf', 'NSGA-II_rank: 1', 'change: 0.303020439141665', 'is_elite: True']\n", + "\n", + "Done with generation 100.\n", + "--------\n", + "\n", + "Done training in 43524.23 seconds.\n", + "representation: NNWeights\n", + "next_population average time: 0.4854\n", + "evaluate_population average time: 432.8242\n", + "next_population times: [0.3740518093109131, 0.1789250373840332, 0.18407201766967773, 0.1801588535308838, 0.17672228813171387, 0.1511678695678711, 0.16870689392089844, 0.18043804168701172, 0.5209460258483887, 16.128835916519165, 0.18066930770874023, 0.17770075798034668, 0.1825869083404541, 0.15593671798706055, 0.16141176223754883, 0.1927170753479004, 0.20873117446899414, 0.18484997749328613, 0.16379809379577637, 0.2034618854522705, 0.18621587753295898, 0.17078208923339844, 0.16803193092346191, 0.1753673553466797, 0.1810290813446045, 0.1978609561920166, 0.2443530559539795, 0.210557222366333, 0.1946089267730713, 0.1795337200164795, 0.19979214668273926, 0.202254056930542, 0.18121099472045898, 0.22707009315490723, 0.22780990600585938, 0.1994309425354004, 0.22921299934387207, 0.19161415100097656, 0.17596697807312012, 0.3300297260284424, 0.20397090911865234, 0.21180009841918945, 0.21247386932373047, 0.2330029010772705, 0.18710613250732422, 0.20577788352966309, 0.20298504829406738, 0.21145987510681152, 0.2021639347076416, 0.18668103218078613, 0.20798325538635254, 0.19258499145507812, 0.19867992401123047, 0.21401381492614746, 0.19850587844848633, 0.22699689865112305, 0.18903589248657227, 0.18698906898498535, 0.21305012702941895, 0.1819758415222168, 0.19646310806274414, 0.22599101066589355, 0.21715974807739258, 0.20891785621643066, 0.19528913497924805, 0.18751001358032227, 0.21609878540039062, 0.19349002838134766, 0.23784279823303223, 0.19317889213562012, 11.875107765197754, 0.20056414604187012, 0.19664883613586426, 0.18945574760437012, 0.20355677604675293, 0.2311089038848877, 0.21558785438537598, 0.20448088645935059, 0.2094268798828125, 0.21153903007507324, 0.22907376289367676, 0.21055984497070312, 0.25650906562805176, 0.21192598342895508, 0.22164130210876465, 0.22121810913085938, 0.23614287376403809, 0.20662307739257812, 0.21935486793518066, 0.24855613708496094, 0.23523807525634766, 0.23766183853149414, 0.20897197723388672, 0.22983813285827637, 0.22025179862976074, 0.21370315551757812, 0.25136375427246094, 0.22481417655944824, 0.21277499198913574, 0.2344040870666504]\n", + "evaluate_population times: [439.6124470233917, 440.4513211250305, 434.5927929878235, 435.8162491321564, 436.7587420940399, 437.08970522880554, 435.109806060791, 436.3007276058197, 436.98778080940247, 436.9964680671692, 436.0698161125183, 429.7945091724396, 428.23713421821594, 428.4324700832367, 428.21227979660034, 428.8842408657074, 430.04585886001587, 430.08490109443665, 429.24136877059937, 429.27363300323486, 429.9732418060303, 429.54248666763306, 429.50381231307983, 431.2183258533478, 431.044016122818, 430.10930609703064, 432.94212770462036, 429.48091197013855, 430.9528331756592, 430.3665888309479, 431.7771408557892, 430.82800698280334, 432.29192876815796, 431.55701088905334, 431.37421107292175, 431.53426933288574, 430.6682929992676, 430.9740500450134, 431.52996826171875, 428.96363973617554, 430.550901889801, 431.62160205841064, 432.03915309906006, 431.69153785705566, 432.28355979919434, 431.81128001213074, 432.2680151462555, 430.23334193229675, 431.79486107826233, 431.1438581943512, 432.27707409858704, 432.4741749763489, 432.8248028755188, 433.38252806663513, 432.8592607975006, 433.2197251319885, 431.56129789352417, 435.3316650390625, 432.96097469329834, 433.82517194747925, 432.6362018585205, 432.8345549106598, 433.20977878570557, 432.84031891822815, 431.118775844574, 432.60846424102783, 432.5553169250488, 432.93637704849243, 432.2855041027069, 435.0758969783783, 433.07992601394653, 433.41545486450195, 434.93521881103516, 434.4984450340271, 432.4624469280243, 434.9265470504761, 434.95959520339966, 434.5601170063019, 433.6357309818268, 434.1482162475586, 433.13092827796936, 432.0078709125519, 433.35203409194946, 433.5649929046631, 436.5023760795593, 435.293475151062, 434.54933285713196, 433.17008113861084, 434.52593517303467, 433.398992061615, 434.1856412887573, 434.1118550300598, 434.4438362121582, 433.2410218715668, 435.4763879776001, 435.015615940094, 433.4966609477997, 432.05756402015686, 435.4689610004425, 435.923024892807]\n" ] } ], @@ -989,11 +66484,13 @@ "\n", "print(\"Running prescriptor training...\")\n", "config_path = Path(\"prescriptors/unileaf_configs/config-loctime-crop-nosoft.json\")\n", + "seed_path = Path(\"prescriptors/seeds/no-overlap\")\n", "presc_config = None\n", "with open(config_path, \"r\") as f:\n", " presc_config = json.load(f)\n", - " presc_config[\"LEAF\"][\"experiment_id\"] = \"test\"\n", + " presc_config[\"LEAF\"][\"experiment_id\"] = \"no-overlap\"\n", " presc_config[\"LEAF\"][\"version\"] = \"1.0\"\n", + " presc_config[\"evolution\"][\"seed_weights_dir\"] = str(seed_path.resolve())\n", "\n", "eval_df_encoded = dataset.get_encoded_train().sample(frac=0.001, random_state=42)\n", "esp_service = EspService(presc_config, esp_username, esp_password)\n", From 40662b70d294614a6b772c9133ca103cb560f3fd Mon Sep 17 00:00:00 2001 From: Daniel Young Date: Fri, 23 Feb 2024 08:35:57 -0800 Subject: [PATCH 2/7] Set up experiments so I can run them over a few days --- .../experiments/predictor_experiments.ipynb | 131 ++++++------------ 1 file changed, 43 insertions(+), 88 deletions(-) diff --git a/use_cases/eluc/experiments/predictor_experiments.ipynb b/use_cases/eluc/experiments/predictor_experiments.ipynb index 7a24284..604e96d 100644 --- a/use_cases/eluc/experiments/predictor_experiments.ipynb +++ b/use_cases/eluc/experiments/predictor_experiments.ipynb @@ -181,21 +181,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "metadata": {}, - "outputs": [ - { - "ename": "type", - "evalue": "invalid syntax. Perhaps you forgot a comma? (48693919.py, line 2)", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mSyntaxError\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/IPython/core/compilerop.py:105\u001b[0m, in \u001b[0;36mCachingCompiler.ast_parse\u001b[0;34m(self, source, filename, symbol)\u001b[0m\n\u001b[1;32m 100\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mast_parse\u001b[39m(\u001b[38;5;28mself\u001b[39m, source, filename\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\u001b[39m\u001b[38;5;124m'\u001b[39m, symbol\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mexec\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m 101\u001b[0m \u001b[38;5;124;03m\"\"\"Parse code to an AST with the current compiler flags active.\u001b[39;00m\n\u001b[1;32m 102\u001b[0m \n\u001b[1;32m 103\u001b[0m \u001b[38;5;124;03m Arguments are exactly the same as ast.parse (in the standard library),\u001b[39;00m\n\u001b[1;32m 104\u001b[0m \u001b[38;5;124;03m and are passed to the built-in compile function.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 105\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcompile\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43msource\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msymbol\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mflags\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m|\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mPyCF_ONLY_AST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n", - "\u001b[0;31mSyntaxError\u001b[0m: invalid syntax. Perhaps you forgot a comma? (48693919.py, line 2)" - ] - } - ], + "outputs": [], "source": [ "forest_config = {\n", " \"features\": constants.NN_FEATS,\n", @@ -395,11 +383,11 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ - "def train_and_test(n: int, model_constructor, config: dict, train_df: pd.DataFrame, test_df: pd.DataFrame, save_path: Path, override_start_year=None):\n", + "def train_and_test(n: int, model_constructor, config: dict, train_df: pd.DataFrame, test_df: pd.DataFrame, train_regions: list, save_path: Path, override_start_year=None):\n", " \"\"\"\n", " Trains a model n times on each region and evaluates each model on each region.\n", " :param n: Number of times to train each model on each region.\n", @@ -415,9 +403,12 @@ "\n", " save_dir = save_path.parent\n", " save_dir.mkdir(parents=True, exist_ok=True)\n", - " with open(save_path, \"w\") as f:\n", + " if not save_path.is_file():\n", + " with open(save_path, \"w\") as f:\n", + " f.write(\"region,test,mae,time\\n\")\n", + " with open(save_path, \"a\") as f:\n", " # Iterate over all regions\n", - " for train_region in constants.COUNTRY_DICT.keys():\n", + " for train_region in train_regions:\n", " print(train_region)\n", " if train_region != \"ALL\":\n", " countries = constants.COUNTRY_DICT[train_region]\n", @@ -456,55 +447,14 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "EU\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 30/30 [00:06<00:00, 4.42it/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "SA\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 30/30 [00:23<00:00, 1.25it/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "US\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 30/30 [00:22<00:00, 1.35it/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "neural_network\n", "ALL\n" ] }, @@ -512,54 +462,59 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 30/30 [02:49<00:00, 5.64s/it]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EU\n" + " 0%| | 0/30 [00:00\u001b[0;34m()\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m model_name \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrandom_forest\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 8\u001b[0m override_start_year \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1982\u001b[39m\n\u001b[0;32m----> 9\u001b[0m \u001b[43mtrain_and_test\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m30\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel_constructor\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_df\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtest_df\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msignificance_path\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mmodel_name\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_eval.csv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moverride_start_year\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moverride_start_year\u001b[49m\u001b[43m)\u001b[49m\n", - "Input \u001b[0;32mIn [6]\u001b[0m, in \u001b[0;36mtrain_and_test\u001b[0;34m(n, model_constructor, config, train_df, test_df, save_path, override_start_year)\u001b[0m\n\u001b[1;32m 30\u001b[0m model \u001b[38;5;241m=\u001b[39m model_constructor(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mconfig)\n\u001b[1;32m 31\u001b[0m s \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m---> 32\u001b[0m _ \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_region_df\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_region_df\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mELUC\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 33\u001b[0m e \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[1;32m 34\u001b[0m \u001b[38;5;66;03m# Evaluate on each region\u001b[39;00m\n", - "File \u001b[0;32m~/workspace/mvp/use_cases/eluc/predictors/sklearn/sklearn_predictor.py:62\u001b[0m, in \u001b[0;36mSKLearnPredictor.fit\u001b[0;34m(self, X_train, y_train)\u001b[0m\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfeatures \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(X_train\u001b[38;5;241m.\u001b[39mcolumns)\n\u001b[1;32m 61\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlabel \u001b[38;5;241m=\u001b[39m y_train\u001b[38;5;241m.\u001b[39mname\n\u001b[0;32m---> 62\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_train\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/sklearn/ensemble/_forest.py:345\u001b[0m, in \u001b[0;36mBaseForest.fit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m 343\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m issparse(y):\n\u001b[1;32m 344\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msparse multilabel-indicator for y is not supported.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m--> 345\u001b[0m X, y \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_data\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 346\u001b[0m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmulti_output\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maccept_sparse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcsc\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mDTYPE\u001b[49m\n\u001b[1;32m 347\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 348\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m sample_weight \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 349\u001b[0m sample_weight \u001b[38;5;241m=\u001b[39m _check_sample_weight(sample_weight, X)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/sklearn/base.py:584\u001b[0m, in \u001b[0;36mBaseEstimator._validate_data\u001b[0;34m(self, X, y, reset, validate_separately, **check_params)\u001b[0m\n\u001b[1;32m 582\u001b[0m y \u001b[38;5;241m=\u001b[39m check_array(y, input_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mcheck_y_params)\n\u001b[1;32m 583\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 584\u001b[0m X, y \u001b[38;5;241m=\u001b[39m \u001b[43mcheck_X_y\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcheck_params\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 585\u001b[0m out \u001b[38;5;241m=\u001b[39m X, y\n\u001b[1;32m 587\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m no_val_X \u001b[38;5;129;01mand\u001b[39;00m check_params\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mensure_2d\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mTrue\u001b[39;00m):\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/sklearn/utils/validation.py:1106\u001b[0m, in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)\u001b[0m\n\u001b[1;32m 1101\u001b[0m estimator_name \u001b[38;5;241m=\u001b[39m _check_estimator_name(estimator)\n\u001b[1;32m 1102\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 1103\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mestimator_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m requires y to be passed, but the target y is None\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1104\u001b[0m )\n\u001b[0;32m-> 1106\u001b[0m X \u001b[38;5;241m=\u001b[39m \u001b[43mcheck_array\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1107\u001b[0m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1108\u001b[0m \u001b[43m \u001b[49m\u001b[43maccept_sparse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maccept_sparse\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1109\u001b[0m \u001b[43m \u001b[49m\u001b[43maccept_large_sparse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maccept_large_sparse\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1110\u001b[0m \u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1111\u001b[0m \u001b[43m \u001b[49m\u001b[43morder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43morder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1112\u001b[0m \u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1113\u001b[0m \u001b[43m \u001b[49m\u001b[43mforce_all_finite\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce_all_finite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1114\u001b[0m \u001b[43m \u001b[49m\u001b[43mensure_2d\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_2d\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1115\u001b[0m \u001b[43m \u001b[49m\u001b[43mallow_nd\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallow_nd\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1116\u001b[0m \u001b[43m \u001b[49m\u001b[43mensure_min_samples\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_min_samples\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1117\u001b[0m \u001b[43m \u001b[49m\u001b[43mensure_min_features\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_min_features\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1118\u001b[0m \u001b[43m \u001b[49m\u001b[43mestimator\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1119\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mX\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1120\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1122\u001b[0m y \u001b[38;5;241m=\u001b[39m _check_y(y, multi_output\u001b[38;5;241m=\u001b[39mmulti_output, y_numeric\u001b[38;5;241m=\u001b[39my_numeric, estimator\u001b[38;5;241m=\u001b[39mestimator)\n\u001b[1;32m 1124\u001b[0m check_consistent_length(X, y)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/sklearn/utils/validation.py:879\u001b[0m, in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)\u001b[0m\n\u001b[1;32m 877\u001b[0m array \u001b[38;5;241m=\u001b[39m xp\u001b[38;5;241m.\u001b[39mastype(array, dtype, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 878\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 879\u001b[0m array \u001b[38;5;241m=\u001b[39m \u001b[43m_asarray_with_order\u001b[49m\u001b[43m(\u001b[49m\u001b[43marray\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43morder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43morder\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mxp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mxp\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 880\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ComplexWarning \u001b[38;5;28;01mas\u001b[39;00m complex_warning:\n\u001b[1;32m 881\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 882\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mComplex data not supported\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(array)\n\u001b[1;32m 883\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mcomplex_warning\u001b[39;00m\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/sklearn/utils/_array_api.py:185\u001b[0m, in \u001b[0;36m_asarray_with_order\u001b[0;34m(array, dtype, order, copy, xp)\u001b[0m\n\u001b[1;32m 182\u001b[0m xp, _ \u001b[38;5;241m=\u001b[39m get_namespace(array)\n\u001b[1;32m 183\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m xp\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m \u001b[38;5;129;01min\u001b[39;00m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnumpy\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnumpy.array_api\u001b[39m\u001b[38;5;124m\"\u001b[39m}:\n\u001b[1;32m 184\u001b[0m \u001b[38;5;66;03m# Use NumPy API to support order\u001b[39;00m\n\u001b[0;32m--> 185\u001b[0m array \u001b[38;5;241m=\u001b[39m \u001b[43mnumpy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43masarray\u001b[49m\u001b[43m(\u001b[49m\u001b[43marray\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43morder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43morder\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 186\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m xp\u001b[38;5;241m.\u001b[39masarray(array, copy\u001b[38;5;241m=\u001b[39mcopy)\n\u001b[1;32m 187\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/pandas/core/generic.py:2070\u001b[0m, in \u001b[0;36mNDFrame.__array__\u001b[0;34m(self, dtype)\u001b[0m\n\u001b[1;32m 2069\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__array__\u001b[39m(\u001b[38;5;28mself\u001b[39m, dtype: npt\u001b[38;5;241m.\u001b[39mDTypeLike \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m np\u001b[38;5;241m.\u001b[39mndarray:\n\u001b[0;32m-> 2070\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43masarray\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_values\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[0;31mValueError\u001b[0m: could not convert string to float: 'France'" + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Input \u001b[0;32mIn [13]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 15\u001b[0m override_start_year \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1982\u001b[39m\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28mprint\u001b[39m(model_name)\n\u001b[0;32m---> 17\u001b[0m \u001b[43mtrain_and_test\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m30\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 18\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel_constructor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 19\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 20\u001b[0m \u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_df\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 21\u001b[0m \u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtest_df\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 22\u001b[0m \u001b[43m \u001b[49m\u001b[43mtrain_regions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 23\u001b[0m \u001b[43m \u001b[49m\u001b[43msignificance_path\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mmodel_name\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_eval.csv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 24\u001b[0m \u001b[43m \u001b[49m\u001b[43moverride_start_year\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moverride_start_year\u001b[49m\u001b[43m)\u001b[49m\n", + "Input \u001b[0;32mIn [12]\u001b[0m, in \u001b[0;36mtrain_and_test\u001b[0;34m(n, model_constructor, config, train_df, test_df, train_regions, save_path, override_start_year)\u001b[0m\n\u001b[1;32m 33\u001b[0m model \u001b[38;5;241m=\u001b[39m model_constructor(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mconfig)\n\u001b[1;32m 34\u001b[0m s \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m---> 35\u001b[0m _ \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_region_df\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_region_df\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mELUC\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 36\u001b[0m e \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[1;32m 37\u001b[0m \u001b[38;5;66;03m# Evaluate on each region\u001b[39;00m\n", + "File \u001b[0;32m~/workspace/mvp/use_cases/eluc/predictors/neural_network/neural_net_predictor.py:222\u001b[0m, in \u001b[0;36mNeuralNetPredictor.fit\u001b[0;34m(self, X_train, y_train, X_val, y_val, X_test, y_test, log_path, verbose)\u001b[0m\n\u001b[1;32m 220\u001b[0m \u001b[38;5;66;03m# Standard training loop\u001b[39;00m\n\u001b[1;32m 221\u001b[0m train_iter \u001b[38;5;241m=\u001b[39m tqdm(train_dl) \u001b[38;5;28;01mif\u001b[39;00m verbose \u001b[38;5;28;01melse\u001b[39;00m train_dl\n\u001b[0;32m--> 222\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m X, y \u001b[38;5;129;01min\u001b[39;00m train_iter:\n\u001b[1;32m 223\u001b[0m X, y \u001b[38;5;241m=\u001b[39m X\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice), y\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m 224\u001b[0m optimizer\u001b[38;5;241m.\u001b[39mzero_grad()\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/torch/utils/data/dataloader.py:631\u001b[0m, in \u001b[0;36m_BaseDataLoaderIter.__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 628\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sampler_iter \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 629\u001b[0m \u001b[38;5;66;03m# TODO(https://github.com/pytorch/pytorch/issues/76750)\u001b[39;00m\n\u001b[1;32m 630\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reset() \u001b[38;5;66;03m# type: ignore[call-arg]\u001b[39;00m\n\u001b[0;32m--> 631\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_next_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 632\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_yielded \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 633\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dataset_kind \u001b[38;5;241m==\u001b[39m _DatasetKind\u001b[38;5;241m.\u001b[39mIterable \u001b[38;5;129;01mand\u001b[39;00m \\\n\u001b[1;32m 634\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_IterableDataset_len_called \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \\\n\u001b[1;32m 635\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_yielded \u001b[38;5;241m>\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_IterableDataset_len_called:\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/torch/utils/data/dataloader.py:675\u001b[0m, in \u001b[0;36m_SingleProcessDataLoaderIter._next_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 673\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_next_data\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 674\u001b[0m index \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_next_index() \u001b[38;5;66;03m# may raise StopIteration\u001b[39;00m\n\u001b[0;32m--> 675\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_dataset_fetcher\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfetch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mindex\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# may raise StopIteration\u001b[39;00m\n\u001b[1;32m 676\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pin_memory:\n\u001b[1;32m 677\u001b[0m data \u001b[38;5;241m=\u001b[39m _utils\u001b[38;5;241m.\u001b[39mpin_memory\u001b[38;5;241m.\u001b[39mpin_memory(data, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pin_memory_device)\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:51\u001b[0m, in \u001b[0;36m_MapDatasetFetcher.fetch\u001b[0;34m(self, possibly_batched_index)\u001b[0m\n\u001b[1;32m 49\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset\u001b[38;5;241m.\u001b[39m__getitems__(possibly_batched_index)\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 51\u001b[0m data \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset[idx] \u001b[38;5;28;01mfor\u001b[39;00m idx \u001b[38;5;129;01min\u001b[39;00m possibly_batched_index]\n\u001b[1;32m 52\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 53\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset[possibly_batched_index]\n", + "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:51\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 49\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset\u001b[38;5;241m.\u001b[39m__getitems__(possibly_batched_index)\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 51\u001b[0m data \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset[idx] \u001b[38;5;28;01mfor\u001b[39;00m idx \u001b[38;5;129;01min\u001b[39;00m possibly_batched_index]\n\u001b[1;32m 52\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 53\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset[possibly_batched_index]\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " ] } ], "source": [ - "model_constructors = [LinearRegressionPredictor, RandomForestPredictor, NeuralNetPredictor]\n", - "configs = [linreg_config, forest_config, nn_config]\n", - "model_names = [\"linear_regression\", \"random_forest\", \"neural_network\"]\n", + "forest_config = {\n", + " \"features\": constants.NN_FEATS,\n", + " \"n_jobs\": -1,\n", + " \"max_features\": \"sqrt\"\n", + "}\n", + "model_constructors = [NeuralNetPredictor, RandomForestPredictor, LinearRegressionPredictor]\n", + "configs = [nn_config, forest_config, linreg_config]\n", + "model_names = [\"neural_network\", \"random_forest\", \"linear_regression\"]\n", + "#train_regions = constants.COUNTRY_DICT.keys()\n", + "train_regions = [\"ALL\"]\n", "significance_path = Path(\"experiments/predictor_significance/no_overlap\")\n", - "for model_constructor, config, model_name in zip(model_constructors, configs, model_names):\n", + "for model_constructor, config, model_name in zip(model_constructors[0:1], configs[0:1], model_names[0:1]):\n", " override_start_year = None\n", " if model_name == \"random_forest\":\n", " override_start_year = 1982\n", " print(model_name)\n", - " train_and_test(30, model_constructor, config, dataset.train_df, dataset.test_df, significance_path / f\"{model_name}_eval.csv\", override_start_year=override_start_year)" + " train_and_test(30,\n", + " model_constructor,\n", + " config,\n", + " dataset.train_df,\n", + " dataset.test_df,\n", + " train_regions,\n", + " significance_path / f\"{model_name}_eval.csv\",\n", + " override_start_year=override_start_year)" ] }, { From 9514ad04cc983918cc2572a09f153492fa267f23 Mon Sep 17 00:00:00 2001 From: Daniel Date: Fri, 1 Mar 2024 09:32:12 -0800 Subject: [PATCH 3/7] Fixed conversion to fit pandas 3. Added significance script to be run on linux machine --- use_cases/eluc/data/conversion.py | 4 +- .../experiments/predictor_significance.py | 107 ++++++++++++++++++ 2 files changed, 109 insertions(+), 2 deletions(-) create mode 100644 use_cases/eluc/experiments/predictor_significance.py diff --git a/use_cases/eluc/data/conversion.py b/use_cases/eluc/data/conversion.py index 737f606..5533694 100644 --- a/use_cases/eluc/data/conversion.py +++ b/use_cases/eluc/data/conversion.py @@ -48,8 +48,8 @@ def construct_countries_df(): # Replace all the bad codes with their real ones for i in range(len(countries_df)): - old_abbrev = countries_df.iloc[i]["abbrevs"] + old_abbrev = countries_df.loc[i, "abbrevs"] if old_abbrev in MANUAL_MAP.keys() and MANUAL_MAP[old_abbrev] in codes_df["Numeric code"].unique(): - countries_df.iloc[i]["abbrevs"] = codes_df[codes_df["Numeric code"] == MANUAL_MAP[old_abbrev]]["Alpha-2 code"].iloc[0] + countries_df.loc[i, "abbrevs"] = codes_df[codes_df["Numeric code"] == MANUAL_MAP[old_abbrev]]["Alpha-2 code"].iloc[0] return countries_df \ No newline at end of file diff --git a/use_cases/eluc/experiments/predictor_significance.py b/use_cases/eluc/experiments/predictor_significance.py new file mode 100644 index 0000000..8a31899 --- /dev/null +++ b/use_cases/eluc/experiments/predictor_significance.py @@ -0,0 +1,107 @@ +import time +from pathlib import Path + +import pandas as pd +from tqdm import tqdm +from sklearn.metrics import mean_absolute_error + +from data.eluc_data import ELUCData +from data import constants +from data.conversion import construct_countries_df +from predictors.neural_network.neural_net_predictor import NeuralNetPredictor +from predictors.sklearn.sklearn_predictor import RandomForestPredictor, LinearRegressionPredictor + +def train_and_test(n: int, model_constructor, config: dict, train_df: pd.DataFrame, test_df: pd.DataFrame, train_regions: list, save_path: Path, override_start_year=None): + """ + Trains a model n times on each region and evaluates each model on each region. + :param n: Number of times to train each model on each region. + :param model_constructor: A function that returns a model. + :param config: A dictionary of configuration parameters for each model type. + :param train_df: The training data. + :param test_df: The testing data. + :param save_path: The path to save the results. + :param override_start_year: If not None, overrides the start year of the test data on the ALL region. + (This is currently only used for the random forest) + """ + countries_df = construct_countries_df() + + save_dir = save_path.parent + save_dir.mkdir(parents=True, exist_ok=True) + if not save_path.is_file(): + with open(save_path, "w") as f: + f.write("region,test,mae,time\n") + with open(save_path, "a") as f: + # Iterate over all regions + for train_region in train_regions: + print(train_region) + if train_region != "ALL": + countries = constants.COUNTRY_DICT[train_region] + idx = countries_df[countries_df["abbrevs"].isin(countries)].index.values + train_region_df = train_df[train_df["country"].isin(idx)] + else: + train_region_df = train_df + + # n times for each region + for i in tqdm(range(n)): + model = model_constructor(**config) + s = time.time() + _ = model.fit(train_region_df, train_region_df["ELUC"]) + e = time.time() + # Evaluate on each region + for test_region in constants.COUNTRY_DICT.keys(): + if test_region != "ALL": + countries = constants.COUNTRY_DICT[test_region] + idx = countries_df[countries_df["abbrevs"].isin(countries)].index.values + test_region_df = test_df[test_df["country"].isin(idx)] + else: + test_region_df = test_df + if override_start_year: + test_region_df = test_region_df.loc[override_start_year:] + + mae = mean_absolute_error(model.predict(test_region_df), test_region_df["ELUC"]) + f.write(f"{train_region},{test_region},{mae},{e - s}\n") + +if __name__ == "__main__": + + dataset = ELUCData() + + nn_config = { + "features": constants.NN_FEATS, + "label": "ELUC", + "hidden_sizes": [4096], + "linear_skip": True, + "dropout": 0, + "device": "cuda", + "epochs": 3, + "batch_size": 2048, + "train_pct": 1, + "step_lr_params": {"step_size": 1, "gamma": 0.1}, + } + forest_config = { + "features": constants.NN_FEATS, + "n_jobs": -1, + "max_features": "sqrt" + } + linreg_config = { + "features": constants.DIFF_LAND_USE_COLS, + "n_jobs": -1, + } + model_constructors = [NeuralNetPredictor, RandomForestPredictor, LinearRegressionPredictor] + configs = [nn_config, forest_config, linreg_config] + model_names = ["neural_network", "random_forest", "linear_regression"] + #train_regions = constants.COUNTRY_DICT.keys() + train_regions = ["US", "ALL"] + significance_path = Path("experiments/predictor_significance/no_overlap") + for model_constructor, config, model_name in zip(model_constructors[1:2], configs[1:2], model_names[1:2]): + override_start_year = None + if model_name == "random_forest": + override_start_year = 1982 + print(model_name) + train_and_test(30, + model_constructor, + config, + dataset.train_df, + dataset.test_df, + train_regions, + significance_path / f"{model_name}_eval.csv", + override_start_year=override_start_year) \ No newline at end of file From a241979ba90a1e6e9ffd5fd388cb81e143eada1f Mon Sep 17 00:00:00 2001 From: Daniel Date: Wed, 13 Mar 2024 10:02:10 -0700 Subject: [PATCH 4/7] Updated predictor significance with fixed dataset! --- .../experiments/predictor_experiments.ipynb | 206 ++++-------------- .../experiments/predictor_significance.py | 85 ++++---- 2 files changed, 84 insertions(+), 207 deletions(-) diff --git a/use_cases/eluc/experiments/predictor_experiments.ipynb b/use_cases/eluc/experiments/predictor_experiments.ipynb index 604e96d..df2c645 100644 --- a/use_cases/eluc/experiments/predictor_experiments.ipynb +++ b/use_cases/eluc/experiments/predictor_experiments.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -378,155 +378,28 @@ "metadata": {}, "source": [ "### Statistical Significance\n", - "The models were tested by training them multiple times and comparing the samples using a t-test." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "def train_and_test(n: int, model_constructor, config: dict, train_df: pd.DataFrame, test_df: pd.DataFrame, train_regions: list, save_path: Path, override_start_year=None):\n", - " \"\"\"\n", - " Trains a model n times on each region and evaluates each model on each region.\n", - " :param n: Number of times to train each model on each region.\n", - " :param model_constructor: A function that returns a model.\n", - " :param config: A dictionary of configuration parameters for each model type.\n", - " :param train_df: The training data.\n", - " :param test_df: The testing data.\n", - " :param save_path: The path to save the results.\n", - " :param override_start_year: If not None, overrides the start year of the test data on the ALL region.\n", - " (This is currently only used for the random forest)\n", - " \"\"\"\n", - " countries_df = construct_countries_df()\n", - "\n", - " save_dir = save_path.parent\n", - " save_dir.mkdir(parents=True, exist_ok=True)\n", - " if not save_path.is_file():\n", - " with open(save_path, \"w\") as f:\n", - " f.write(\"region,test,mae,time\\n\")\n", - " with open(save_path, \"a\") as f:\n", - " # Iterate over all regions\n", - " for train_region in train_regions:\n", - " print(train_region)\n", - " if train_region != \"ALL\":\n", - " countries = constants.COUNTRY_DICT[train_region]\n", - " idx = countries_df[countries_df[\"abbrevs\"].isin(countries)].index.values\n", - " train_region_df = train_df[train_df[\"country\"].isin(idx)]\n", - " else:\n", - " train_region_df = train_df\n", - " \n", - " # n times for each region\n", - " for i in tqdm(range(n)):\n", - " model = model_constructor(**config)\n", - " s = time.time()\n", - " _ = model.fit(train_region_df, train_region_df[\"ELUC\"])\n", - " e = time.time()\n", - " # Evaluate on each region\n", - " for test_region in constants.COUNTRY_DICT.keys():\n", - " if test_region != \"ALL\":\n", - " countries = constants.COUNTRY_DICT[test_region]\n", - " idx = countries_df[countries_df[\"abbrevs\"].isin(countries)].index.values\n", - " test_region_df = test_df[test_df[\"country\"].isin(idx)]\n", - " else:\n", - " test_region_df = test_df\n", - " if override_start_year:\n", - " test_region_df = test_region_df.loc[override_start_year:]\n", - " \n", - " mae = mean_absolute_error(model.predict(test_region_df), test_region_df[\"ELUC\"])\n", - " f.write(f\"{train_region},{test_region},{mae},{e - s}\\n\")" + "The models were tested by training them multiple times via [predictor_significance.py](experiments/predictor_significance.py)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Generate results:" + "#### Load Results and Perform T-Test" ] }, { "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "neural_network\n", - "ALL\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 0%| | 0/30 [00:00\u001b[0;34m()\u001b[0m\n\u001b[1;32m 15\u001b[0m override_start_year \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1982\u001b[39m\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28mprint\u001b[39m(model_name)\n\u001b[0;32m---> 17\u001b[0m \u001b[43mtrain_and_test\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m30\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 18\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel_constructor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 19\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 20\u001b[0m \u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_df\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 21\u001b[0m \u001b[43m \u001b[49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtest_df\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 22\u001b[0m \u001b[43m \u001b[49m\u001b[43mtrain_regions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 23\u001b[0m \u001b[43m \u001b[49m\u001b[43msignificance_path\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mmodel_name\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_eval.csv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 24\u001b[0m \u001b[43m \u001b[49m\u001b[43moverride_start_year\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moverride_start_year\u001b[49m\u001b[43m)\u001b[49m\n", - "Input \u001b[0;32mIn [12]\u001b[0m, in \u001b[0;36mtrain_and_test\u001b[0;34m(n, model_constructor, config, train_df, test_df, train_regions, save_path, override_start_year)\u001b[0m\n\u001b[1;32m 33\u001b[0m model \u001b[38;5;241m=\u001b[39m model_constructor(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mconfig)\n\u001b[1;32m 34\u001b[0m s \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m---> 35\u001b[0m _ \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrain_region_df\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_region_df\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mELUC\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 36\u001b[0m e \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[1;32m 37\u001b[0m \u001b[38;5;66;03m# Evaluate on each region\u001b[39;00m\n", - "File \u001b[0;32m~/workspace/mvp/use_cases/eluc/predictors/neural_network/neural_net_predictor.py:222\u001b[0m, in \u001b[0;36mNeuralNetPredictor.fit\u001b[0;34m(self, X_train, y_train, X_val, y_val, X_test, y_test, log_path, verbose)\u001b[0m\n\u001b[1;32m 220\u001b[0m \u001b[38;5;66;03m# Standard training loop\u001b[39;00m\n\u001b[1;32m 221\u001b[0m train_iter \u001b[38;5;241m=\u001b[39m tqdm(train_dl) \u001b[38;5;28;01mif\u001b[39;00m verbose \u001b[38;5;28;01melse\u001b[39;00m train_dl\n\u001b[0;32m--> 222\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m X, y \u001b[38;5;129;01min\u001b[39;00m train_iter:\n\u001b[1;32m 223\u001b[0m X, y \u001b[38;5;241m=\u001b[39m X\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice), y\u001b[38;5;241m.\u001b[39mto(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m 224\u001b[0m optimizer\u001b[38;5;241m.\u001b[39mzero_grad()\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/torch/utils/data/dataloader.py:631\u001b[0m, in \u001b[0;36m_BaseDataLoaderIter.__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 628\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sampler_iter \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 629\u001b[0m \u001b[38;5;66;03m# TODO(https://github.com/pytorch/pytorch/issues/76750)\u001b[39;00m\n\u001b[1;32m 630\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reset() \u001b[38;5;66;03m# type: ignore[call-arg]\u001b[39;00m\n\u001b[0;32m--> 631\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_next_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 632\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_yielded \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 633\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dataset_kind \u001b[38;5;241m==\u001b[39m _DatasetKind\u001b[38;5;241m.\u001b[39mIterable \u001b[38;5;129;01mand\u001b[39;00m \\\n\u001b[1;32m 634\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_IterableDataset_len_called \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \\\n\u001b[1;32m 635\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_yielded \u001b[38;5;241m>\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_IterableDataset_len_called:\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/torch/utils/data/dataloader.py:675\u001b[0m, in \u001b[0;36m_SingleProcessDataLoaderIter._next_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 673\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_next_data\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 674\u001b[0m index \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_next_index() \u001b[38;5;66;03m# may raise StopIteration\u001b[39;00m\n\u001b[0;32m--> 675\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_dataset_fetcher\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfetch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mindex\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# may raise StopIteration\u001b[39;00m\n\u001b[1;32m 676\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pin_memory:\n\u001b[1;32m 677\u001b[0m data \u001b[38;5;241m=\u001b[39m _utils\u001b[38;5;241m.\u001b[39mpin_memory\u001b[38;5;241m.\u001b[39mpin_memory(data, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pin_memory_device)\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:51\u001b[0m, in \u001b[0;36m_MapDatasetFetcher.fetch\u001b[0;34m(self, possibly_batched_index)\u001b[0m\n\u001b[1;32m 49\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset\u001b[38;5;241m.\u001b[39m__getitems__(possibly_batched_index)\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 51\u001b[0m data \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset[idx] \u001b[38;5;28;01mfor\u001b[39;00m idx \u001b[38;5;129;01min\u001b[39;00m possibly_batched_index]\n\u001b[1;32m 52\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 53\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset[possibly_batched_index]\n", - "File \u001b[0;32m~/anaconda3/envs/leaf/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py:51\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 49\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset\u001b[38;5;241m.\u001b[39m__getitems__(possibly_batched_index)\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 51\u001b[0m data \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset[idx] \u001b[38;5;28;01mfor\u001b[39;00m idx \u001b[38;5;129;01min\u001b[39;00m possibly_batched_index]\n\u001b[1;32m 52\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 53\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdataset[possibly_batched_index]\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], - "source": [ - "forest_config = {\n", - " \"features\": constants.NN_FEATS,\n", - " \"n_jobs\": -1,\n", - " \"max_features\": \"sqrt\"\n", - "}\n", - "model_constructors = [NeuralNetPredictor, RandomForestPredictor, LinearRegressionPredictor]\n", - "configs = [nn_config, forest_config, linreg_config]\n", - "model_names = [\"neural_network\", \"random_forest\", \"linear_regression\"]\n", - "#train_regions = constants.COUNTRY_DICT.keys()\n", - "train_regions = [\"ALL\"]\n", - "significance_path = Path(\"experiments/predictor_significance/no_overlap\")\n", - "for model_constructor, config, model_name in zip(model_constructors[0:1], configs[0:1], model_names[0:1]):\n", - " override_start_year = None\n", - " if model_name == \"random_forest\":\n", - " override_start_year = 1982\n", - " print(model_name)\n", - " train_and_test(30,\n", - " model_constructor,\n", - " config,\n", - " dataset.train_df,\n", - " dataset.test_df,\n", - " train_regions,\n", - " significance_path / f\"{model_name}_eval.csv\",\n", - " override_start_year=override_start_year)" - ] - }, - { - "cell_type": "markdown", + "execution_count": 5, "metadata": {}, + "outputs": [], "source": [ - "#### Load Results and Perform T-Test" + "significance_path = Path(\"experiments/predictor_significance/no_overlap_fixed\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -537,7 +410,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -545,18 +418,18 @@ "output_type": "stream", "text": [ "EU p-value forest < nn: 1.0\n", - "SA p-value forest < nn: 4.081372920256761e-96\n", - "US p-value forest < nn: 8.865504240014044e-41\n", - "ALL p-value forest < nn: 5.399007032681815e-49\n" + "SA p-value forest < nn: 1.601086174014152e-93\n", + "US p-value forest < nn: 1.0\n", + "ALL p-value forest < nn: 2.01460753545334e-33\n" ] } ], "source": [ "for region in constants.COUNTRY_DICT.keys():\n", - " lr_region_results = linreg_results[(linreg_results[\"region\"] == region) & (linreg_results[\"eval\"] == region)] \n", - " region_results = forest_results[(forest_results[\"region\"] == region) & (forest_results[\"eval\"] == region)]\n", - " other_results = nn_results[(nn_results[\"region\"] == region) & (nn_results[\"eval\"] == region)]\n", - " print(f\"{region} p-value forest < nn: {ttest_ind(region_results['mae'], other_results['mae'], alternative='less').pvalue}\")" + " lr_region_results = linreg_results[linreg_results[\"train\"] == region][region]\n", + " forest_region_results = forest_results[forest_results[\"train\"] == region][region]\n", + " nn_region_results = nn_results[nn_results[\"train\"] == region][region]\n", + " print(f\"{region} p-value forest < nn: {ttest_ind(forest_region_results, nn_region_results, alternative='less').pvalue}\")" ] }, { @@ -569,7 +442,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -581,17 +454,18 @@ " Prints by region.\n", " \"\"\"\n", " for region in constants.COUNTRY_DICT.keys():\n", - " region_results = self_results[self_results[\"region\"] == region]\n", - " row = f\"{self_name} ({region if region != 'ALL' else 'Global'}) & {region_results['time'].mean():.4f}\"\n", + " region_results = self_results[self_results[\"train\"] == region]\n", + " row = f\"{self_name} ({region if region != 'ALL' else 'Global'}) & {region_results['time'].mean():.3f}\"\n", "\n", " for eval_region in constants.COUNTRY_DICT.keys():\n", " # Other model significance test\n", - " region_maes = region_results[region_results['eval'] == eval_region]['mae']\n", - " other_maes = other_results[(other_results[\"region\"] == region) & (other_results[\"eval\"] == eval_region)][\"mae\"]\n", + " region_maes = region_results[eval_region]\n", + " other_maes = other_results[other_results[\"train\"] == region][eval_region]\n", " other_pval = ttest_ind(region_maes, other_maes, alternative=\"less\").pvalue\n", "\n", " # Linreg significance test\n", - " linreg_mae = linreg_results[(linreg_results[\"region\"] == region) & (linreg_results[\"eval\"] == eval_region)].iloc[0][\"mae\"]\n", + " # We only need 1 sample from linreg because it's deterministic\n", + " linreg_mae = linreg_results[linreg_results[\"train\"] == region][eval_region].iloc[0]\n", " linreg_pval = ttest_1samp(region_maes, linreg_mae, alternative=\"less\").pvalue\n", "\n", " # Best method bolding\n", @@ -599,7 +473,7 @@ " if region == eval_region and region_maes.mean() < other_maes.mean():\n", " bold = True\n", "\n", - " row += f\" & ${region_maes.mean():.4f}\" if not bold else f\" & $\\\\textbf{{{region_maes.mean():.4f}}}\"\n", + " row += f\" & ${region_maes.mean():.3f}\" if not bold else f\" & $\\\\textbf{{{region_maes.mean():.3f}}}\"\n", " if linreg_pval <= 0.01 or other_pval <= 0.01:\n", " row += \"^{\"\n", " if linreg_pval <= 0.01:\n", @@ -619,10 +493,10 @@ " \"\"\"\n", " # Linreg\n", " for region in constants.COUNTRY_DICT.keys():\n", - " region_results = linreg_results[linreg_results[\"region\"] == region]\n", - " row = f\"LinReg ({region if region != 'ALL' else 'Global'}) & {region_results.iloc[0]['time']:.4f}\"\n", + " region_results = linreg_results[linreg_results[\"train\"] == region]\n", + " row = f\"LinReg ({region if region != 'ALL' else 'Global'}) & {region_results.iloc[0]['time']:.3f}\"\n", " for eval_region in constants.COUNTRY_DICT.keys():\n", - " row += f\" & {region_results[region_results['eval'] == eval_region].iloc[0]['mae']:.4f}\"\n", + " row += f\" & {region_results[eval_region].iloc[0]:.3f}\"\n", " row += \"\\\\\\\\\"\n", " print(row)\n", " print(\"\\\\hline\")\n", @@ -635,27 +509,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "LinReg (EU) & 0.0847 & 0.0333 & 0.1712 & 0.1689 & 0.2061\\\\\n", - "LinReg (SA) & 0.5705 & 0.1360 & 0.1534 & 0.0623 & 0.1109\\\\\n", - "LinReg (US) & 0.3427 & 0.1399 & 0.1456 & 0.0351 & 0.0726\\\\\n", - "LinReg (Global) & 6.8722 & 0.1376 & 0.1503 & 0.0361 & 0.0742\\\\\n", + "LinReg (EU) & 0.047 & 0.033 & 0.172 & 0.169 & 0.206\\\\\n", + "LinReg (SA) & 0.457 & 0.137 & 0.153 & 0.061 & 0.110\\\\\n", + "LinReg (US) & 0.331 & 0.139 & 0.146 & 0.035 & 0.073\\\\\n", + "LinReg (Global) & 4.644 & 0.139 & 0.150 & 0.035 & 0.074\\\\\n", "\\hline\n", - "RF (EU) & 16.4930 & $0.0517$ & $0.2078^{\\dag}$ & $0.1532^{*\\dag}$ & $0.2196^{\\dag}$\\\\\n", - "RF (SA) & 206.4513 & $0.1333^{\\dag}$ & $\\textbf{0.0634}^{*\\dag}$ & $0.0757^{\\dag}$ & $0.1268^{\\dag}$\\\\\n", - "RF (US) & 101.7903 & $0.1424$ & $0.1844^{\\dag}$ & $\\textbf{0.0194}^{*\\dag}$ & $0.0922^{\\dag}$\\\\\n", - "RF (Global) & 422.2839 & $0.0348^{*\\dag}$ & $0.0669^{*\\dag}$ & $0.0202^{*\\dag}$ & $\\textbf{0.0398}^{*\\dag}$\\\\\n", + "RF (EU) & 17.697 & $0.064$ & $0.211^{\\dag}$ & $0.161^{\\dag}$ & $0.218^{\\dag}$\\\\\n", + "RF (SA) & 209.688 & $0.133^{*\\dag}$ & $\\textbf{0.071}^{*\\dag}$ & $0.074^{\\dag}$ & $0.126^{\\dag}$\\\\\n", + "RF (US) & 111.701 & $0.163$ & $0.185^{\\dag}$ & $0.032^{*}$ & $0.094^{\\dag}$\\\\\n", + "RF (Global) & 417.647 & $0.041^{*\\dag}$ & $0.076^{*\\dag}$ & $0.028^{*}$ & $\\textbf{0.045}^{*\\dag}$\\\\\n", "\\hline\n", - "NeuralNet (EU) & 10.6497 & $\\textbf{0.0243}^{*\\dag}$ & $0.2663$ & $0.2817$ & $0.3329$\\\\\n", - "NeuralNet (SA) & 96.4302 & $0.2516$ & $0.0991^{*}$ & $0.5507$ & $0.4120$\\\\\n", - "NeuralNet (US) & 71.9760 & $0.1275^{*\\dag}$ & $0.2322$ & $0.0237^{*}$ & $0.1470$\\\\\n", - "NeuralNet (Global) & 1047.7100 & $0.0455^{*}$ & $0.1086^{*}$ & $0.0249^{*}$ & $0.0477^{*}$\\\\\n", + "NeuralNet (EU) & 10.711 & $\\textbf{0.025}^{*\\dag}$ & $0.277$ & $0.286$ & $0.334$\\\\\n", + "NeuralNet (SA) & 103.696 & $0.248$ & $0.100^{*}$ & $0.562$ & $0.399$\\\\\n", + "NeuralNet (US) & 73.141 & $0.136^{\\dag}$ & $0.225$ & $\\textbf{0.024}^{*\\dag}$ & $0.150$\\\\\n", + "NeuralNet (Global) & 1649.193 & $0.046^{*}$ & $0.110^{*}$ & $0.025^{*\\dag}$ & $0.050^{*}$\\\\\n", "\\hline\n" ] } @@ -681,7 +555,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.11" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/use_cases/eluc/experiments/predictor_significance.py b/use_cases/eluc/experiments/predictor_significance.py index 8a31899..b41e7b8 100644 --- a/use_cases/eluc/experiments/predictor_significance.py +++ b/use_cases/eluc/experiments/predictor_significance.py @@ -24,45 +24,51 @@ def train_and_test(n: int, model_constructor, config: dict, train_df: pd.DataFra (This is currently only used for the random forest) """ countries_df = construct_countries_df() - + print(f"Saving to: {save_path}") save_dir = save_path.parent save_dir.mkdir(parents=True, exist_ok=True) - if not save_path.is_file(): - with open(save_path, "w") as f: - f.write("region,test,mae,time\n") - with open(save_path, "a") as f: - # Iterate over all regions - for train_region in train_regions: - print(train_region) - if train_region != "ALL": - countries = constants.COUNTRY_DICT[train_region] - idx = countries_df[countries_df["abbrevs"].isin(countries)].index.values - train_region_df = train_df[train_df["country"].isin(idx)] - else: - train_region_df = train_df - - # n times for each region - for i in tqdm(range(n)): - model = model_constructor(**config) - s = time.time() - _ = model.fit(train_region_df, train_region_df["ELUC"]) - e = time.time() - # Evaluate on each region - for test_region in constants.COUNTRY_DICT.keys(): - if test_region != "ALL": - countries = constants.COUNTRY_DICT[test_region] - idx = countries_df[countries_df["abbrevs"].isin(countries)].index.values - test_region_df = test_df[test_df["country"].isin(idx)] - else: - test_region_df = test_df - if override_start_year: - test_region_df = test_region_df.loc[override_start_year:] - - mae = mean_absolute_error(model.predict(test_region_df), test_region_df["ELUC"]) - f.write(f"{train_region},{test_region},{mae},{e - s}\n") + + # Iterate over all regions + results = [] + for train_region in train_regions: + print(f"Training on {train_region}") + if train_region != "ALL": + countries = constants.COUNTRY_DICT[train_region] + idx = countries_df[countries_df["abbrevs"].isin(countries)].index.values + train_region_df = train_df[train_df["country"].isin(idx)] + else: + train_region_df = train_df + if override_start_year: + print(f"Overriding start year to: {override_start_year}") + train_region_df = train_region_df.loc[override_start_year:] + + # n times for each region + for _ in tqdm(range(n)): + result_row = {"train": train_region} + model = model_constructor(**config) + s = time.time() + _ = model.fit(train_region_df, train_region_df["ELUC"]) + e = time.time() + result_row["time"] = e - s + # Evaluate on each region + for test_region, countries in constants.COUNTRY_DICT.items(): + if test_region != "ALL": + idx = countries_df[countries_df["abbrevs"].isin(countries)].index.values + test_region_df = test_df[test_df["country"].isin(idx)] + else: + test_region_df = test_df + + mae = mean_absolute_error(model.predict(test_region_df), test_region_df["ELUC"]) + result_row[test_region] = mae + + results.append(result_row) + + results_df = pd.DataFrame(results) + results_df.to_csv(save_path) if __name__ == "__main__": + print("Loading data...") dataset = ELUCData() nn_config = { @@ -89,13 +95,10 @@ def train_and_test(n: int, model_constructor, config: dict, train_df: pd.DataFra model_constructors = [NeuralNetPredictor, RandomForestPredictor, LinearRegressionPredictor] configs = [nn_config, forest_config, linreg_config] model_names = ["neural_network", "random_forest", "linear_regression"] - #train_regions = constants.COUNTRY_DICT.keys() - train_regions = ["US", "ALL"] - significance_path = Path("experiments/predictor_significance/no_overlap") - for model_constructor, config, model_name in zip(model_constructors[1:2], configs[1:2], model_names[1:2]): - override_start_year = None - if model_name == "random_forest": - override_start_year = 1982 + train_regions = list(constants.COUNTRY_DICT.keys()) + significance_path = Path("experiments/predictor_significance/no_overlap_fixed") + for model_constructor, config, model_name in zip(model_constructors, configs, model_names): + override_start_year = None if model_name != "random_forest" else 1982 print(model_name) train_and_test(30, model_constructor, From 1726c9e9649d6650d1ee57cfca59f03b7abd93c6 Mon Sep 17 00:00:00 2001 From: Daniel Date: Thu, 14 Mar 2024 11:15:46 -0700 Subject: [PATCH 5/7] Changed neural net to allow different devices --- .../eluc/predictors/neural_network/neural_net_predictor.py | 2 +- use_cases/eluc/prescriptors/nsga2/train_prescriptors.py | 6 ++++-- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/use_cases/eluc/predictors/neural_network/neural_net_predictor.py b/use_cases/eluc/predictors/neural_network/neural_net_predictor.py index 996a291..2ba4689 100644 --- a/use_cases/eluc/predictors/neural_network/neural_net_predictor.py +++ b/use_cases/eluc/predictors/neural_network/neural_net_predictor.py @@ -114,7 +114,7 @@ def load(self, path: str): self.__init__(**config) self.model = ELUCNeuralNet(len(self.features), self.hidden_sizes, self.linear_skip, self.dropout) - self.model.load_state_dict(torch.load(load_path / "model.pt")) + self.model.load_state_dict(torch.load(load_path / "model.pt", map_location=self.device)) self.model.to(self.device) self.model.eval() self.scaler = joblib.load(load_path / "scaler.joblib") diff --git a/use_cases/eluc/prescriptors/nsga2/train_prescriptors.py b/use_cases/eluc/prescriptors/nsga2/train_prescriptors.py index 7d647b3..7a9e9db 100644 --- a/use_cases/eluc/prescriptors/nsga2/train_prescriptors.py +++ b/use_cases/eluc/prescriptors/nsga2/train_prescriptors.py @@ -1,3 +1,4 @@ +import argparse from pathlib import Path from data import constants @@ -6,10 +7,11 @@ from predictors.neural_network.neural_net_predictor import NeuralNetPredictor if __name__ == "__main__": + print("Loading dataset...") dataset = ELUCData() print("Loading predictor...") - nnp = NeuralNetPredictor() + nnp = NeuralNetPredictor(device="cuda") nnp.load("predictors/neural_network/trained_models/no_overlap_nn") print("Initializing prescription...") candidate_params = {"in_size": len(constants.CAO_MAPPING["context"]), @@ -24,7 +26,7 @@ predictor=nnp, batch_size=4096, candidate_params=candidate_params, - seed_dir=Path("prescriptors/nsga2/seeds/small_sample") + seed_dir=Path("prescriptors/nsga2/seeds/test") ) print("Training prescriptors...") save_path = Path("prescriptors/nsga2/trained_prescriptors/test") From 39a2d3f49c3cb087e100ea9ff3568fd25ce88ada Mon Sep 17 00:00:00 2001 From: Daniel Young Date: Thu, 14 Mar 2024 12:48:42 -0700 Subject: [PATCH 6/7] Fixed prescriptor experiments to work with new prescriptor API after updating with new trained TorchPrescriptors --- .../experiments/prescriptor_experiments.ipynb | 3807 ++++++++++++++--- 1 file changed, 3290 insertions(+), 517 deletions(-) diff --git a/use_cases/eluc/experiments/prescriptor_experiments.ipynb b/use_cases/eluc/experiments/prescriptor_experiments.ipynb index 4d3df2a..0f25097 100644 --- a/use_cases/eluc/experiments/prescriptor_experiments.ipynb +++ b/use_cases/eluc/experiments/prescriptor_experiments.ipynb @@ -39,16 +39,7 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Using the latest cached version of the dataset since projectresilience/ELUC-committed couldn't be found on the Hugging Face Hub\n", - "Found the latest cached dataset configuration 'default' at /Users/964840/.cache/huggingface/datasets/projectresilience___ELUC-committed/default/0.0.0/c5965fb027a710b57d30c88f25c2ff627c05c011 (last modified on Fri Feb 16 15:28:56 2024).\n" - ] - } - ], + "outputs": [], "source": [ "dataset = ELUCData()" ] @@ -72,19 +63,19 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "TOTAL_GENS = 100\n", "\n", "esp_results_dir = Path(\"prescriptors/esp/trained_prescriptors/no-overlap/seeded\")\n", - "torch_results_dir = Path(\"prescriptors/nsga2/trained_prescriptors/small_sample\")" + "torch_results_dir = Path(\"prescriptors/nsga2/trained_prescriptors/full\")" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +90,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -116,7 +107,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -133,7 +124,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -241,452 +232,3217 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "gens_to_plot = [1, 3, 10, 25, 100]\n", + "plot_gens(esp_results_dir, gens_to_plot, save_path=None)\n", + "plot_gens(torch_results_dir, gens_to_plot, save_path=None)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def get_gen_df(gen: int, results_dir: Path):\n", + " gen_filename = results_dir / f\"{gen}.csv\"\n", + " gen_df = pd.read_csv(gen_filename)\n", + " # Sort by first objective, maximize: lowest to highest, minimize: highest to lowest\n", + " gen_df = gen_df.sort_values(by='change', ascending=True)\n", + " gen_df[\"Name\"] = f\"Gen {gen}\"\n", + " return gen_df\n", + "\n", + "def get_all_gens_df(gens: list, results_dir: Path):\n", + " dfs = []\n", + " for gen in gens:\n", + " dfs.append(get_gen_df(gen, results_dir))\n", + " merged_df = pd.concat(dfs, ignore_index=True)\n", + " return merged_df" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_all_gens(gens: list, results_dir: Path, save_path=None):\n", + " all_gens_df = get_all_gens_df(gens, results_dir)\n", + " fig, ax = plt.subplots()\n", + "\n", + " all_gens_df.plot.scatter(x='change',\n", + " y='ELUC',\n", + " ax=ax,\n", + " label=\"All prescriptors evaluated\")\n", + " # Plot last gen's pareto front in red\n", + " \n", + " #get_pareto_df(dir, gens[-1]).plot.scatter(x='change', y='ELUC', c='red', ax=ax, label=\"Gen 100 Pareto Front\")\n", + " overall_pareto = get_overall_pareto_df(gens[-1], results_dir)\n", + " overall_pareto.plot.scatter(x='change', y='ELUC', c='red', ax=ax, label=\"Final Pareto Front\")\n", + " plt.grid()\n", + " #plt.title(\"All Generations All Prescriptor Performance\")\n", + " plt.legend(loc=\"upper left\")\n", + " if save_path:\n", + " plt.savefig(save_path, format=\"png\", dpi=300) \n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "all_gens = [a + 1 for a in range(100)]\n", + "plot_all_gens(all_gens, esp_results_dir, save_path=None)\n", + "plot_all_gens(all_gens, torch_results_dir, save_path=None)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "esp_all_pareto_df = get_overall_pareto_df(100, esp_results_dir)\n", + "torch_all_pareto_df = get_overall_pareto_df(100, torch_results_dir)\n", + "# TODO: This is temporary until we rerun the training with new id format\n", + "torch_all_pareto_df[\"id\"] = torch_all_pareto_df[\"gen\"].astype(str) + \"_\" + torch_all_pareto_df[\"id\"].astype(str)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Comparison with Heuristic" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "nnp = NeuralNetPredictor()\n", + "nnp.load(\"predictors/neural_network/trained_models/no_overlap_nn\")\n", + "presc_config = None\n", + "with open(\"prescriptors/esp/unileaf_configs/config-loctime-crop-nosoft.json\") as f:\n", + " presc_config = json.load(f)\n", + "unileaf_prescriptor = UnileafPrescriptor(presc_config,\n", + " dataset.train_df.iloc[:1],\n", + " dataset.encoder,\n", + " [nnp])\n", + "\n", + "candidate_params = {\"in_size\": len(constants.CAO_MAPPING[\"context\"]), \"hidden_size\": 16, \"out_size\": len(constants.RECO_COLS)}\n", + "torch_prescriptor = TorchPrescriptor(100, \n", + " 100, \n", + " 0.2, \n", + " dataset.train_df.iloc[:1], \n", + " dataset.encoder, \n", + " nnp, \n", + " 4096, \n", + " candidate_params, \n", + " seed_dir=\"prescriptors/nsga2/seeds/test\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "even_heuristic = EvenHeuristic(\"secdf\", nnp)\n", + "\n", + "linreg = LinearRegression()\n", + "linreg.fit(dataset.train_df[constants.DIFF_LAND_USE_COLS], dataset.train_df[\"ELUC\"])\n", + "coefs = linreg.coef_\n", + "coef_dict = dict(zip(constants.LAND_USE_COLS, coefs))\n", + "reco_coefs = []\n", + "for col in constants.RECO_COLS:\n", + " reco_coefs.append(coef_dict[col])\n", + "\n", + "perfect_heuristic = PerfectHeuristic(reco_coefs, nnp)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "test_df = dataset.test_df.sample(frac=0.01, random_state=100)\n", + "encoded_test_df = dataset.encoder.encode_as_df(test_df)\n", + "\n", + "context_df = test_df[constants.CAO_MAPPING[\"context\"]]\n", + "encoded_context_df = encoded_test_df[constants.CAO_MAPPING[\"context\"]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Trained Prescriptors" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "def evaluate_prescriptor(context_df: pd.DataFrame, prescriptor: Prescriptor, **kwargs):\n", + " context_actions_df = prescriptor.prescribe_land_use(context_df, **kwargs)\n", + " eluc_df, change_df = prescriptor.predict_metrics(context_actions_df)\n", + " return eluc_df[\"ELUC\"].mean(), change_df[\"change\"].mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, "metadata": {}, "outputs": [ { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEGCAYAAABLgMOSAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAABy3klEQVR4nO2dd3hUxd6A39nNbnoPkBAgCb1LR0ogUQQFEVSwBRRE0YuFq169Kp9e9IoNy1UREXtBsVIUkB6kCEjvvXeSkN535/vj7CabZDd1k2zIvM9znj07Z86U7GZ/Z+bXhJQShUKhUCgqiq62B6BQKBSKuokSIAqFQqGoFEqAKBQKhaJSKAGiUCgUikqhBIhCoVAoKoVbbQ+gJgkJCZGRkZFl1svIyMDb27v6B1QDqLm4Jmouromai322bt2aIKVsULy8XgmQyMhItmzZUma9+Ph4YmJiqn9ANYCai2ui5uKaqLnYRwhx0l652sJSKBQKRaVQAkShUCgUlUIJEIVCoVBUCiVAFAqFQlEplABRKBQKRaVwWQEihLhRCHFQCHFECPGsnevuQogfLNc3CSEiq2McS24bRapvQ6TQkerbkCW3jaqObhQKhaLO4ZICRAihBz4EbgLaA3cLIdoXqzYBuCKlbAm8C7zh7HEsuW0Ug377Hb/0ywgkfumXGfTb70qIKBQKBa7rB9ILOCKlPAYghJgLjAD22dQZAUy1nP8MzBBCCOnE+PT9lv+JIT+nSJkhP4d+y//k+zXH8PAx4m7UY9TrcDfoMOp1GN10uLvpLa/aYbQcp7ZdZtPCY6Qn5eAT5E6fES1o3TvUWcNVKBSKGkW4Yj4QIcQo4EYp5QOW92OB3lLKR23q7LHUOWN5f9RSJ6FYWxOBiQCNGjXqPnfu3DL7T09Px8fHh4Gx1yEo+feRwIVGHUgMiuR8cBSngyM5HhLJJS9fMoQkQyfJEJJ0HQzYv4rH1n1FWGoC6T4N2NhrAodbDQIgD8l6/zzO+Jhx0wkMOjDowE1HsfcCgx4MovDcTQcGSx279S3nudlZ+Pt4WeqDQS8KznVCVOrzqS2sn8vVgJqLa6LmYp/Y2NitUsoexctddQXiNKSUs4HZAD169JDl8cy0enCm+oTgl365xPU8Nw9MMpWWx1bRcX9WQXmGdxCJgVEkBUaSFBSFV8Zlum+fi8GkrWL80i8R++c7ABxuNQgDgn7ZHhzu7EdOvhnfizk0OZ2Le54kyw32hgiOeUFuvpmcfBO5+WZyTSbyTBUR+gLIsnvFTScKVkcFKyV94Qqq+CrK3U1vs8rS2dSxU79gVaa3U9/yqtcXrNx0urKFmfISdk3UXFyTmpiLqwqQs0BTm/dNLGX26pwRQrgB/kCiMwex/oYBDPrt9yLbWHlu7swd0peFvTLpfLY5jS7oCU5OJzw3nwi9O42uJNP0yGJElv0fbUN+Dtdu/qxgFWLIMfNIRCh5OSY2bj1Kfp4mHLzyoU+S4Pmb2pbY5jKbJbkmMzm2giVfe68JGTM5eZqw2bZjN63atiu4VlCniFCy1i8st9ZLy84n0VrHTl/5ZuesYN10wr5QstkezEjN5tuTW2wEmq5YHfvCyr2UNotvOZZXmCkUCtcVIH8DrYQQUWiC4i7gnmJ1FgL3AX8Bo4BVztR/ANz0688suW0U/Zb/iW96Amk+Iay/YQB3/jQH9n/H7B0fkZWdw82ndORf8GZzeiD54UF49upEx4iWRL/0KvZ+inxtVjVCB6u/PWC3//xcM38tOFpCgOh0Ag+dHg+DHjCUOgfdhf3EdAmv6NTLjcksC4WKyVRMEDkWVjkmO9eKC0FLeY7lyMyXnEvO0srt9OEsYWbQC4uQcbTi0mF0K9R9uZe2KrMjrNzddOxPNOFzIqnU+u5uOkQd22ZU1C9cUoBIKfOFEI8CSwE98LmUcq8Q4mVgi5RyIfAZ8I0Q4giQhCZknM5Nv/5ccO6HZhYGcG/H8YxsfTuf7/6cb92/5rcWqdx55TyDz8B5Uzt2HdvPNV6e+GeWXImk+WhBLd2MOmLi2hDS1Je5L2+22396Ug6XT6cREu6D0AkObbrAXwuOuowiXq8TeBr1eBrLFmZVRVuSRzu8XkSYWVdRdlZXxYVVjslMTp59oWRvlZaTbyYlK89Sx2Rn5WfGVB5h9vdfZVaxCh77K66ythDL2HIsIQD1Jfuyaa+2hdn87WeZvvQg55KzaBzgydND2jCya/U9HCnKxiUFCICUcjGwuFjZizbn2cDomh6XLX5GP/7Z/Z/c3fZuZu6cyXeH5zM/SM+E9OOM8z9H1pBQTL+fRp+XX3CPBAx52XQ8tYyw//wTU+5+fpn2NWbTCHR6P7v9/Djtbzx9DfiFeHL5VBpmiw4kPSmH1XO01Yuy5qpZYVYW+aZCoWW7irIKpc1bttG+U2e7ws22ru12ZEnhpr0mZ+WVKgCdtDArWBUVFzI5WVmE7N/gUFi5FxNERVZxjrYcbfRjRjcdqw5c5JVF+8nOMwNwNjmL537dDaCESC3isgKkLtHIuxEv9X2Jse3G8t7293jvdDzft27HpAgDI8V55JJ8yNLU2QLwzEml77LprMtdw46GjTCb8tEZ1mLwHowQhT98bkYdfW5tgdHTjdP7kzi8+SLFN+kcbXMpahc3vQ43vQ4vo/3rKcf0RLcqkV6hWrAKM0d6rhJCqZiwyrEjlGyF2/lLWXga9OTkm8jMzC/ars3qLiffXOL7WxWy8kxMX3pQCZBaRAkQJ9IysCUfXPcBWy9u5d2t7zL18k6+vnsgc1etwDPLVKSuwWSm+187yOzUlv67D+KXuYg0r0/Y0GsCR9vcjE+QR5HtqbbXhnFo00W7/aYn5dgtVyigbGFWVbStxd5l1pNSkl9km9G6yjKRXYbu7FnLaqM455LtG6soagYlQKqB7o26881N37Dq1Cr+t+1/uCeb7Nbzzczmxk070Fve+2WmMST+f2Rt+BCvz7+A3v2K1PcJcrcrLHyC3J09BYXC6QghMOgFBr0O7wp+ZT9YdYSzdoRF4wBPJ41OURlcMpTJ1YAQgusjrmfeiHlkBTrej9cXey8Ar9w8mDgR5swpcq3PiBa4GYt+ZG5GHX1GtHDSqBUK1+TpIW3wNBT9b/E06Hl6SJtaGpEClACpdtx0bng//RCymAzJNZRh0ZKZCf98CLZ/C2kXAGjt+SexQV/go7sMSAwGM7FxJf1EFIqrjZFdw3nttk6EW1Yc7m46Xrutk9J/1DJqC6smeO4DzR9k+sfIK3mkBhl4fXQor358utTbZEIGYsEj2hu/JpB+gdbk07rhfH5NnIZJGGntmQTcUd0zUChqnZFdwxnZNZzHvt/OjtNXlPBwAdQKpKZ47gNIykVIiX9iLpOmryfTv/T92xxPD3LHrYTr/wMZl8FcaA4cbtzD5dwocv94tbpHrlC4FFEh3py9ojmUKmoXJUBqiaa+TfH+8BPMRsf6EbPJxM+ffE9W1wfBlFvkWrhxDxI9564EwofXwtIpcHQ15GVX99AVilolKsQLs4TTSZm1PZR6jxIgtUlcHLrPv7AT71fDMy+fSyeO8uPUZ0n3jChyrZHxIDryOGfqDr6hsHk2fDMS3oyCOXfAptmQeLTap6BQ1DRRIVqE2WOXM2p5JAqlA6lt4uIQU6bAyZMlLiU18Kb7IxPYPusr5qa1Y3ToFfxFCgAGkYuv/hI7029i+waBT+C/6HNtFq0Ny+HICji8FIDeHqGQMRxaDoLI/uB+dYSqVtRfooK9ATieoARIbaNWIK7AtGng5VWkyGR0Y8boxkw6/DwXbw4jK9fMl6e7c2tQczpHNmW810hSzGGYzZo1V/qVXFavNHAo+El4fBs8vh2GvkWGd1PYMQe+v1NbnXx1C6x/Hy7uw6luwQpFDeHvZSDY26gEiAugViCuQFyc9jplCpw6BXo9+oAgnnxtPQGH5/Dtvm/x6i4ZtLkBPTaHcqXnJdqcGQ6yqPwvEtYkqDn0as6ezFbE9O8DpzZqK5MjK2H5C9rh2xhaXq+tTprHgGdAjU9doagMUSHeHFMCpNZRKxBXIS4OTpwAsxkWLYJLl/B9/2Mmd5vM77f+TlagjiXXXiDPzcyQzY3wyQ2024zdsCZu7tB8IAz+L0zaAE/sg1tmQNNesH8h/HQfvNkcPhsCa6bD2W3aOBQKFyUqxFutQFwAJUBckcGD4fbb4aWXoEkTGvmGMX/yDqJ3JrCkz0Vy9WakKdXureUKa+IfDt3Gwh1fwdPH4P5lEP2UZum1ehp8EgtvtYRfHoSdP4CdrIwKRW0S1cCby2k5pGXn1fZQ6jVqC8tVGTAAfvkFzmqJGBsn5vHa7DP8EJvB4aah5GetKxG9F/LpM6J9xfrRu0Gz3tpx3RTISNDMgY+s0I7dP2r1wrpoW10tB0GTntp9CkUt0TxEU6SfSMikUxP/Wh5N/UX9Crgq77xTokgH3Ln6Cot7X+BghBt5GeDmGY3Q+SKEID97D617D65av94h0Hm0dpjNcGFXoe5k3buw9i1w99e2xFoO0nQo/k2q1qdCUUGsprzHEzOUAKlFlABxVU6dslusA2K37yV69yH8MheR6vUR6zq14VinF9G7d2LGQysRIoP2fX2Ivfe6IvdWOJuhTgeNu2jHgH9BdgocW1O4Otm/UKvXoF2hMr5ZHzB4OOVPoFA4IiLYCyHguPIFqVWUAHFVmjWz6xsC4JWbj8jVwpr4Z2YxeMseVnlt4khr6+rDh73r84BViGaamuvQpgusnnOA/FxNOV6pbIYe/tD+Fu2QEi4fLBQmm2fDXzPA4AWR0YWrk2AVKVjhfDwMehr7e3I8Ib22h1KvUQLEVZk2DcaOteurUTyOr8GUzw3x0xFCx+FWg7Q6wsC+Dfn4nXIj/uwBDv99sUB4WKlSNkMhoGFb7ej7KORmwIn1hQLF4shIYFSh7kQ5MiqciLLEqn1cToAIIaYDw4Fc4CgwXkqZbKfeCSANMAH5UsoeNTjM6icuDtavh1mzyuXwp5NmYv/U9CZWISKlnpxUOLbjMrnZ9gPPOS2bodEbWg/WDoCkY5re5MhK2PEd/P0J6I3aFpdVoDRspwkihaISRIV4M3/HWaSUCPU9qhVc0Yx3OdBRStkZOAQ8V0rdWClll6tOeFiZORO++QYiIrQf2ogICA52WN2Qn8O1mz8rLJBppJx8h/zMz3H3sn9PtWUzDGoOvR6Ee+bCv4/DvQuh98OaldfyF+CjPvBOe1jwKOydD1nJ1TMOxVVLVIg3adn5JGbkll1ZUS243ApESrnM5u1GYFRtjcUliIsr9FQHLUvhxIlawik7+Fp8NqTMIy9zLQBpCZcxeC7D4D0Yc7GFiIeXGzlZ+bh7VuNXwerIaHVmTDkLR1cVKuK3fwNCr5kHW3UnYV00Jb5C4YCoBoUxsUJ8VFrn2kBIF46HJIT4DfhBSvmtnWvHgSuABD6WUs520MZEYCJAo0aNus+dO7fMftPT0/Hxcd29+oYrVtD2tdfQ2fEWz3T35bOxX5GftQ5z3sEi14y+XXD3u468THDzAq8GkHoKjD7QLFrg7lfz2wDCbMI37RBBSdsIStqOb9oRBJJcgx9XAruSFNSNpKAu5BkDXP5zqQhqLlXnUqaZZ/7M4v6ORgY0cZwWoSKoz8U+sbGxW+3t9NSKABFCrADsaW6nSCkXWOpMAXoAt0k7gxRChEspzwohGqJtez0mpfyztH579Oght2zZUub44uPjiYmJKXsitcmcOTB+POQV9cSVRiOLurbnYIT9bG1P/fB7kfdnD17hj0/2YM43c8OEDkR2Cqm2IZcLW0fGoyu1RFoAYV04aWhFxPUTrgpHxjrxHSsntTWXfJOZdi/+wYT+zXn2prZOaVN9LvYRQtgVILXyXyilHFTadSHEOOBm4Hp7wsPSxlnL6yUhxDygF1CqALmqiIuDyZMhMbFIscjNpf+eA3YFSJZnyT9leJtARj/XgyWzdrNo5i56D29O95siak8pWYojY7NTv8AXPylHRgUAbnodzYK8lClvLeJyj3FCiBuBZ4CBUkq7G/1CCG9AJ6VMs5wPBl6uwWG6BklJdov9MrLJ15lxMxfqECSSXPK546fbiGzUkpYBhUd4YDi3Pd2d1d8cYNPCYyScTuO6+9ph9Kjlr0cxR8Z1KxYR3dikHBkVBUSF+HAiQWUmrC1cToAAMwB3YLnlKXijlPJhIURj4FMp5VCgETDPct0N+E5K+UdtDbjWcOBseDnEg/WdEul+MBDvbD0ZHiZONsqg3Sk/uqyWbOi7gyXHlxTUd9e709y/OS1atSDC0I2jf8Gl8ykMn9SVwIbeNTmjUjG5eUP7GOXIqCigeQNv/jx8GbNZotMpU96axuUEiJSypYPyc8BQy/kx4JqaHJdLMm1aSYssLy/OPf8PzjdYw8/hZwuKPfQeDLnuHi7MWcHtW5sz9N+fclGfzNHkoxxJPsLR5KP8ffFvfpe/06RtGwYduo8vXl7Nwe6rCGnlSYuAFrQMaEmLgBaEeYehE7VsIaUcGRVAZLA3uflmzqVk0STQga26otpwOQGiqADFE1FJCU89RdcnXmbqsUW8t+09zmecJ8w7jMndJjOs+TDOREQz742XWPjKS4x+YRqdW3Uu0mRabhpHk49y8MRxLs4z0GnTUPYkrmJhyLsFLvCebp608G9RRKi0DGhJqHdo7elOlCNjvSQqpNCUVwmQmkcJkLqO1U8kObmIk+Gw5sMY1nxYCUuMJu06MvqFV/nl1ReZ+59nGP1/rxDcpFnBdV+jL10adqFLwy7kds5n1Vf7EdsHEZs/gtSkTHJTzZi9cznVbgvrMlay4OiCgnu9Dd4FgsVWuDTyalTzgsWSkZFeD0J+jsrIeJXS3MYXJLpVg1oeTf1DCZCrhYAA6NULli+Hl0u3Jwht0Yo7//MaP097gR+mPsvtz79Mo+Yldw6NHm4MmdiRpZ/s4eg2a1IpgS7DnZa7onkw7kEaXuNRsAV2JPkIR1OOsubMGuYdmVfQjq/Bt4RQaRnQkhDPELuCZZFl9XQh4wKh3qEFq6dKoxwZr1oa+rrjZdRzTEXlrRWUALmaCA2F+fO1H76gIAAGJiVpyvZp04p4tIc0i+TOl97gp/9O4ceXn+e2Z6cS3rZkMiohBBdPlMx+aA3EeF/vfvQI7UGP0KIm4knZSUX0K0eSj7Dy1Ep+OfxLQR0/o1+BQLEKleMpx3l7y9tkm7IBOJ9xnqkbpgLgjZMU+taMjN3Ggikfzm4t1J2sngarXwGvYGhhWZ20uA581NOtKyKEUEEVaxElQK4W5syBJRbLKikL/EMEaJZaEydq12yESGBoY+566U1+fuX/+PnVFxj5rxeI6NylRNOOAi6WFogxyCOIoNAgeob2LCiTUpKYnVh0xZJ8lD9O/EFabprDtrJN2by37T2eD3neYZ1KU1pGxqMrVUbGOkBUiDe7zqTU9jDqJeq/4GphyhTIKSWybmamVsc2rhbgF9KAO6e+zs/TXmDeG1O5+Z/P0rLntUXq+AS52xUWQqflGSlvOHghBCGeIYR4hnBtWGEfUkouZ13mSPIRHlr+kN17L2RcgJpwklcZGesczUO8Wbz7PDn5Jtzd9LU9nHqF2uS9WnCQwbAIJ0+Cm5tmeRQZqa1aAO+AQO74z2s0iGzOwndeZf/6NUVu6zOiBW7Gkl8VaYbVcw5waNOFKg1dCEFDr4b0bdyXMO8wu3VCvSuRs6SqWB0ZB/wL7l+iRRW+4xvoMBLOboPfHod3O8CH18LSKdrKJS+75sdZz4lq4I1Zwukk5VBY0ygBcrXQrFnZdQBMlnC81m0tixDx9PFl9P+9QpO2HVj8wVvsWrm04JbWvUOJjWuLPdcPqy7EWUzuNhkPfUlP8omdJzqtj0pjzch4y/vwxB6YtAkGTwPfUM2R8ZuR8GYUzLkDNs2GROf9XRSOKciPrjzSaxwlQK4Wpk0DrwrawVu3tSwYPb249bmpRF3TjeWzP2DrovkF11r3DkWWDP4LODEpFZr58dS+UwnzDkMgCPEIQSDYfmm70/pwClZHxr6Pwr3z4d8n4J6foOtYSDwCS56GD7rBe11g0b/g4B+Qo2I2VQdRwVZTXvX3rWmUDuRqobhTocUKSyYmlkiBW4RiW18Gozsjnv4/Fr0/nfivPyU3K4trb78LIYRDXYizk1JZfVisfLjjQ2btnEWDBg2IIcapfTmNCjoyeqf7a8YOypGxyvh7GQj2NipLrFpACZCrieLJp4Cc0FA8Ll50fI+drS+9m4GbJ/+bZR+/z4af5nD+yEESTp8kIzUYo/dgbL82bkYdfUZUb7ypiZ0n8ueZP5mbOJcxWWMI8azlkPPloQxHxp4AB19XjoxOIjLEW/mC1AJqC+sq59gDD5S+tZWaqimLbZTqADq9niEPT6ZZpy4c376FtITLmHMPkJu+FGnW/lE9fAzExrUttxVWZTHoDLzW/zVyzDm8tOElXDkJml2sjoyD/wuTNsCT+znQ5jFo2ktzZPzpPnizOXw2BNZM1/xS7CQLUzhG+YLUDkqAXOVcGjQIZs/W8qkD6C1mjgEB2uuVK9pWysmTMGYMhIQUCBKh03Hl/Nki7ZnzDpKbrjkDxsS1qXbhYaV5QHNuCbyF+DPxRbzc6yR+jbkQNgju+AqePgb3L4Pop8CUqzkyfnIdvNUSfnkAdv4A6ZfLbrOeExXizaW0HNJz8mt7KPUKtYVVH7CztUVkpBY/qziJiUWcDtMSE0rWsWjTj27dQsOIXvgG1cyW0kDfgZxxP8Mbm9+gV2gvmvheBf4XZToy/qTVU46MpdLcElTxREIGHcP9a3k09Qe1AqmvlOY3YmOd5RtsTzhoAmTvmtXMnjSeuf95hm1LFpKelGinrvPQCR2v9HsFndAxZd0UTGZTtfZXK1gdGW/7GJ46BBPXwHUvaHlO1r0LX9yobXf9MBa2fgUpZ2p7xC5BlCWo4jG1jVWjqMeY+oqDZFQFWJwOHzSZkEKws3lTVnXvBIDeoH1tou8eR37Wbg5uXMfqL2ez+qtPCG/TjtbXRtO6d198goIdt19JwnzCeLbXs/zf+v/jm33fMK7jOKf34TIUy8hIdgocW1OojC+RkfF6aNa3XmZkjLSa8ipFeo2iBEh9xV4yquKYTAhASEmXo9qK5e8h1xHZdSyHt8CmhRfxCWpKn1H/R3CTPA5tXMehjetZ/eXHrP5qNuFt2tP62v5OFya3tLiF1adX8+7Wd/l639ckZCU4J2qvq2N1ZCwtI6ObJ0RFF2531ZOMjB4GPeEBnpxIVAKkJlECpL5i1YmMGVOu6gLoevQUoQ17smCnDus2VnpSDqvnHCA2ri19br+bPrffTeLZ05ow+WtdEWHSpk9/WvXux+k9O1k792vSEhPwDQ4h+q57aRcdW+6hCyHo07gPK0+t5HKWpmC2jdp7VQsRK2VmZFym1atHGRmjQrzVFlYNowRIfSYuTtN1lLaVVYzQqY9wn7sfa/s9wuFWg4DCcCZWi6zg8KaFwuSMRZhsXMeqLz5m1RcfI4QoMMVNS7jMstkzACokRD7b/VmJMmvU3nohQIpTzzMyzt9+lu2nrpCRa6Lf6yt5ekhbRnYNr+1hXfW4nBJdCDFVCHFWCLHDcgx1UO9GIcRBIcQRIcSzNT3Oq4YKhkARgGdOKrF/vkOrwysKytOTctjwyxHOHLyCKb/QhyG4SVP6jLqb+976kHFvf4S7l1cJP4783BzWzv26QsO+kGE/gKOj8npHkMWJ8Z65WhDIexdC74c1K6/lL8BHfeCd9rDgUdg7D7Ku1PaIK8387Wd57tfdZORqRhVnk7N57tfdzN9+tow7FVXFVVcg70op33J0UQihBz4EbgDOAH8LIRZKKffV1ACvGoqHQGnWDFq2hJUrS73NkJ/DtZs/K1iF6N107Fx1mu3LT2Hw0NO0bRDNOgQR0TEYn0BNqRvcpCk5WVl220tLuMz+tavLvQoJ9Q7lfMb5EuU6oWPO/jnc2vJWvAwqRzZQMiNj6jnL6sQ2I6OuWEbGrnUmI+P0pQfJyitqkZeVZ2L60oNqFVLNuKoAKYtewBEp5TEAIcRcYASgBEhlsOcnMmkSfPRRqbf5Whzc3Iw6YuPaEnlNCGcOXOHk3kRO7Unk2A7tenC4N806BBPRIRifoAakJ14CQGdog5tnNELnizSnsfwzLQJweYTI5G6TmbphakHmQtA81ht7N+b1za/z0c6PuLvt3dzd9m6CPILK/aeoF/g1LiUj46uaM6NXsJaJseUNLp+R8Vyy/YcSR+UK5yFcLSyEEGIqMA5IBbYAT0kprxSrMwq4UUr5gOX9WKC3lPJRO+1NBCYCNGrUqPvcuXPLHEN6ejo+PleHsrEqc2m4YgVt3noLvYNEVZnuvnw7aT4NO0NAZNGnVSklOamQfg7Sz0syLgMShM5Efs5xpCkTvXs7hDDY3JOHNK2l05hB5ZrL3+l/81vyb1wxXSFQH8jwgOH09OnJsexjrExdya6sXRiEgWu9ryXWL5YGBtf5EXTV75ghN4XAKzsIStpGUNJ2jHlapr80nxYkBXUjKagbqX5tkLrCxE21PZen4jNJzC75OxbsIXg7pmKr0NqeizNx5lxiY2O3Sil7FC+vFQEihFgB2IuBMQXYCCQAEvgvECalvL/Y/eUWILb06NFDbtmypczxxcfHExMTU46ZuD5VnsucOTB5ckGKXLtERJTIuV6c3Kz8gtXJ0W3nyHFgPWw2pfLYJyPtXqvoXI6lHOPrvV+z8OhCTNLEDRE3ML7DeDqEdCh3G9VFnfiOFc/IeHoTSJMlI+OAAmV8/PYjtToXqw7EdhvL3U3HG7d3rvAWVp34XMqJM+cihLArQGplC0tKaf8RsxhCiE+A3+1cOgs0tXnfxFKmcDbW7a2QEMdCxEHOdVuMnm4079qA5l0bEBPXhpn/WAV2As3r9L5OGjg092/O1L5TeaTLI8zZP4cfD/7I0hNL6R3am/Edx9O3cV/EVWKFVC2U6cj4GwA9vZpCzohac2S0ConpSw9yLjkLCVzftqHSf9QALqcDEUKESSmt2tFbgT12qv0NtBJCRKEJjruAe2poiPWTpKTSrzvIuW4PIQTuXsLuKkSITLb/8Rt///Zrpf1EitPAqwH/7P5PHuj0AL8c/oWv933NwysepnVga8Z3HM+QyCEYdIayG6rvOHBkzPn7J7xr2ZFxZNfwAoEx8sP1nFX6jxrB5QQI8KYQogvaFtYJ4CEAIURj4FMp5VApZb4Q4lFgKaAHPpdS7q2l8dYPygp9AuXLy25hwJ3tWfn1PoqHszLl57Dqyx9Aaj8Atn4i9lYsFcHH6MN9He7jnrb3sPj4Yr7Y8wXPrX2O97e9z9j2Y7m91e14GbxYdGwR7217jwsZF+qHh3tlsHFk3JXbkZi+PV3GkfGG9o2YvvQgF1KyCfWvf2FdahKXEyBSyrEOys8BQ23eLwYW19S46j3lCX1S3rzsUOB0+NeCo6Qn5eAT5E5k5xD2xOdj9L2bvPQFSLO2ZWb1E2k9+r4qTcGKQW9gRMsRDG8xnHVn1/H5ns958+83mbVzFt0bdmfD+Q3kmDTDgXrn4V5Zyu3IeK2NI2P7anFkHNJBEyDL919k7LURTm9fUYjLCRCFi2LrL3LypPaPb2uA4eWlCZkK0Lp3aIl8Ilt/m47R+xaMfneRl74Ic/4JQFuJOBud0DGgyQAGNBnAzss7+XLPl6w4taJEvXrt4V5ZSs3I+KJ2+IYVy8gY6JSuWzTwISrEm2V7LygBUs0oAaIoP7b+InPmwCOPQEoKNG0Kr71WLv1HWfgEmEhL/A6jz0gMPiPJz4rHlLMDgCOLf6VVWCNSL12oUiwte1zT4BrejX2Xzl91RlLSMlF5uFeBUh0Zf4Pt3zrVkVEIweD2jfh8/XFSs/Pw81D6reqibriaKlyPuDi4917t/MwZbWVikxK3skTfdS9uhjxy037AnHcMg9d1GH0G0bJXX9Ivnmfui0+z5MN3tBWJlAU6kv1rV1e5b9A83CtSrqgEVkfGIhkZ/wWmPM2R0QkZGW9o34g8kyT+oMrmWJ0oAaKoHHPmwCefaOfWlLgTJ2oe7JGRdvOsl4d20bEMnvgoviEB5GX+jk7sRWfojDAMpf0dD+Lu7eOUWFqOmNxtMh76oopXD70Hk7tNdkr7imJYMzJeNwUmroanj8Btn2oe8MfiYd5ETZh8PABWvgwnN2iCpgy6NgskxMfI8n0Xq38O9Ri1haWoHFOmQHZ20bLMTJg1q1A3Ug7/EHu0i44tsiW1b/051sw5iDjmBm734B7gjTSnkZ+1FnPeQQD7qXcrgVXP8Z/1/yHHrCnSPdyUJU+NYc3I2Hl0SUfGdf+DtW+Du5+2HWZVxvs3gV0/agIm5Qz4N0F//Ytc37Yti3efJzffjNFNPStXB0qAKCqHI5Pd4pENKuAf4oj2/RqTejmLrX+cROg0M1Ch98PgPZi8DDDnHXSQerfy2OpBknOSlSVWbVBOR0Z8wyDjMpjztfcpp+G3xxnb/b/8kNOYjccSGdDadcLYXE0osayoHBUw2a2If4gjDm4uqcQWwoCbZzRuRiPRd91b5T6svLftPXLNuUXKrJZYilrE6sh4y/vwxB6YtAkGT4OspELhYSUvi/b7/oenQc+yfcoAorpQAkRROezlEXFk0y9ElRXs6Un2AzoKnS9R3XpW2QrLFpVrpA5gdWTs+yjk59qtoks9y8DWDVix7xJms2sFjb1aUAJEUTni4mD2bC2QohDa68MPg8GOyaTZrKXOFaJSinUAnyB3u+V6txzO7N1NXk623euVQVli1TH8mzgsD/I2cCE1mxbPL6bf66tUkiknowSIovLExcGJE5qAOHECZs4EP7/S77Eq1isoRPqMaIHQlyxv1y+ErLRUdq9aVqH2SkNZYtUxrn8RDJ5Fy9w8+bvFY/xqERgSOJucpTIVOhklQBTOpaygi1CoWK8ArXuH0rhn4UrEO8AdnZsgNcFI4zYd+Pu3XzHll23eWR6GNR/G1L5TCfMOKyi7ufnNSoHuqnS+A4a/D/5NKYiX1mEk/9zXiuw8c5Gq1kyFCuegrLAUzqU8QRehUor1gEgdI8f1K3i/O/4Mf849xDWxI9j066vsXxtPx9gbKtyuPYY1H8aw5sOQUjL6t9FsvbQVszSjE+qZyyXpfId2SAlfDIVja0hIHgIYS1RVmQqdh/pvUDiXadPs60GKI0SlnQ2tdBwQTmhzPw5uNhHcrC2bF/yMuXh43yoihGBCpwkcTznO6lPO8XZXVCNCQMyzkHaOiT7r7VZpHOBpt1xRcZQAUTiXuDj44gsIDi69ntlc1IO9EkJE6ASxY9qRm52Pb4ObuXL+LEc2/1XJgTvmhogbaOLThM/2fFbCC17hgkQNgGZ9meS2EH9D0QcKT4Oep4e0qaWBXX0oAaJwPnFxkJCgCYjyhOuuhE7ESlBjb7rdGMGFY2b8GnZn07yfnP4j76ZzY3zH8exO2E3sj7F0/qozg38ezKJji5zaj8JJCAEx/8Yz+yJfdzlIgKe2Im7k585rt3VSmQqdiBIgiuqlvA6HVXA27HFjJIGhXgjDAC6dOMXJndsq3ZYjjHptLz0xOxGJLMgTUhUhsujYIgb/PFgJpOogaiAEteSaPa+xXd7BOuPj/DbwvBIeTkYp0RXVS3kSUUHFPNuLoTfoiBnTlnlvbcMz8Ho2zf+JyC7dK92ePWbumFmiLNuUzfS/pxPpF4mbzg2j3ohBZ8CgMxSe67X3xZXvf6f/zY8bfiTbpPmvWAXS9kvb+fPMnyobYlXZ/ZMW0kSaEEATXQLm1U+Dr7umbFc4BSVAFNWLbSKqU6c07/WMjJL1hg4tWVYBGrcMoOOAcPb8Kbl8rhkfPrwKnyB3+oxoUSJpVWVw5IWemJ3IXYvuKvN+N+GGQW/QBI3OyJXsK5gpamKabcrmh4M/FLxX2RCrwMqXwVQ0eoEuP4sLvz7PRlM/tRJxEkqAKKof20RUkZH2BcjiqmcnDmnqA4iCgIvpSTmsnnMAoMpCJNQ7lPMZ50uUB3kE8XLfl8k155JnyiPPnFfkPM+cV+Q815RLnjmPnw79VK5+VTbESpJyxm5xQ5nAc7/uBlBCxAm4nAARQvwAWM0kAoBkKWUXO/VOAGmACciXUvaooSEqqoIjXYcTAi5uWXKiRFl+rpm/FhytsgCZ3G0yUzdMLdhyAs07/ZmezzCw6cAKt7fi6AqumK6Uq66KwVUJ/JtoW1jFOCeDC5wJlQCpOi6nRJdS3iml7GIRGr8Av5ZSPdZSVwmPuoIjXUfjxlVu2lHARUflFcHWO10gCPMOY2rfqZVeGQwPGF4iXIojVAyuSmAnvEmmNPJmvqb/UM6EzsHlBIgVIYQA7gC+r+2xKJyIvSi+oOVWf/HFKmUzdBRwEeCr59dzaFPVnuSHNR/GslHL2HXfLpaNWlalbaWePj1LCKQ729yJu77oHFQMrkpiCW9ymUAAkqQvz+Y9wEJzf0A5EzoL4aqOUUKIAcA7jlYXQojjwBW0OGkfSylnO6g3EZgI0KhRo+5z584ts+/09HR8fHwqO3SXwhXn0nDFCpp/+inuly6R07AhZ269laY//ogxKQlbrxGzXk++tzeGtDRyGjZk35gxpN58s8N2k0+YOfc3SAfO6EIPjXtqIVFKa+PSLsjLBIMXNOxcev3K4uhzWZ68nIUpCwEI1AcyPGA4PX16Or1/Z+KK3zErW08n89TR+5iWdw+fmLTvjlEH4zoa6du4ZMQEV55LRXHmXGJjY7fa+y2uFQEihFgB2FuXT5FSLrDU+Qg4IqV820Eb4VLKs0KIhsBy4DEp5Z+l9dujRw+5ZcuWMscXHx9PTExMmfXqAnVmLk2bwhn7ik8rJnd39J99Vmp2w0ObLvDXgqMOt60MHnquua4pBnc9bkY9Bned5VXP+aMp7FxxGlN+oXWUm1FHbFxbp1hy2eLoczmafJSRC0YyfcB0boy60al9Vheu/h3Le6Ux82Qsz2TcA8B/hrdnfL8ou3VdfS4VwZlzEULYFSC1okSXUg4q7boQwg24DXBozC+lPGt5vSSEmAf0AkoVIAoX5mzZIbb1OTllpsdt3TuU1r1D+fDhVXav52Wb2LL4RLmH5SwlfHkRlMNzX1EhDAFNuKOBjn5DrmPgm6s5mViGT5Ki3LicFZaFQcABKaXdR1IhhDegk1KmWc4HAy/X5AAVTsbJUXx9gtztrkJ8gty5d1pf8vPM5OeYyMsxkZdrIj/HzM9v2F+dOkMJr6hF/BpD6lnCAzwZ2TWcuX+f4rHrWhLs41hnpigfrqpEv4tiynMhRGMhhNVZoBGwTgixE9gMLJJS/lHDY1Q4E0fK9eJIWS4Fe58RLXAzFv16S5lH5pUVHFgXj8Gox9PXiF+IJ8GNfWgU5edQCV+acr66kLimbrJO4hcOqecAeHhgc3LyzXy54UTtjukqwSUFiJRynJRyVrGyc1LKoZbzY1LKayxHBynltNoZqcJpFE+RGxwMxpK5HABtpTJ2LEya5LC51r1DiY1ri7sXSCkxm1LJy1hGZtLfLJs9g/1rS4Zmtyd0dHpBnxEtqjS1CqF2sJyPX2NIuwCmPFo29GVw+0Z8teEEadnOSUBWnylVgAghpgshHrJT/pAQ4vXqG5aiXmKbIjchAT7/XBMo9pASZs3ShIgD09/WvUMx53xDTvK75KZ+ijlPy0SXn5vD2rlfl2jSKnSsKw69mw6dmyCyc4iTJ6qoUfzDAQnpFwGYFNOS1Ox8vt9cdefV+k5ZK5DrAHvmsZ8Aju0pFQpnYBUojkLCSwkffaStSBzkFklLTLB7q6Py1r1Due/Vfjwy6zpue7ob+Tlmti0rh27GybiqeX2dxM/icW7ZxrqmaQCtGnrz+pIDRD27iH6vr1J50itJWQLEXdr5JkspzajFtqKmqEik3mK5RXyD7a8eHJXb0jDCj1Y9GrJzxWkykpUivc7iZ4lyYImPNX/7WU4mZmGWmhPZ2eQsnvt1txIilaAsAZIlhGhVvNBSpmIBKGqGadPKl5jKio2lVvRd9+JmLKoEdzO6E33XveVqqveIFpjNks2/Hy9//1VAmfFWA1YBYlmBTF96kFxT0UjIWXkmnvpxJ+P+yFArkgpQlgB5EVgihBgnhOhkOcYDiyzXFIrqJy4OHn64pF2SI6Fis2JpFx3L4ImP4hvSQLtFp+OGBx+hXXRsubr2b+BJx4Hh7F9/jqRzdqIIK1wfjwAtrIBFgDiKg2WybLaoFUn5KVWASCmXACOBWOBLyxEL3C6lrHr8bYWivMycyf4pUwqttCIi4OGHS5r+enlpKxYb2kXHMvHDL7jpkSeRZjN+DRtVqOseQyMxuOv5a/7Rqs6i3CgzXicihMWUVxMI5YmDZY3YqyidMs14pZR7pJT3SSm7W457pZS7a2JwCoUtlwYNKrTSOnECZs4sNP21YtWB2PETadmrD27u7nZNeEvD08dI1yERnNiVwLkjyVWaQ1moLaxqwq9xwQrk6SFt8DToy7xFRewtm7LMeH8TQiy0ORYIIT4TQoypqQEqFKUSF6etONxt9Bx2rLEAjB6etOxxLYf+Wocpv2I+ANdc3xRvfyMbfjmiLKTqIjYrkJFdw3nttk6EB3giAL2DrVAVsbdsylqBvAW8bXO8A/wO3Kr8QBQuw5QpkFPMSqqYNZaVdtExZGekc3z71gp1YTDq6TW8ORePp3Jsx+WqjLZcqC0sJ1PgTJgPaEJk/bPXcfz1Ybx9xzUlViSeBj1PD2ljryWFDWXpQNbYOeah5emoG6FCFVc/FchyGNGpK55+/uxfF1/hbtr2CSUwzJu/5h3FVMyKR+Hi+DXW4vxnXCpxyboi8XUvFCIeBpcM0uFyVOqvJKWjjAsKRS3gyE/ETrnezY02faI5unUTOZkVs6rS6XX0ubUFKZey2L/uXGVGWiaiIubKivLj30R7TXX8ueWbC1d9VzLzlCVWOShLBxJk52ghhHgJ2FtDY1QoSsdeIEY71lhW2kfHYsrL49Cm9RXuKrJTMGEt/dm86AS52fmVGa2iNijwBbEvEKYvPUhWXknfEGWJVTplrUC2Alssr9bz7wFP4OHqHZpCUU5sAzFaKcUaK7RlawJCwzhQiW0sIQR9b2tJVmouO1acrsKgS0cp6p2MNZxJin0B4sjiSllilU5ZOpAoKWVzy6v1vJeU8hng0xoao0JRNlZrLE8byxkH1lhCCNr1j+HU3t2kJdmPiVUaoc39adG1AduXnyIjxbkhTpQZbzXhGQhuHg5XII4srpQlVulURVPUx2mjUCicwZQpkFXsidGRNVb/GJCSA+srl8Ty2pEtMOWZ2bLoRKXuV9QwBc6E9nUgjnxDRvdoUt0jq9MoUwPF1YMja6yTJ0uEeg8MC8evYSjrvv+Kt+8azuxHxlfIwTCgkRcdohuzd905ki+qFKl1AhtnwuJYLbGCPbQ1YJi/BwGeBn7acoaUTJU3xBFlKdG7OTi6A4YaGqNCUT5Ki9p78iTce2+BENm/djXpiQmYTSaQkrSEyw4TTTmi57Ao3Aw6NtZgiBNFFShlBQKaEHk7xovjrw/jr+eu54vxPbmYms0zv+xUOikHlLUCedvB8RZwoHqHplBUkLLS4prN8JCWH23t3K8xm4paUTlKNOUILz8jXW5oxtHtl7lwLKVSQy6O0oFUI36NIe0cmMvnhdC1WSD/vrEtS/de5CuVAtcuZSnRY0s7amqQCkW5sGeNVZyMDJgzp8KJphzRZVBTPP2MbPhVhThxefwagzkfMsofSWBC/yiua9uQVxcfYPcZ5zwkXE2UtYX1jM356GLXXq1Kx0KI0UKIvUIIsxCiR7FrzwkhjgghDgohhji4P0oIsclS7wchhIME2op6hTWLYWlMnEiXRPs/BuVJNGWL0cONXsMiOX8khc+fXseHD6/iq+fXc2jThQq1UxwVyqQaKHAmLL9zoE4neHv0NQT7GHn0+20qj3oxytrCusvm/Lli16oaymQPcBtQxAxGCNHe0m8HSx8zhRD2Qme+AbwrpWwJXAEmVHE8iqsJXSlf7cxMoncfLJFoCiHoOyquwl25GbWvZ3a69uOSnpTD6jkHKidE1A5W9VEssVR5CfQ28v7dXTlzJYtnf92tVpo2lCVAhINze+8rhJRyv5TSnpvnCGCulDJHSnkcOAL0KtKxFu/hOuBnS9FXaHlLFAoNi67DEcZLlwsTTQmBp68fSMnJ3dsr/AOx6bdjJcryc838tUAp112KYrnRK0LPyCCevKE1i3ad5/vN1edAWtdwK+O6dHBu772zCAc22rw/YymzJRhIllLml1JHUZ+ZOVN7/egj+9ebNaNddGyRzISb5v3IurlfExTehD63313urtKT7DsTOiovD+optxrwCga9sSA3ekX5x8AWbDyWyEu/7aVrswDahfk5eYB1j7IEyDVCiFS01Yan5RzLe4+yGhdCrABC7VyaIqVcUKGRVhIhxERgIkCjRo2Ij48v85709PRy1asL1Ou53HEHDYOCaPPWW+htwr1L4GyXLhwp1pYMaEBQ6/Zs+HEO56+kENSybbm6MXhBnh1XEL0HDsfraC4JeZoS/8CBA/if8S9X/7VNXfqO9TYEkXpkB/uN8XavlzWXUU0ku05Jxn+6jql9PPFwc909x5r4XEoVIFLKstN2lX7/oErcdhZoavO+iaXMlkQgQAjhZlmF2KtjHcNsYDZAjx49ZExMTJkDiI+Ppzz16gL1fi4xMZCUVGQlIoAmy5fTZPRoTeluQ37//vz08vOcjl9G35jrCG3ZuswuGnteYPWcA+TnFg3GZ8qBBvpWdIguuTh2NJczaWfgV2jbti0xLUted0Xq1HfseEs8ZT6NHIy3PHNp0DKBuE83sSwxkLfvuMZlIyjXxOfiip7oC4G7hBDuQogooBWw2baC1Nb3q4FRlqL7gBpZ0SjqIIsXlyzLzIT77isRJ8vNYGDEv6bgFRDA/LdeKZdZb+veocTGtcUnSFPK+wS5M/DuNjRtF0T8nIOs/mY/+XkqA4JL4Ne4QlZY9ujbIoTHr2vFr9vP8vPWym2HXS3UmgARQtwqhDiDFlNrkRBiKYCUci/wI7AP+AN4xJp/RAixWAhhMaXg38CTQogjaDqRz2p6Doo6gqMQJyaT3WCLXv4BjHzmRXKzspj/5n/Jy84us4vWvUO579V+PDLrOu57tR8dB4Zz86PX0P3GCPatP8+8t7aRllR2O1aUGW81YQ1nYq5aQrDHr2/Ftc2DeHHBXg5fTHPS4OoetSZApJTzpJRNpJTuUspGUsohNtemSSlbSCnbSCmX2JQPlVKes5wfs0QGbimlHC2ldG5YVMXVQ2khThwEW2zQLJKbJz/D5ZPHWfLhO8hK/ODodIJrR7bgpoc6ceViJj+99jdnDl4p9R5X3Q65avALB3MeZFY8CrMtep3gvbu64mXU88h328jKrZ8rTFfcwlIonEtZIU5OnrSbN6R5t54MHHs/hzdvYN0P31S6++ZdGzD62R54eBtY+L/tbF92SllZ1RZlJJaqCI38PHj3zi4cupjOS7/Vz/x6SoAorn6sIU70pdiEjBkDISElBEm3oSPodP0QNs//ib1rVlZ6CIGh3ox6tgfNuzRgw69HOLNBlprRUAmYasK/8r4g9hjQugGTYlow9+/TLNhR/9LflmXGe1WTnJxMQkICeXlFwxP4+/uzf//+WhqVc7ka52IwGAgJCSEgIKD8N1utrSZO1Lat7JGYqF23qS+E4Pr7/0HyhfMsn/0BAY3CCG/bvlLjN3q4MWRiR7YvO8Vf84/yy5tbuemhTgQ0KmV1pHAuVXAmdMSTN7Rm8/Eknv91N53C/WnewMdpbbs69VqAnD9/nsjISDw8PIrsPaelpeHr61uLI3MeV9tcfHx8yM7O5sSJExUTIFAoRMaMcVzHap01dqymO5k2DX1cHMOffI7vpjzJgrenETftHfwbNqrUHIQQdBsSwbkrx7j4dy4/vfY3g8a3J+qaBtp1FcukevEKAZ2h0s6E9nDT63j/7q4MfX8tj363nV8n9cXDTnKqq5F6v4Xl6empFJd1CCEEnp5VSDMaF1d6tF7QrLOkLJIS19PHl1v//R/MpnzmvfESOY5WMeXEJ1Qw+vke+Df0YvFHu9m08Bhms9q2qnZ0OvALc+oKBLTUt2+PvoZ951OZtujqWPGXh3ovQBT1kLKU6rbY+IsENW7C8H8+R9K5Myx6/03M5cwr4Qi/YE9u+1c32vYJZcviEyz6cBe5mfXTmqdG8WvidAECcH27RjwYHcU3G0+yePd5p7fviigBUk7mbz9Lv9dXEfXsIvq9vor52yuvMNu5cyc33XQTAwcOpH///jz44IMl9DAV5YUXXiAiIoJBgyrj/F/PsCrVg4PLV99k0ra0hCDilpHcHtGG49u3sOabz6s8FDejnuvubcfAe9pw5kAS8e+dIDijMZn7DXz1/HqnhYdXWNj1I5zfASfXwbsdtfdO5OkhbbmmaQD//nkXpxKv/lTHSoCUg/nbz/Lcr7s5m5ylxVFKzuK5X3dXSoikpKQwduxYZsyYwZo1a1i3bh333XcfJlPVnjwnTZrE6tXlT8da74mLg4QE+PZbbUtLiNKttKxWUSdPEvHm29xxOY1tixewa8UfVR6KEIKOA8K59alumPIkt+56iuQ/PAuCMVYpPLyikF0/wm+PFwYuSzmtvXeiEDG66Zhxd1cQ8Oj328jNr5rDoqtTr5Xotrz02172ndNiRZpMJvQ2PybbTyWTayr6RcjKM/HMz7v4fnNJL+f2jf34z/AOdvtZtGgRt9xyCy1atCgo69+/f8H5c889x4YNG8jNzWXKlCncfPPNTJ06lcOHD5OWlsapU6eYO3cubdsWDfQXFhbGibISKSlKEhdXqFyfM6d0Ky0rUtIkfi39R41k5ecfERAaRrOO11R5KKHN/bnun1Es/O8+MBfVy1nDw7fubS82qaJcrHwZ8rKKluVlaeWd73BaN02DvJg+qjMPf7uN15cc4MXhlbPaqwuoFUg5KC48yiovjdOnT9O0qRYr8vLly8TExNCxY0e2bNnCH3/8wZUrV1izZg0rV65kypQpBf4ADRo0YOHChTzzzDN8+umnlZ+MwjHl8RexIKSk18YtBIaF89s7r5F0zjk+AB5+buil/ee6qoSHV+DY8sqJFllWbuwYxn19Ivh8/XGW77vo9PZdBbUCsWC7Yihu+trv9VWcTc4qcU94gCc/PNSnQv00bdqUffv2AZpQiI+PZ9y4cWRnZ7N7927WrFlTEEEzJyeHxMREALp37w5As2bNWL58eYX6VFSA8viLWBBnzjDymRf5bsqTzH/zZe555W08fKrmA7Dq9CrSje745gaVuGYN1qioJP5NtG0re+XVwPPD2rH11BX+9dNOFk+OJjygCtaDLopagZSDp4e0wbOYXbenQc/TQ9pUuK2hQ4eycOFCjh0rzGKXn695JHfo0IHBgwcTHx9PfHw8u3btIiREy9Fta2qsvJSrGetKpCxz32bNCGgUyi1PPU/KpYv89u6rmPIde5eXxaJji3h367tsavY7ebrcEtd9gz1K9V6vaF+Dfx5M5686M/jnwSw6tsgp7bo0178IBjs/4m2qmp3bPu5uembc3Q2TWfLYd9vIq8SOhaujViDlYGRXzXt1+tKDnEvOonGAJ08PaVNQXhECAgL4+uuvmTRpEllZWXh6etKsWTM6dOhAYGAgGzZsICYmBiEETZo04ZtvyheDacaMGcydO5f9+/czaNAgPv744yJ6FkUFsdWNTJoEs2YVKtKtnDwJkZE0mTaNwQ89xh8z3+XDCXeRl5ODb3AI0XfdWyTjYVm8t+09ckw5HGmwFYDep27GJzeQdGMyuUEpyMMRfPjCYtIHHsSjEfgYffAxWA6jD94Gb3wNvngbvQvKPd1K+jktOraIqRumkm3SogOfzzjP1A1TARjWfFjl/l51AaueY+XL2raVXzi4ecLWr6DDbRDR1+ldRoZ48+ptnXj8++28vewQz95UviRldQVRn55me/ToIbds2VLwfv/+/bRr165EvavNe/tqnIujz67acCRELOT7+7GsfUv2Nw0rKHMzujN44qN2hYi9ZD+dv+rsMIx7n7A+6M/70nLbQAy5HmyJWsz2hispy3FdL/R4GzSB4m3UBMzexL3kmErqU8K8w1g2alnpDdqhTiWUKk5mEnw2GDIuw4TlxO89Vy1zee7X3Xy/+RRfjO9JbJuGTm/fHs78XIQQW6WUPYqXqxWIQlEeFi92KDwA3FJSuWHzTqTZzIEIbWWan5vD2rlfl3sVEuodyvmMkg5oYd5hzB48G4Cs23NZ9dV+9LtvYbTXOHrd3RSTew5puWlk5GWQnpdOem669mo5L15uT3gAXMioh2bCXkEw5mf4dBDMuR1ju5erpZv/DG/P9lNXeOrHnSx+PJpQ/zIzgtcJlABRKMqDo6RUNhhMJvrvPlggQADSEsqfd2Jyt8lFtpYAPPQeTO42ueC9p4+RoZM6s2v1GTb8eoTEN9MZdH8H2rRpbK9Juwz+ebBdQRXqXU9NhAMj4Z4f4cthdNr9X4gdDEZvp3bhYdAz455uDP9gHY/P3c53D/TGTV/3VdB1fwYKRU1QWlIqG/wys3jg91U8+eMiHvh9Fe3PnCcnM6Nc9w5rPoypfacS5h2GQBDmHcbUvlNL6CWEEFxzXVNG/bsHBg83FvxvuxZLq5xK2sndJuOhL/oEXFxQ1TvCu8GoL/BJPw4/jQeTc4wVbGnZ0IdXRnZk8/Ek3l952Ont1wZKgCgU5aEC8bP8M7MQltcbN2zF6O2DuWlTu0mrijOs+TCWjVrGrvt2sWzUslKV2g2a+nLH8z1p1yeMLYtPMO/t7aQmljQ3t9eHVVBZeazrY1e3Ar08tLmRw60mwuGlsOTpUrcsK8vt3ZswqnsTPlh9hPVHqpYV0RVQAkShKA/FTXvtRHCWlNRpC8uhO3MG8wMPlEuIVASDuxZL64YJ7Uk8l84Pr/zNka2XyrzPKqhWjFqBQWfgWMqxMu+pD5wLvwn6/RO2fA7r/1ctfbw8ogMtGvgwee4OLqVll32DC1MrAkQIMVoIsVcIYRZC9LApv0EIsVUIsdvyep2D+6cKIc4KIXZYjqE1N3pFvSUuDk6c0J5MzeaicbQiIsrM5KHLzib3oYdI8/VhYGwsab4+nH1Ry8e+f+1qZj8ynrfvGs7sR8azf23F4pq17hnKnVN6EdDIi6Wf7GH1nAPklSNPdyPvRtze6nYWHF3AuXTnR6itk1z/H+g4ClZMhV0/Ob15L6MbH97TjbTsPJ74YQemOhzGv7ZWIHuA24A/i5UnAMOllJ2A+4DSnCDelVJ2sRyLq2mchez6UYveOTWgylE8qyMa79ixY4mJiaFHjx68++67VWpLUU6sAsVs1l7LcjwEDBkZ+KZnIADf9Awa//dVpBCE3zSM8K07QErSEi6zbPaMCgsR/wae3PZ0N7oNaca+tef46bUtJJ5NL/O+CZ0mAPDZ7s8q1N9Vi04HI2dCRH9YMAlOrHN6F21CfXnplg6sP5LIzNVHnN5+TVErAkRKuV9KedBO+XYppfUxaC/gKYSo/fgN1iieKacBWaUontUVjfezzz4jPj6ejRs3MnPmTNLS0qrUnqISlENP4miLyy8jiyGbd9L2pBZTy2oCXFH0eh19bm3JLY93ITsjj59e38KeNWdKjV4Q6h3KbS1v49cjv9ZPU157uLnDXd9CYBTMvQcuHXB6F3f2bMqILo15d8UhNh1LdHr7NYErm/HeDmyTUjqKIPeoEOJeYAvwlJTySpV6W/IsXNgNgKcpH/Q2f5ozf0Nx2/m8LFjwqObFWpzQTnDT63a7qa5ovEajEYDs7GyaNWuGV3kTJimch9VzfcoUzUtdiCKKWHs6ElvcpCR2294CM+C0xMorWZu2D+Ku/+vFyi/3seb7Q5zef4XYsW3x8DbYrT+h0wR+Pfwrn+/5nOd7P1/pfq8qPANtfERGwQMrwNd5ps5CCKbd2oldZ1J4fO52Fj8eTbBP7T8vV4RqEyBCiBWAvb/2FCnlgjLu7QC8AQx2UOUj4L9o/5P/Bd4G7nfQ1kRgIkCjRo2Ij48vuObv71/wpO6el4vOaronId/GjE9vyrH7jy9NOZjsmPuZ83LJcbACOHLkCA0aNCAtLY2EhATuvfdeEhMT+eijj0hMTOTSpUv8/vvvZGZmMmjQIAYMGEBOTg7+/v7MmjWLH3/8kZkzZzJt2rQSbd97772sW7eOCRMmkGkJBGgyma6a1YjtXLKzs4t8li5DeDh8+SUADVesoPmnn+J+6RI5DRsik6/gmVMyxpUtnjZbmW4eHlWeo08nSSOj4Piuy5x+4TL+kZByQkuJYfCChp0hIFLbiOjp3ZO5B+ay+PBiUkwpBOoDGR4wnJ4+PUvtIz093TU/i0pgby4+bZ6h6/YpZH58Ezu6vIrJzblBEce1NvHfjTmMn7Waf3Z3R+ekFNs18blUmwCRUlYqNZ4QogkwD7hXSnnUQdsXbep/AvxeyjhmA7NBC2Vi69q/f//+wjAft7xTUF4i/Me7He1G8RT+TXF7YKndfo0OxtOyZUv27duHr68vvr6+rF27lnHjxqHX6zl69CgbNmxg+PDhAOTl5ZGbm4u7uzt9+vTB19eXNm3asG7dOrvhSebNm0dmZiYDBgzg3nvvpX379ldtKBMPDw+6du1ayyMqg5gYeOUVADyAsy9OoeGrb2Aoz3alEORnZZG+YxMx9z2IT2DJ6LzlJhYunUzltxk7SdhXKKDyMuHiNh3t27Wlde9QTu09xV9b/iLFlALAFdMVfkz+kfbt25dq4lunQ5kUw/5cYqBNM3y/v4voC5/B3XOL7lA4AV2DE7ywYC+Hdc14aKBzYtjVxOfiUma8QogAYBHwrJRyfSn1wmze3oqmlK8+7EXxNHhq5RWkOqLxSinJzdWebD08PPD09MTT8+oLHV3XCX95Gpee/zdpPt4OIl5pS+ouSak8Fr+ZJ39axIApL7F+xFB2Ll+MNFc+mmvDCD/c3Er+u1sTVQF8u//bEtezTdm8t+29Svd71dB6MAx7G44sh0VPON1HZMy1EQztFMqbSw+y9WTVduNrktoy471VCHEG6AMsEkJYH+MfBVoCL9qY6Da03POpjcnvmxZT311ALPBEtQ648x0w/H3wbwoI7XX4+5XKYmYbjXfgwIHceOONeHl50aFDB4YOHYqvry8xMTHExsYyYcKEcrWZn5/P4MGDiYmJoX///tx+++1ERUVVeGyK6if85Wn4pjm2jNIB1/+5CePFSwipebZfv3ErZ16YwvcvPs3lk8cr3Xf6FfvqRGuiKkcK9AsZF+pn+Pfi9BgP0U/Btq9h7dtObVoIwWu3daZxgAePf7+d5MzStzpdBRWNV0XjrTPUajReJ5MdGorHxfJnqsv38yU3OxvPXMsWlE6HMJu17Ikmk2ZCPG1aoSLfDl89v95uVkNPPwP3vxntMEYWgA4dZgpXQB56j4IwK1f/FpYNUsK8h2DXD3DrbLjmTqf2v/N0MqNmbSCmTUNmj+1eIhR/RaiJaLwutYWlUNQXjj3wQEmT31Is59xS0/DKzSsw+xXW7SyrPuXkSRgzBgY5Vj32GdECN2PJf/mstDwObrpgN0aWu94dD71HEeEB9XhrSwi4ZQZERsOCR+DYGqc2f03TAJ69qR3L913ki/UnnNp2daAEiEJRC1waNKgwNIrFk71cWRDLYuVK8PW1GzKlde9QYuPaFqTG9QlyZ+A9bQhvFcCKL/YRsqcd/+lTNJjjS31fUuHfi+NmhDu/heCW8MMYuLjPqc3f3y+SQe0a8dqS/ew6k+zUtp2NK/uBKBRXN7ZZD20pRz72UklPR44Zw5WffyRoXlGL+da9Q2ndu6h1fbu+YcR/d5Ati0/Q8lIEi+9dgpuxMIXze9ves7u1FewZXPkx1nU8AyDup6I+In7lD6lfGkII3hrdmaHvreXR77bz++P98fOw779T26gViELhStgGbbSuTIIr/kMtgMD5CzEZDGUGcNS76bhubFv63NqCI1suMf/d7WSmFipx7W1tAaTnprM3YW+Fx3bVENAU4n6E7BSYcwfkOM/fKsDLyAf3dOVschbP/rKr1EgCtYkSIAqFq1E8xtZ774Gh4k+gAtDn5yPHjNGU7UKAm5uWnrd4XSHoNiSCGx/qSOKZdL5/aR0fT3qCt+8aztm3f+YJz3uKbG090/MZgj2DeWDZAxzPqbxlWJ0n7Bq44yu4tA9+vBdMVYtpZ0v3iCD+NbgNi3df4NtNZSc0qw2UACknzjRjrI5gii+88AIREREMKqZEnTNnDn379qVfv35s27atSn0oaom4OPjii6IrEV35/3UFaMIIwGRCfvQRV26/jTMH9pJ07iw5mRkFT7gtujaky/VmstIyyDMNRqePIC3hMpfnr+O9Rs8V5CkZ234sX974JUEeQbx/4X1ifoipvya+LQfB8P/B0VXw9QinBV0FeGhAcwa2bsB/f9/H3nMpThmuM1E6kHKw6NiiIqlGz2ecZ+qGqQAVTsJjDaY4b968gnhY69atw2QyYajEU6aVSZMmMX78eCZOnFhQduXKFWbNmsXmzZs5e/YsY8eOZd0650cWVdQAjvQlkybBrFlIKcsMJ29FAAG/zkP3xx+s69SGAxHh6A0GvPwC8PIPIPH0SfLzjRh9RmLwGUl+1mryc3aWyO8e6h1KXLs4Xtv8GonZWjDAqvxv1Gm63QsHl8JBm6AY1qCrUCmfMQCdTvDOHdcw9P21PPbddhY+1h8fd9f52XadkdQyb2x+gwNJWsRNk8mEXl+oRNx1eRe55qKOPdmmbF5c/yI/H/q5RFttg9ry717/tttPdQVTDAsL48SJE0XKNm/eTJ8+fTAajURFRZGWlkZOTg7u7nUrYJuiFGbOhJkzuXLrCALnL6yQEPHPzGLoph0M3neUw3F3crJDOzJTU8jPywVyyU37AYP3UAxe1yN0QaQlxJOXk43BvVAf8uXeL0u0nW3K5rVNr9UvAQJwYWfJsrwsWPlypQUIQLCPO+/d1ZW7Zm+k5ysryM4z0TjAk6eHtGFk1/AqDLjqKAFSDooLj7LKS+P06dM0bdoUgMuXLzN69GgSEhL48ssvSUhI4MqVK6xZs4bMzEz69OnDsGHaP2GDBg2YM2cO3333HZ9++ilvvfVWmX0lJiYSEBBQ8D4gIICkpCTCwsIc36SokwTNW0BCu7YEHzhYbiECmiAxpKXR/rOvaO/nB0lJpHl78WeHVhyICCcvYyHSPAA3j+4IfQAfPTieqG5daHNtP6K69nBoypuSm8KiY4vqlxBJOeOg/LS2lVUFIXIhJRs3nSArT/P7OZucxXO/atHDa1OIKAFiwXbFUNx725GHbph3GF/c+EWF+mnatCn79ml24w0aNCA+Pp5x48aRnZ3N7t27WbNmTYH3aE5ODomJ2tZA9+7dAWjWrBnLly8vV19BQUGkpBTum6akpBAUVIWgfAqXJmT/AZJuHUGAzUpE6nToyhNDKy8PLN813/QMbty0g5s27bC08zt5bkbiBzzFyc5jObVvGyf2JiB065mge4m9wUv4O2ojTS960v1gIN7ZejI8TPyQ8AHDnqpHAsS/id2gq0CVt7KmLz1IfrHMhVl5JqYvPVirAkQp0cuBPTNGD70Hk7tNrnBb1RFM0RG9e/dm48aN5OXlcerUKXx8fNT21VVO0LwF6KREWA6dyQT/+IdmhVUB9Gg/DlbPd2N+LjeseZOovetB1xed3g8hBG7Sn86Xb2fM6kHE7OtPkPFhPAKeJMj4MNfsbF/hrIp1GntBV61Yt7IqybnkrAqV1xRKgJSDYc2HMbVvUQ9daxygilIdwRQBZsyYwZgxY9i+fTuDBg3i6NGjBAYG8sADDzBw4EDuvvtu/ve//1V4vIqrgJkzIT9fy+FehURjwmTi2k0l094KYcDoNQij95ACwaLT++HuOYRl3ywn31wyZ85ViTXoqiMcbXGVg8YB9gWTo/KaQgVTVMEU6wxXUzDFWgtAOGcOTJ5csF1VUSSQ5tOQjb20h5trN3+Gb/pl0nwasLHXBA63KmpGbjalsCnmG/51w4t0adilioOvfpzyuTjIH4R/U3iicpkn5m8/y3O/7i7QgQB4GvS8dlsnh1tYKpiiQqFwLnFxkJCgrUas3u7BwWB0lAKtKALwS7/Edavf5Pr46filX0Ig8Uu/xA2rXuMfHw8iem1hkEWh86PLwhw+m/YEU395kqTspGqamAvhxPxBVkZ2Dee12zoR6q9tpft7GkoVHjWFUqIrFPWR4n4lc+ZoudxPndK2uTIySr3dTZoonhVL05dIOu1bSNtDyzHkZ5Pm04Cdg+IQyRfRzRN8s3wNbvjhE+hBn5EtMOXuZ+3cr0lLTMA3OITou+4t4mtSJ7EqyldMhdSzYPSFm9+pkhUWaEJk+DWNaTllMff1jax14QFKgCgUCigpUCwOipXJvKcp3TXlrl/6JfoseJ8e7t54ZKeR5vNtwVbX8i93Y8paSV7WZQDSEi6z5KP/seqr2WSnp9dtgdL5Du345ja4chw6jXZKs3qdINDLSGK6/QjJNY3awlIoFCWZOVMLfyJllUPMu0kTntmpBVtdsX++Q6vDK0DqEYZri9SVJhPZaWkgJWkJl1k2e0bdtuRqOxSSjsHlg05rMsjbSFKGa2QsVAJEoVCUzrRpJa23DIZy602KY8jPof/6GQAInS9uHn3RuTUDSobyyc/NYe3cryvVj0vQZqj2etB58cGCvI0kuogAUVtYCoWidKxbW1YdSbNmmlABeOghZEZGhbzfATxz0rj/y1vxyElFCh1CmknzaciG7qM4GBmBOf8s5vyzILNJS0xw6nRqFL/G0LgrHFis5VN3AiE+Rg5ecF7o+KqgViDlZP/a1cx+ZDxv3zWc2Y+Mr9Ky2tnReLOysrjhhhvo378/1157LUuWLAHgxIkTNGvWjJiYGGJiYli0qJ5FSVU4j+Ih5q06k/R0zo4YUeioaA0ZXwYC8MxJRQA6aS6w7rp+3ae0PZWE0WcEHgGTMPrdi8F7EOt+/IvUxNp1mqs0bYfB2S2Q5pwMjq60hVUrKxAhxGhgKtAO6CWl3GIpjwT2A9YNw41Syoft3B8E/ABEAieAO6SUV6prvPvXrmbZ7Bnk52qKK+veLFBhBV91RON1c3Pjk08+ITIykoSEBPr168dNN90EQJcuXVi9ug7vIStcniP//CdN5s8vLLC16AoKqpDPicGUyw2r3yB6/f/wzM0hzTuIv3pNYOeqLHau+gt3L2jWoSHhrQMJaxlAYKhXkSgNLkmbYbDqFTi4BHqMr3JzQd7uJGflkW8y46av3TVAbW1h7QFuAz62c+2olLJLGfc/C6yUUr4uhHjW8t5++NtysvrL2Vw6qYUXMeWb0LsVhn44f+ggpvyiK4T83ByWznqfXauWlmirYURzYsdNLFEO1RON12AwEBkZCYCnpyc6m1wRu3fvJjo6mqioKN59912CK5HdTqGoEMUtukJCKiREdICX5WHNLyOJG1ZPZ/Dq6aT6+PNXt9s4nHk7h/++BICHj4GwFv40bhVA41YBhDTxQVfLP6olaNgOvELgj2fh9ye0mFnXv1hps94QHyNSwpXMPBr41m5ooloRIFLK/UBVnhxGADGW86+AeKooQEqjuPAoq7w0qjsa7xNPPMEzzzwDaCHed+3aRePGjZk9ezbPPPMMn31WMhSFQlGtvPdelfK8W8WBf3oKg//8AvHnF6R5ebGh52CSBo7n8mnB8Z2aniRXl01ywHlat29CTM9eNIryK5LfvVbY/RNkJ4M1pEsV84QEeWvGC0kZufVTgJRBlBBiO5AK/J+Ucq2dOo2klNbwuBeARo4aE0JMBCYCNGrUiPj4+IJr/v7+pKVpyqget99dUF48H8h3zzxGelJJRZ5PUAhDn5xit19ru8UJCQnhwIEDpKWl4eHhwW+//cbDDz9MUlISW7ZsYfXq1URHRwOabuPkyZPk5OTQvn170tLSCAkJ4cKFC3bbf+ONN/Dw8GDUqFEF1728vEhLS2PEiBF88MEHDsdVFzCZTAXjz87OLvJZ1jXS09Pr9PhtKXMu4eE0fOIJmn/6Ke6XLpHn64tbZia6/IrHyLIKE7/MTAatmc8f2Sc4ENWEk2GQGByCf24EYWktubJOz/x12xE68AgC7wbg1UDgFQJ6o+MH1+r4XK7963k8iscDy8sie9HzbExqWOH2Tidq4UxWrt/M+WDHwrEmvmPVJkCEECuAUDuXpkgpFzi47TzQTEqZKIToDswXQnSQUqY66kdKKYUQDr2dpJSzgdmgxcKyjQ2zf/9+u3GiisePGnDPfUV0IABuRncG3HNfheNM3X777QwYMIB//OMfNG/eHNBWYl5eXnTr1o3Lly/z3ntaKIjc3FyMRiPu7u54eXnh6+uLl5cXbm5uJfqdMWMGp06d4quvvipY2aWkpKDX6/H19WXNmjW0a9euTsfFsv1cPDw86Nq1ay2PqPLUWiysaqBcc4mJgVdeAcAIhXqSkycr3a8bMGzTDoZt2kGW0cDqrh1Y1vMka5r/TrKfjva53flHo6c4fySZS4fSSNgvQUBwuDeNWwYQ1lLb+vL2L3yKr5bPJd6+FZlHzmViovuDvmI/w/vjjwAHefPvbMJLSSxVE9+xahMgUspBZdcqcU8OkGM53yqEOAq0BrYUq3pRCBEmpTwvhAgDLlV5wKVgVZQ7I+SCbTTerKwsPD09adasGR06dCAwMJANGzYQExODEIImTZrwzTfflNnmpUuXmDx5Mn369CE2VhvTypUrWb16NVOnTsXf3x8PDw8++eSTCo9XoagWbPUkc+ZUeovLupbwys1j6KYdxO4wsLpLB/68JoC9zbfR56HmCJ2OvFwTF4+ncv5IMucOJ7P/r/Psjtei4/o18NR0KC39yUmTWnpgZyrmS8sTMqM7RP8LrrkL9GUb0czffpb3Vh4ueF/biaVqNRqvECIe+JeNFVYDIElKaRJCNAfWAp2klEnF7psOJNoo0YOklM+U1Z+Kxlu3UdF4XROnzKW45RZoinchKhxOJVcHeQYDXjl5pPp4khXVhEb7jiFMJs3ceOJETB/MIOF0OucOJ3P+SDLnj6SQnaHpNL38jZYVSgCNW/kT1NgHna4KAmXXj5rOI8/GDNngCd3vh5Pr4fwO8G8G0U9Alzhwc6zX6Pf6Ks7ayQESHuDJ+mevK1JWE9F4a8uM91bgA6ABsEgIsUNKOQQYALwshMgDzMDDVuEhhPgUmGURNq8DPwohJgAngapFKVMoFLVLccstK5XY6jKawZijCQP/9Cz8dh8udHQ0mZAffYR+1iwaPfwwjWbOpOsNzZBmyZULmcQv3oyPCOT8kWSObNU2NoyebgWWXmEtA2gY4YverQKWXlZF+cqXtZwgtlZYUsKRFRD/umah9edb0O+f0O1eMHiUaMrVEkvVlhXWPGCenfJfgF8c3POAzXkicH21DVChULgGVsEyaRJ89FGlmii+dhAAUiI/+kg7nzkToRMENfYmqKUgJqYDAKmJWZw/ksK5I8mcP5zMyT2aKbLeoKNRpJ9FoPgT2twfo0cZP6XW4IolBieg1Q3QchAcWw1r3oQlT8Pat6HfZHD3gzWvFwie+3xu58v0XiWaqa3EUq5ohaVQKBRFmTlTe509G0ym0uuWEwHIjz4ic8FPiFdfw+u+B4pc9wv2xC/Ykza9NVugrLTcQoFyJJmtS04gJQidoEFTH23Ly6Kc9/StYJwwIaDFddA8Fk6sgzVvwNLnitZJOc3/6WeRbszn59y+BcWeBj1PD2lTmT9BlVECRKFQ1A1mziwUJFXMrGhFAN7nEjCNexA57kEGoqU5OdkwiGWjbiliLOPpa6R51wY079oAgNzsfC4cS9GEyuFk9vx5lp0rNWV5YKgXYa0KBYpfcNEVwqFNF/hrwVHSk3LwCXKnz4gWtO4dqgmSqGjtmN4KMoraB7mZsnnZ+xf+8rqes8lZuOlErSaWUgJEoVDUPYpbcdkq4NPSILdisaKKe1NEXEriwZlfwswvyff3w+3DmSV0NEYPN5q1D6ZZey26gynPzKVTaZw7fIXzR1I4suUS+9aeA8An0L1Ah5Kblc/fi46Tn2sGID0ph9VzDgBoQsRKxmW7Y/XKusD6qdfx2brj/Pf3fVzTNKBCc3UmLubz77oc2nSBr55fz4cPr+Kr59dzaFPlA6M5O5giwAsvvEBERASDBhW1np4zZw59+/alX79+bNu2DQApJY899hjR0dHcfPPNJCXVgzSjiqsX20CPCQnw+eeF6XojIuD6iqtLhc3hlpKKHDNGa08IzZJr0qQS9+gNOsJa+NP9xkhufvQaJrwdzZ3/15PoO1vTKMqfMweusOa7g/w172iB8LCSn2vmrwVHizbo38T+4CzlN3XUhM3i3eft16sBlAApB4c2XWD1nAOkJ2mOhNYnhsoIEWswxRkzZrBmzRrWrVvHfffdh6mK+7qTJk0qETTxypUrzJo1i/j4eL799lsef1wLn7B06VIyMzNZu3Ytd9xxB2+++WaV+lYoXIrikYNXrIB//KNKTRZRxJvNyI8+wuTlRdL0N0lPSkSazSXu0ekEIU186RzbhBsndmTcG/2Ie/naEvWspCfl8MfHu9my5ASn9iaS1fc/RXKrH8qM5qvLs/nw4Ht89fx60g+m0LVZAEv21J4AUVtYFtb+eIiE0+lAyVAmF4+nYMovaouen2tm1Tf72bvuXIm2Qpr6EH1Ha7v9VEcwRdDiXp04caJI2ebNm+nTpw9Go5GoqCjS0tLIyclhzZo13HzzzQAMHz6cjypp3aJQ1BlmzoRDh2DlSqc0JwB9VhaBz/wbnvk3EtjfuT377xqFf4NG+De0HqH4NWyEh7cPQggCGnrhE+Re8DBqi5tRR8KZdI5ut25dBePj8w0N2IPIy+BkTg9Mmh9/wUPskO5BvL7/NKcSM2kW7FWizepGCZByUFx4lFVeGtUdTNGWxMREAgICCt4HBASQlJREYmIigYGBBWVXrlRbJHyFwnVYsaKoX4ler1l0GY0V1plYETav7Xbto92ul8l2N7KqS3v+jChUbBs9vfBv0BC/hqH4BbUgM6UhZlPhusbNqCM2ri2te4eSk5lHwul0Lp1K4+jWIxw/EYmUfiW84/NzzXju16I8Ld5znocHtqCmUQLEgu2Kobj39lfPr7f7xOAT5M6tT3WrUD9NmzZl3759gCYU4uPjGTduHNnZ2ezevZs1a9YUeI/m5OSQaLEy6d69OwDNmjVj+fLl5eorKCiIlJSUgvcpKSkEBQURFBREcnJyQZlVmCgUVz2OHBY7dADL/2Vlsf68e+bkMnTTDoZu2gGA2cOD/WPu5nBIA5IvnCPl8nbM5kjcPKMROl+kOY387K38vXAhh/4qXLmkXb7AmT0LMeXl4h7whN0+s5JzuaajP4t3KwHisvQZ0YLVcw4UUXy5GXX0GVHxD2zo0KG8/vrr3H///QXBFPMtUUk7dOjA4MGDSwRThKKh78sbfqZ37948//zz5OXlcf78eXx8fHB3d2fgwIHMmzePkSNHsnjxYgYOHFjheSgUVxV798KcOWQ/9RQeFy9WuTnbtYI+O5uOn35BRx8fmDULec89ZKWmkHLpIimXLpByKZeUyw1JuXSRi8eOcHjzBszFdKLSnIbQ+5Xox8ctiVeMSwg8E4+cmoioYq6RiqIESDmwmtbZtduuINURTBG0aLxz585l//79DBo0iI8//pgWLVrwwAMPMHDgQIQQBYJpyJAh/P7770RHR+Pn58fXX39d4XkoFFcdcXFsDA8vjB/lhIjBRUhPhzFjEGPG4BURgde0aYTZWQ2ZzSbSkxL55JH7C8rys9Zi8B6MEIUBFwX59PH6klbn1iKs5lC2uUaoeKj4ilKrwRRrGhVMsW6jgim6JvVqLk5yYLQigVyDjhfHN2b7De2Y3G0yw5pres/Zj4wnLaHQF0RnaIObZzQ6nS8GXTZ50h0vXTKZ5gB8dAn08fmW1l6W9En+TYnvOqPagykqM16FQqEoL3Fxmq/Jt99qyvcqIgD3PDOvzz7DvDEruanFzWSGN4Q5c4i+617cjIWRec15B8lN/ZSW5mfo5/M5IMg0BwE60s0NWZ06iUOZWjK6RflJvHjmRTp/1ZnBPw9m0bFFVR6rPZQAUSgUiooSFwc5OZogCQ6ucnMC8M4xa/ngz11GjhlD4/vvI+y2GIyBmu7DMyiQAM8c9qaGsjH9ToqHiczHg7/Sx7DI24upDYK4YrqCRHI+4zxTN0ytFiGiBIhCoVBUFuuKRMrCoxKe78URgN+R04y+7XFCDv3Bl0NP8tG1O5gRfZFL/rlkme0LrTRzA14KCSK7mMlvtimb97a9V+VxFUcJEIVCoXAmK1Y4ZWViDaVy1+or7Bq3h13j9rDxXye40VeAgyzfufpksnT2f9YvZFQ+/JIjlABRKBQKZ2NvZVLJcCq2cbnck9OIeWc5j3xyG/d/eSutDq8oqCelGbfUdXQ9VTIRFUCod8WtRstCCRCFQqGoCWbOdKry3TMnlRtWvcakj69n0sfXM2DdB5h1QXQ/FIBHMetaD70Hk7tNrnK/xVECpLzMmQORkaDTaa9z5lSqmRMnThAYGEhMTAwxMTFMnz6d119/nd27d1e4rZiYGM6cOVOkLD4+nrCwMGJiYujVq1eJAIsVZf78+Zw6darc9ceNG0fXrl0L5nf5sv2Q1OVhx44d/Pnnn5W+X6FwOazKdyk1YWKNGqwvHlC+fNiuTjrtW8jkr1/kngVbuGtJBKNWhRN11osw7zCm9p1aYB7sTJQjYXmYMwcmToTMTO39yZPae7AfFqEMunfvzooVK8quWEmGDRvGp59+yqlTp7jpppu45ZZbyrzHbDajs7N3On/+fEJCQmjWrFm5+//ggw+KBIi0UjxIZVns2LGDM2fOMGDAgHLfo1DUGYqHValiOBWr2jwkLZknf1xMltHAyu4daPnGc7RrHlu1sTqgVlYgQojRQoi9QgizEKKHTXmcEGKHzWEWQnSxc/9UIcRZm3pDqzyof/4TYmIgJgbPoUMLzomJgQkTCoWHlcxMrdy2nvX45z8r1PW4ceNYt24doMW6euihh7j22mv517/+BcC+ffu47rrrGDhwINdff325n+qbNWtGRkaGw/tjYmJ46qmnGDJkCIcPH+aBBx4gNjaW/v37s3nzZvbt28cff/zBY489xujRowF46aWX6NOnD71792bRorLNAk+cOEHPnj0ZO3YsDz74IBs3bqRv377079+ff/zjH0gpOXHiBN27d2fMmDF069aN//3vfwC88847fPbZZ8TExHD27NkK/U0VijrH3r3aqsTbu0rNWFckXrl53PzXDtoOuA4pBH9GdKHf66uYv915/0u1tYW1B7gNKLI/IaWcI6XsIqXsAowFjkspdzho411rXSnl4modbU7JQIqllpfB1q1bC7Z41qxZU+TapUuXeOmll/jrr7/4/fffSU1NJSoqihUrVrBmzRpGjRpV7vDrO3bsIDg4uNT7e/TowdKlS1m9ejUtW7Zk9erV/PLLLzzxxBO0b9+eG2+8kQ8++ICffvqJHTt2sHbtWjZs2MDSpUt54oknMNvJg/DYY48RExPD+PHjAU2IfPjhh3z++ec8+uijfPvtt6xbt46cnBx+++03AM6fP8/s2bPZsGFDQciVJ598kgkTJhAfH094eO2k7FQoapS4OC3kiVXxXkWBYrvFFX1qJ2ufu57nft3tNCFSK1tYUsr9QInwxMW4G5hbIwMCsDz1AmQVD/8RGWk/Hk5EBMTHV7ir4ltYX3zxRcF5eHg4oaGatUSTJk24cuUKubm5PPnkk6SmppKSkkLPnj1LbX/RokXExsbi7u7O+++/z5kzZxze37dvXwB2797Nhg0b+OOPPwCKRPG1cvDgQa699lotr0FAAA0bNiQhIYGGDYvG3LHdwjpx4gQdO3bEz8+voF1rEMm+ffty4MABOnfuTLt27fDy0vIZVGSbS6G4qrFuc82ZAw89BBkZlW7K+mu795WbiPZe6ZQ86q6sA7kTGFHK9UeFEPcCW4CnpJR2k1oIISYCEwEaNWpEvM0Pvr+/P2lpaSXuMZlMRcrdXngBj8ceQ2RlFZRJT0+yX3iBfDv3l0Z6enqJ9vPy8sjMzCQtLQ0pZcE1a70PP/yQW2+9ldGjR/PJJ5+wc+dO0tLSMJlMpKenF2krMzOTwYMHM2PGjII2nnvuOYf3Z2VlkZaWRosWLWjSpAmPPvoooEUCTktLQwhBamoqaWlphIeHM2vWrAJBdOHCBdzd3R3OxTpfoOC9r68vu3btIioqijVr1jBs2DDS09Mxm80FdaznJpOJjIyMEn8PgOzs7CKfZV0jPT29To/fFjWXGiA8HH7/nYYrVtDygw8wpBb6gZT6GF4Ma92zyVlOmWe1CRAhxArAnuHxFCnlgjLu7Q1kSin3OKjyEfBftFhk/wXeBu63V1FKORuYDVowRdvgYvv377cbaLBEAMIJE8DDQ4vMeeoUNGuGmDYNz0oo0H18fNDr9UXaNxgMeHl54evri06nK7im1+vx8fHhjjvu4NFHH2X+/PmEh4djMBjw9fUtuG7blpeXV8F161zKc/9jjz3GY489VqBw79GjB9OnT+fWW2/l9ddfZ8GCBXz88cdER0czePBgzGYz7777Lv7+/kXmZzsXe/OdMWMGDz30EHq9ng4dOnDnnXdy8uTJInWsf4NBgwbx2WefcfjwYWbMmIG3t3dBHQ8PD7p27Vrhv7+rUK8CENYhXH4uMTHwyiuF7ydNAsuWtKT8wiQ8wNM585RS1toBxAM97JS/CzxfzjYigT3lqdu9e3dpy759+6Q9UlNT7ZbXRa7WuTj67OoKq1evru0hOA01Fxfh229lvk4nzUXdF0scZpDztp2pUNPAFmnnN9Xl/ECEEDrgDkrRfwghwmze3oqmlFcoFIr6S1wcepMJcf31SLQVSXGs5c7Qf0DtmfHeKoQ4A/QBFgkhltpcHgCcllIeK3bPpzYmv28KIXYLIXYBsYD9fI8KhUJR31ixAiEled7eBQLD9tA5MQdUbVlhzQPmObgWD1xrp/wBm/OxzhpLVlYWHh4eZVmEKVwEKSXZ2dm1PQyFwuXZ8PvvJfQczv6Vc2UrrGonLCyMs2fPkpeXV6Q8OzsbDw/7AcnqGlfjXAwGA2FhYWXfoFAoqpV6LUACAgIICAgoUR4fH1+nLXxsUXNRKBTVhcsp0RUKhUJRN1ACRKFQKBSVQgkQhUKhUFQKIZ1o0uXqCCEuA3aCWpUgBEio5uHUFGouromai2ui5mKfCCllg+KF9UqAlBchxBYpZY+ya7o+ai6uiZqLa6LmUjHUFpZCoVAoKoUSIAqFQqGoFEqA2Gd2bQ/Aiai5uCZqLq6JmksFUDoQhUKhUFQKtQJRKBQKRaVQAkShUCgUlaLeCRAhxI1CiINCiCNCiGftXHcXQvxgub5JCBFpc+05S/lBIcSQGh24HSo7FyFEpBAiSwixw3LMqvHBF6MccxkghNgmhMgXQowqdu0+IcRhy3FfzY3aPlWci8nmc1lYc6O2Tznm8qQQYp8QYpcQYqUQIsLmWl37XEqbS137XB62pLzYIYRYJ4Rob3PNeb9j9rJMXa0HoAeOAs0BI7ATaF+sziRgluX8LuAHy3l7S313IMrSjr6OziWScmZxdKG5RAKdga+BUTblQcAxy2ug5TywLs7Fci29tj+PCs4lFvCynP/D5jtWFz8Xu3Opo5+Ln835LcAflnOn/o7VtxVIL+CIlPKYlDIXLevhiGJ1RgBfWc5/Bq4XWrKQEcBcKWWOlPI4cMTSXm1Rlbm4GmXORUp5Qkq5CzAXu3cIsFxKmSSlvAIsB26siUE7oCpzcTXKM5fVUspMy9uNQBPLeV38XBzNxdUoz1xSbd56U5ig0Km/Y/VNgIQDp23en7GU2a0jpcwHUoDgct5bk1RlLgBRQojtQog1Qojo6h5sGVTlb1sXP5fS8BBCbBFCbBRCjHTqyCpORecyAVhSyXurm6rMBerg5yKEeEQIcRR4E3i8IveWl3qdD6Qecx5oJqVMFEJ0B+YLIToUe2pR1A4RUsqzQojmwCohxG4p5dHaHlRZCCHGAD2AgbU9lqriYC517nORUn4IfCiEuAf4P8Dpeqj6tgI5CzS1ed/EUma3jhDCDfAHEst5b01S6blYlq+JAFLKrWj7oK2rfcSOqcrfti5+Lg6RUp61vB4D4oHazKBVrrkIIQYBU4BbpJQ5Fbm3BqnKXOrk52LDXGBkJe8tndpWCNXkgbbiOoamPLIqnzoUq/MIRRXPP1rOO1BU+XSM2lWiV2UuDaxjR1PEnQWCXHkuNnW/pKQS/TiaojbQcl5X5xIIuFvOQ4DDFFOOutpc0H5IjwKtipXXuc+llLnUxc+llc35cGCL5dypv2O18geozQMYChyyfFGmWMpeRnviAPAAfkJTLm0GmtvcO8Vy30Hgpro6F+B2YC+wA9gGDK8Dc+mJtl+bgbYi3Gtz7/2WOR4BxtfVuQB9gd2Wf/DdwIQ6MJcVwEXLd2kHsLAOfy5251JHP5f3bP7HV2MjYJz5O6ZCmSgUCoWiUtQ3HYhCoVAonIQSIAqFQqGoFEqAKBQKhaJSKAGiUCgUikqhBIhCoVAoKoUSIAqFkxFCfFk8yq5CcTWiBIhCoVAoKoUSIApFFRFC3GvJIbFTCPGNpXiAEGKDEOKYdTUihPCx5JnYZsnVMMJSHimE2C+E+EQIsVcIsUwI4Wm51tPS9g4hxHQhxB5Lud7y/m/L9YdqZfKKeo0SIApFFRBCdEALVHedlPIaYLLlUhjQH7gZeN1Slg3cKqXshpZ74m2b8PqtgA+llB2AZLRoAQBfAA9JKbsAJpuuJwApUsqeaJ7tDwohopw/Q4XCMSoar0JRNa4DfpJSJgBIKZMsMmG+lNIM7BNCNLLUFcCrQogBaLlAwgHrteNSyh2W861ApBAiAPCVUv5lKf8OTSABDAY62+ha/NGE0HHnT1GhsI8SIApF9ZBjc25dZcShBbLsLqXME0KcQItXVry+CfAso30BPCalXOqEsSoUlUJtYSkUVWMVMFoIEQwghAgqpa4/cMkiPGKBiFLqIqVMBtKEEL0tRXfZXF4K/EMIYbD021oI4V3JOSgUlUKtQBSKKiCl3CuEmAasEUKYgO2lVJ8D/CaE2A1sAQ6Uo4sJwCdCCDOwBi2rJMCnaLnVt1n0KJcpzPmgUNQIKhqvQuHCCCF8pJTplvNngTAp5eQyblMoagS1AlEoXJthQojn0P5XTwLjanc4CkUhagWiUCgUikqhlOgKhUKhqBRKgCgUCoWiUigBolAoFIpKoQSIQqFQKCqFEiAKhUKhqBT/D3hShlEsO1huAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" + "name": "stderr", + "output_type": "stream", + "text": [ + " 0%| | 0/213 [00:00" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "gens_to_plot = [1, 3, 10, 25, 100]\n", - "plot_gens(esp_results_dir, gens_to_plot, save_path=None)\n", - "plot_gens(torch_results_dir, gens_to_plot, save_path=None)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def get_gen_df(gen: int, results_dir: Path):\n", - " gen_filename = results_dir / f\"{gen}.csv\"\n", - " gen_df = pd.read_csv(gen_filename)\n", - " # Sort by first objective, maximize: lowest to highest, minimize: highest to lowest\n", - " gen_df = gen_df.sort_values(by='change', ascending=True)\n", - " gen_df[\"Name\"] = f\"Gen {gen}\"\n", - " return gen_df\n", - "\n", - "def get_all_gens_df(gens: list, results_dir: Path):\n", - " dfs = []\n", - " for gen in gens:\n", - " dfs.append(get_gen_df(gen, results_dir))\n", - " merged_df = pd.concat(dfs, ignore_index=True)\n", - " return merged_df" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_all_gens(gens: list, results_dir: Path, save_path=None):\n", - " all_gens_df = get_all_gens_df(gens, results_dir)\n", - " fig, ax = plt.subplots()\n", - "\n", - " all_gens_df.plot.scatter(x='change',\n", - " y='ELUC',\n", - " ax=ax,\n", - " label=\"All prescriptors evaluated\")\n", - " # Plot last gen's pareto front in red\n", - " \n", - " #get_pareto_df(dir, gens[-1]).plot.scatter(x='change', y='ELUC', c='red', ax=ax, label=\"Gen 100 Pareto Front\")\n", - " overall_pareto = get_overall_pareto_df(gens[-1], results_dir)\n", - " overall_pareto.plot.scatter(x='change', y='ELUC', c='red', ax=ax, label=\"Final Pareto Front\")\n", - " plt.grid()\n", - " #plt.title(\"All Generations All Prescriptor Performance\")\n", - " plt.legend(loc=\"upper left\")\n", - " if save_path:\n", - " plt.savefig(save_path, format=\"png\", dpi=300) \n", - " plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ + "name": "stdout", + "output_type": "stream", + "text": [ + "757/757 [==============================] - 3s 4ms/step\n" + ] + }, { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" + "name": "stderr", + "output_type": "stream", + "text": [ + " 99%|█████████▉| 211/213 [13:43<00:08, 4.10s/it]" + ] }, { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "all_gens = [a + 1 for a in range(100)]\n", - "plot_all_gens(all_gens, esp_results_dir, save_path=None)\n", - "plot_all_gens(all_gens, torch_results_dir, save_path=None)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "esp_all_pareto_df = get_overall_pareto_df(100, esp_results_dir)\n", - "torch_all_pareto_df = get_overall_pareto_df(100, torch_results_dir)\n", - "# TODO: This is temporary until we rerun the training with new id format\n", - "torch_all_pareto_df[\"id\"] = torch_all_pareto_df[\"gen\"].astype(str) + \"_\" + torch_all_pareto_df[\"id\"].astype(str)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Comparison with Heuristic" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [], - "source": [ - "nnp = NeuralNetPredictor()\n", - "nnp.load(\"predictors/neural_network/trained_models/no_overlap_nn\")\n", - "presc_config = None\n", - "with open(\"prescriptors/esp/unileaf_configs/config-loctime-crop-nosoft.json\") as f:\n", - " presc_config = json.load(f)\n", - "unileaf_prescriptor = UnileafPrescriptor(presc_config,\n", - " dataset.train_df.iloc[:1],\n", - " dataset.encoder,\n", - " [nnp])\n", - "\n", - "candidate_params = {\"in_size\": len(constants.CAO_MAPPING[\"context\"]), \"hidden_size\": 16, \"out_size\": len(constants.RECO_COLS)}\n", - "torch_prescriptor = TorchPrescriptor(100, \n", - " 100, \n", - " 0.2, \n", - " dataset.train_df.iloc[:1], \n", - " dataset.encoder, \n", - " nnp, \n", - " 4096, \n", - " candidate_params, \n", - " seed_dir=\"prescriptors/nsga2/seeds/test\")" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "metadata": {}, - "outputs": [], - "source": [ - "even_heuristic = EvenHeuristic(\"secdf\", nnp)\n", - "\n", - "linreg = LinearRegression()\n", - "linreg.fit(dataset.train_df[constants.DIFF_LAND_USE_COLS], dataset.train_df[\"ELUC\"])\n", - "coefs = linreg.coef_\n", - "coef_dict = dict(zip(constants.LAND_USE_COLS, coefs))\n", - "reco_coefs = []\n", - "for col in constants.RECO_COLS:\n", - " reco_coefs.append(coef_dict[col])\n", - "\n", - "perfect_heuristic = PerfectHeuristic(reco_coefs, nnp)" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "metadata": {}, - "outputs": [], - "source": [ - "test_df = dataset.test_df.sample(frac=0.01, random_state=100)\n", - "encoded_test_df = dataset.encoder.encode_as_df(test_df)\n", - "\n", - "context_df = test_df[constants.CAO_MAPPING[\"context\"]]\n", - "encoded_context_df = encoded_test_df[constants.CAO_MAPPING[\"context\"]]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Trained Prescriptors" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [], - "source": [ - "def evaluate_prescriptor(ids: list, context_df: pd.DataFrame, prescriptor: Prescriptor, results_dir: Path, verbose=False):\n", - " elucs = []\n", - " changes = []\n", - " iterator = tqdm(ids) if verbose else ids\n", - " for cand_id in iterator:\n", - " context_actions_df = prescriptor.prescribe_land_use(cand_id, results_dir, context_df)\n", - " eluc_df, change_df = prescriptor.predict_metrics(context_actions_df)\n", - " elucs.append(eluc_df[\"ELUC\"].mean())\n", - " changes.append(change_df[\"change\"].mean())\n", - " return elucs, changes" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [ + "name": "stdout", + "output_type": "stream", + "text": [ + "757/757 [==============================] - 3s 4ms/step\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|█████████▉| 212/213 [13:47<00:04, 4.07s/it]" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 3ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", - "757/757 [==============================] - 3s 4ms/step\n", "757/757 [==============================] - 3s 4ms/step\n" ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 213/213 [13:51<00:00, 3.90s/it]\n", + "100%|██████████| 397/397 [02:12<00:00, 2.99it/s]\n" + ] } ], "source": [ @@ -694,35 +3450,53 @@ "assert len(torch_all_pareto_df[\"id\"].unique()) == len(torch_all_pareto_df)\n", "\n", "esp_ids = esp_all_pareto_df[\"id\"].tolist()\n", - "esp_elucs, esp_changes = evaluate_prescriptor(esp_ids, context_df, unileaf_prescriptor, esp_results_dir)\n", + "esp_elucs = []\n", + "esp_changes = []\n", + "for id in tqdm(esp_ids):\n", + " eluc, change = evaluate_prescriptor(context_df, unileaf_prescriptor, cand_id=id, results_dir=esp_results_dir)\n", + " esp_elucs.append(eluc)\n", + " esp_changes.append(change)\n", "\n", "torch_ids = torch_all_pareto_df[\"id\"].tolist()\n", - "torch_elucs, torch_changes = evaluate_prescriptor(torch_ids, context_df, torch_prescriptor, torch_results_dir)" + "torch_elucs = []\n", + "torch_changes = []\n", + "for id in tqdm(torch_ids):\n", + " eluc, change = evaluate_prescriptor(context_df, torch_prescriptor, cand_id=id, results_dir=torch_results_dir)\n", + " torch_elucs.append(eluc)\n", + " torch_changes.append(change)" ] }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 213/213 [01:01<00:00, 3.46it/s]\n", - "100%|██████████| 213/213 [00:38<00:00, 5.52it/s]\n" + "100%|██████████| 213/213 [01:46<00:00, 2.00it/s]\n" ] } ], "source": [ "pcts = [i/len(esp_ids) for i in range(1, len(esp_ids) + 1)]\n", - "even_elucs, even_changes = evaluate_prescriptor(pcts, context_df, even_heuristic, None, True)\n", - "perfect_elucs, perfect_changes = evaluate_prescriptor(pcts, context_df, perfect_heuristic, None, True)" + "even_elucs = []\n", + "even_changes = []\n", + "perfect_elucs = []\n", + "perfect_changes = []\n", + "for pct in tqdm(pcts):\n", + " even_eluc, even_change = evaluate_prescriptor(context_df, even_heuristic, pct=pct)\n", + " even_elucs.append(even_eluc)\n", + " even_changes.append(even_change)\n", + " perfect_eluc, perfect_change = evaluate_prescriptor(context_df, perfect_heuristic, pct=pct)\n", + " perfect_elucs.append(perfect_eluc)\n", + " perfect_changes.append(perfect_change)" ] }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -734,7 +3508,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 42, "metadata": {}, "outputs": [], "source": [ @@ -744,7 +3518,7 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ @@ -762,12 +3536,12 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 44, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEGCAYAAACO8lkDAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAABDg0lEQVR4nO3deXxTVfr48c/pTqUiFNzgS1sdEaGbWBDFBaksM/DFAWQAi4qMIjDjoL+vuDHu4vBTZ1xG2fSHoERF0XFURkFQRMGtMAiolcUWBP2OpbK0lLZpe35/3CRNk3uzNW3S9nm/XrXNzc3NIbZ5cs5zznOU1hohhBDCXUykGyCEECL6SHAQQgjhRYKDEEIILxIchBBCeJHgIIQQwktcpBsQDl27dtXp6emRboYQQrQqmzdvPqi17mZ2X5sIDunp6RQWFka6GUII0aoopfZa3SfDSkIIIbxIcBBCCOFFgoMQQggvbSLnIIQInt1uZ//+/VRVVUW6KaKZJSUl0aNHD+Lj4wN+jAQHIdqp/fv3k5KSQnp6OkqpSDdHNBOtNWVlZezfv5+MjIyAHxe1w0pKqRFKqe+UUruVUnc0+xMW2+DNdHgpxvhebGv2pxQikqqqqkhNTZXA0MYppUhNTQ26hxiVPQelVCzwDDAU2A98qZR6S2v9TbM8YbENNk0FVWPcrtxr3AbIKGiWpxQiGkhgaB9C+f8crT2HAcBurfX3Wusa4BXginA/iW27jfQn0ildO7khMDipGtg0K9xPKYQQrUK0BofuwA9ut/c7jrkopaYppQqVUoWlpaVBP4Ftu41nvn2Ga8dcS9dkq7PKgr6uECJwsbGx5Obmur7mzZvXbM+1fv16Ro0a1ejYlClTWLlyZViu/+OPP3LllVda3n/48GHmz58f8PmRFq3BwS+t9WKtdZ7WOq9bN9PV3z698P0LjBk8hi4ndoGDFidZHbfZID0dYmKM7zbJTwgRig4dOrB161bX1x13NH96sTnU1tZy+umn+ww0nsHB3/mRFq3B4QDwX263eziOhc3A3IEkxCcAcHxtMlR7nFANfJDq/UCbDaZNg717QWvj+7RpEiBEm+ccho25P4b0J9KxbW+e3/n33nuP8ePHu267f+Jfs2YNF1xwAf369WP8+PFUVFQARgmde++9l379+pGVlUVRUVHQz7t582YuvfRSzjvvPIYPH85PP/0EwODBg13leQ4ePIizjtvSpUsZPXo0Q4YMIT8/n5KSEjIzMwH4+uuvGTBgALm5uWRnZ7Nr1y7uuOMO9uzZQ25uLrNnz250fl1dHbfeeiuZmZlkZ2fz97//PbQXL4yiNTh8CZyllMpQSiUAE4G3wvkEnVM6u37+6L/HUvtCDJQC9UAp1CyFTy74nfcD58yBysrGxyorjeNCtFG27TamvT2NvUf2otHsPbKXaW9Pa3KAOH78eKNhpRUrVnD55Zfz+eefc+zYMQBWrFjBxIkTOXjwIA899BBr165ly5Yt5OXl8be//c11ra5du7JlyxZmzJjBY489Zvp8H3/8caPne+st423Fbrdz0003sXLlSjZv3szUqVOZE8Df9JYtW1i5ciUfffRRo+MLFy5k1qxZbN26lcLCQnr06MG8efM488wz2bp1K48++mij8xcvXkxJSQlbt25l27ZtFBREfiJMVM5W0lrXKqX+CKwGYoElWuuvw/kcsXWx1MfVA7BzfB4Agx5cRcqBQ5R378zHf/41cztv5Q/bbRRkuf2P2mtRp8rquBBtwJx1c6i0N/5QVGmvZM66OY3/PoLkHFbyNGLECN5++22uvPJKVq1axSOPPMJHH33EN998w6BBgwCoqanhggsucD1m7NixAJx33nm88cYbps938cUX884777huT5kyBYDvvvuOHTt2MHToUMD4JH/aaaf5bf/QoUPp0qWL1/ELLriAuXPnsn//fsaOHctZZ53l8zpr165l+vTpxMUZb8lm12xpURkcALTW/wL+1VzXH3riUFZXrHb1nXaOz3MFCacx9lyeWPcEQMMfQGws1NV5XzA21vrJbDajZ7FvH/TsCXPnQhR8MhAiUPuO7AvqeFNNnDiRp59+mi5dupCXl0dKSgpaa4YOHcrLL79s+pjExETASHLX1tYG9Xxaa/r27cunn37qdV9cXBz19cYHSc+1AieccILp9a666irOP/98Vq1axW9+8xsWLVrEGWecEVSbIi1ah5WaXe/E3gzvOBy09TkJ8QlMGjaJx3c8jrpfkf5EOtosMEBDwPBMVs+cKTkK0er17NQzqONNdemll7JlyxaeffZZJk6cCMDAgQPZuHEju3fvBuDYsWPs3LkzLM939tlnU1pa6goOdrudr782BivS09PZvHkzQMAJ5O+//54zzjiDP/3pT1xxxRVs27aNlJQUysvLTc8fOnQoixYtcgW1X375pan/pCZrt8EBHAHihOFGnsFCbEwsE/In0K9XP/Ye2csPJ1ksJklLM09WL1ggOQrR6s3Nn0tyfOM538nxyczNn9uk63rmHJyzlWJjYxk1ahTvvvuuKxndrVs3li5dyqRJk8jOzuaCCy4IKfFsJiEhgZUrV3L77beTk5NDbm4umzZtAuDWW29lwYIFnHvuuRw8aDWFsbFXX32VzMxMcnNz2bFjB9dccw2pqakMGjSIzMxMZs+e3ej866+/np49e5KdnU1OTg4vvfRSWP5dTaG09vHRuZXIy8vTTdnsp6i6iNXHVoOPRYRaaw6VH6L2kWXc9exeTrC73ZmcDIsXG2/4geYelIJ6H1FJiGb27bffcs455wR8vm27jTnr5rDvyD56durJ3Py5Tco3iJZl9v9bKbVZa51ndn7U5hxaUu/E3gCNchCelFJ0ObELNff+gYd5hhtse+l5BCpPS6Xjo08aOYSrrw78SXs2T3dciOZSkFUgwaAdadfDSu4CyUGAkYdIfeBPjFvQj9j74JQ/HseW7bgz0Df85GQjKS2EEFFKgoObQHIQYOQhJuZPpF+vflTaK7n2H9ca873nzjXe+H1JSzOGoGS2khAiiklw8ODsQaTEpPg8LyE+gYJhBfTr1Y86XWcsCMrGeONPNVlZnZwMy5dDSYkEBiFE1JPgYKJ3Ym+mdprK8OThxPlIy5j2ILKBgweNQJCWZiSepbcghGhlJDj40DuxN/nJ+Sgf05g8exCT35hM10e6GkFi7lwjD7FvnzGTSdY2CCFaCQkOfvRO7M2w5GEB9yAAyo6XsfbB66i9fmrjNQ+TJ0PXrhIkhHBwluzOzMxk/PjxVHquCfJj9uzZ9O3b12vdQCAefvhhy/vS09MbrWkwK/fdFNdffz3ffGO9d9nSpUv58ccfAz6/OUhwCECwPQiAe9fYiauq8T6xrMx6hbT76uquXY0vKQsu2jBnbaUdO3aQkJDAwoULA3qccyXx4sWL2bZtm1chu0D4Cg7Nqa6ujueee44+ffpYnuMZHPyd3xwkOAQo2B5EzyM+Lma2QtpzdXVZmfElJTdElCiqLmLJkSU8eehJlhxZQlF1eFYnO1188cXs3r2bY8eOMXXqVAYMGMC5557LP//5T8C7RPbo0aOpqKjgvPPOY8WKFZSWljJu3Dj69+9P//792bhxIwAVFRVcd911ZGVlkZ2dzeuvv84dd9zhWp0dbAVUX+374x//6Dpv1KhRrF+/HoCOHTvyP//zP+Tk5PDpp5+6yoDX1dUxZcoUMjMzycrK4vHHH2flypUUFhZSUFBAbm4ux48fb1Q2/L333qNfv37k5OSQn5/f1JfdkiyCC4JzsdyayjVoiwURzh7E/3bdzukH7abnAEYewp1ZKXB3zoAiSW0RAUXVRayrXEctxif28vpy1lWuAxr+LpqitraWd999lxEjRjB37lyGDBnCkiVLOHz4MAMGDODyyy8HjBLZ27Ztc1Ut7dixo6uq61VXXcUtt9zCRRddxL59+xg+fDjffvstDz74IJ06dWL79u0AHDp0iHHjxvH000+bVoR1uuyyy4h1FNSsqKigd2/j3+mrfVaOHTvG+eefz1//+tdGx7du3cqBAwfYsWMHYGwIdNJJJ/H000/z2GOPkZfXePFyaWkpN9xwAxs2bCAjI6NZazBJcAiS8w/B/Q/FU2xMLJsfGEfnm1fQocZiVZ3ngjnPYGEmkHOEaAabqjZ5/b7XUsumqk1NCg7OT+9g9Bx+//vfc+GFF/LWW2+59mSoqqpin+N336pENhhlr93H5Y8ePUpFRQVr167llVdecR3v3Lmz2cO9fPjhh3Tt2hUwcg7O9qxZs8ayfVZiY2MZN26c1/EzzjiD77//nptuuomRI0cybNgwn9f57LPPuOSSS8jIyACat7S3BIcQBNKD+H7iQD6IieHCW1/hpIr6RtmKY/Hw7+m/4SL3B3TpYgwj+SIlN0SElNebVxO1Oh4os/0ctNa8/vrrnH322Y2Of/7555YlsgHq6+v57LPPSEpKalKb/LFq3+bNm12lvaFxee+kpCRXL8Rd586d+eqrr1i9ejULFy7k1VdfZcmSJc3X+CBIziFEgeQgdv9uAM/tmcefZ6ZR0slYeF3SCW74bxhcs7hhFy2bDSxK+bpIyQ0RQVaLQv0tFg3F8OHD+fvf/46zKOi///3vgB43bNiwRttrOoPO0KFDeeaZZ1zHDx06BEB8fDx2u4+h3yDbl56eztatW6mvr+eHH37giy++8HutgwcPUl9fz7hx43jooYfYsmULgGV574EDB7JhwwaKi4uB5i3tLcGhCQKdxdTtwZt5/qt76P9SPzJugZezabQmomL2LKgxmdkUEyOL6ERUuDDpQq8PQnHEcWHShWF/rrvvvhu73U52djZ9+/bl7rvvDuhxTz31FIWFhWRnZ9OnTx/XzKc///nPHDp0iMzMTHJycvjwww8BmDZtGtnZ2UEnpK3aN2jQIDIyMujTpw9/+tOf6Nevn99rHThwgMGDB5Obm8vkyZP5y1/+Ahg71E2fPt2VkHbq1q0bixcvZuzYseTk5DBhwoSg2h4MKdkdBp7JOis19hpeWfcKW3ZuaXS87j6LKC1lvUUzCrZkd1F1EZuqNlFeX05KTAoXJl0YlmS0aBlSsjsCAslBQMNMJqBRgNjXCdLNpr5KjkFEkd6JvSUYtCMyrBQmgeQgwJjJdPXwq3nohodcC+buyjeS1I1IjkEIEUHScwgj56cqZ9fbilKKjh06MjHf2Bv3ZYxexMProOcR2H+SYt/t13KR5BiEEBEiPYcwC7SiKzQuufFyNmTcArH3QdrNuvFsJif38hpSUkMI0YwkODSTQGYygXfRPqdGFV6327zLawRSUqPYBm+mw0sxxvdiCSZCiMBIcGhGgeYhPIv2uSs7Xsa0t6cZ0109y2uY1WhyKrbBF9Ogci+gje9fTJMAIYQIiASHZubsQSSS6PM8qx4EQKW9kuSfLFZPWy3b/2oO1HkEk7pK47gQUcJZstv5NW/ePADeeecdzj33XHJycujTpw+LFi0C4L777qN79+6uMt9vvfWW1zWXLl1Kt27dyM3NpU+fPjz77LMt9u+55557WLt2rc9z3nzzzRYvvx0KSUi3AOcUwKLqooCK9gFeayGCnu5aaRE0rI4LEQFm5TPsdjvTpk3jiy++oEePHlRXV1NSUuK6/5ZbbuHWW2/l22+/5eKLL+bnn38mJqbx59wJEybw9NNP8/PPP9O3b19Gjx7NKaec4rq/traWuLjwvv3V1dXxwAMP+D3vzTffZNSoUUGV4G6O9vojPYcWFMrGQU5m011rkxKsp7smWwQNq+NC+NNCEyLKy8upra0l1bEXe2JiolcdI4BzzjmHuLi4RpvyeDr55JM588wz2bt3r2vV8fnnn89tt93Gnj17GDFiBOeddx4XX3wxRUVGCfLXXnvNtZr6kksuAYw3/ltvvZXMzEyys7NdZTrS09O5/fbb6devH6+99hpTpkxh5cqVrvtuu+02srKyGDBgALt372bTpk289dZbzJ49m9zcXPbs2cPWrVsZOHAg2dnZjBkzxlXeY/Dgwdx8883k5eXx5JNPmrarOUnPoYUFU/YbGnoQL2cb9zmnu+7rBPcP01yeDaYTXnPmGjkG96Gl2GTjuBDBck6IcOa9nBMioEllXdyrsgLceeedTJgwgdGjR5OWlkZ+fj6jRo1i0qRJXr2Dzz//nJiYGLp162Z5/e+//57vv/+eX/3qVwDs37+fTZs2ERsbS35+PgsXLuSss87i888/Z+bMmXzwwQc88MADrF69mu7du3P48GHA2FSopKSErVu3EhcX16imUWpqqqsm0nvvvdfo+Z2lwl944QVuvvlm3nnnHUaPHs2oUaO48sorAVzB5tJLL+Wee+7h/vvv54knngCgpqbGtY9DVlaWV7uakwSHCAi07LdzHYR7gHAGCYOdF/9xLQAFWR5/oBmO21/NMYaSknsagSFD1k6IEJjtNxKGPUbMhpXA2Pls+/btrF27lscee4z333+fpUuXAvD444+zfPlyUlJSWLFiBUp5zwhcsWIFn3zyCYmJiSxatMhV2nr8+PHExsZSUVHBpk2bGD9+vOsx1dXVgFEjacqUKfzud79j7NixgFEOfPr06a6hHfdS2b7qG02aNMn1/ZZbbvG6/8iRIxw+fJhLL70UgGuvvbZRm9yvbdau5iTBIUJC7UE4Tdrm7EXUse9vk5k24kYunbOocZDIKJBgIMLDauJDM+4xkpWVRVZWFldffTUZGRmu4ODMOfjizDl4cpb8rq+v56STTjINTAsXLuTzzz9n1apVnHfeeWzevNnnc/kqI+4euMyCmD/u1zZrl3PorTlIziGCAs1BeJbbmLQNlpRC+v0Qs9z4/tSPx1h1n9u6CCHCyWriQzPU/6qoqHBtrwlG6e20tLSwPseJJ55IRkYGr732GmDs0fDVV18BsGfPHs4//3weeOABunXrxg8//MDQoUNZtGiRa+/qQEtlr1ixwvX9ggsuABqX4+7UqROdO3fm448/BuDFF1909SI8mbWrOUVdz0EpdR9wA1DqOHSX1vpfkWtR8wqkB+FZbuPJj7eQdB24Zsd2g6Tr4EkbnOxYFwEmQ01ChGru3MY5BwhL/S/PnMOIESOYM2cOjzzyCDfeeCMdOnTghBNOcPUawslmszFjxgweeugh7HY7EydOJCcnh9mzZ7Nr1y601uTn55OTk0NmZiY7d+4kOzub+Ph4brjhhkb7RVs5dOgQ2dnZJCYm8vLLLwMwceJEbrjhBp566ilWrlzJsmXLmD59OpWVlZxxxhk8//zzptcya1dzirqS3Y7gUKG1fizQx0S6ZHc4BFr2u66+jluW/w/KJAenSyHmsPFzrIpl2ZhlEiCEpWBLdmOzGTmGffuMHsPcubLHiA/p6ekUFha6thqNtGBLdsuwUpQIptwGVr9rbse9ym8I0VQFBVBSYuwxUlIigaGNi9bg8Eel1Dal1BKllOlu4EqpaUqpQqVUYWlpqdkprU6g5TaqtHkCTJdB/X0NXz//Xxj2eZkECSEioKSkJGp6DaGISHBQSq1VSu0w+boCWACcCeQCPwF/NbuG1nqx1jpPa53na55zaxNIuY31uWOo1Y03K9fVELMCFA1f3Y7Dkjfh7+9A4cNlTMqeTMXpXaWaqxDCr4gkpLXWlwdynlLqWeCdZm5O1PFXbmNnd2OIcNDOVaRUHUIfiiHmpXrY5H2tpHqYWdjwKaDjT2XUXj/V+B8vwwJCCAvROFvpNK31T46bY4AdkWxPJPlaLLeze54rSPypy80+r+PZPYyrquGHP17DhmyZ0SSEMBeNOYdHlFLblVLbgMsA72WF7Yi/RHWv1wrxk8M21f1wveQihBCWoi44aK2v1lpnaa2ztdaj3XoR7ZavRPWgB1ehQpyNPGmbsV/E1W9czcxVM5vYSiGCU1ZW5irVfeqpp7pKcefm5lJTUxP09e677z4ee8z/DPj09HSysrLIzs5m2LBh/O///m8ozQ/ajz/+6KqnZOXw4cPMnz+/RdrjT9QFB2HOKlGdcuCQ6fna8WUlBqP8hnGuZmHhQulBiBaVmprK1q1b2bp1K9OnT+eWW25x3U5ISLB8XF1dXZOf+8MPP2Tbtm3k5eXx8MMPN7pPa019fX2Tn8NdbW0tp59+uqtiq5VQgoNz1Xa4SXBoRXon9mZ65+kMTx7uGmYq724605fyHp0p72F+n1NPt/0hNJpr/3GtBAhhrQW2nV23bh3nnnsuWVlZTJ061VUMz7M09nvvvUe/fv3IyckhPz/f9fhvvvmGwYMHc8YZZ/DUU0/5fb5LLrmE3bt3U1JSwtlnn80111xDZmYmP/zwA48++ij9+/cnOzube++9F4Bjx44xcuRI16ppZ3mML7/8kgsvvJCcnBwGDBhAeXk5S5cuZfTo0QwZMoT8/HxKSkrIzMwEjA2JrrjiCgYPHsxZZ53F/fffD8Add9zBnj17yM3NZfbs2WitmT17NpmZmWRlZbmeb/369Vx88cWMHj2aPn36WLarKaIuIS38c09Ub7x7JJffvIL443bX/fYO8Wy8eySA133uyjpA8eNGkCjrAFBH6r2T+eGka9h7+41cdEd0dG9FFHBuO+ssAe/cdhbCVtyxqqqKKVOmsG7dOnr16sU111zDggULuPnmm4GG0tilpaX069ePDRs2kJGR0ajOUVFRER9++CHl5eWcffbZzJgxg/j4eItnNHacy8rKAmDXrl0sW7aMgQMHsmbNGnbt2sUXX3yB1prRo0ezYcMGSktLOf3001m1ahVgVFWtqalhwoQJrFixgv79+3P06FE6dOgAwJYtW9i2bRtdunRptGERwBdffMGOHTtITk6mf//+jBw5knnz5rFjxw5XQcDXX3+drVu38tVXX3Hw4EH69+/v2sthy5Yt7Nixg4yMDF5//XWvdjWV9BxaKecw067x/Vn7xASO9uiMVnC0R2fWPjGBnePz2Dk+j7VPTOB4lxO8hpiqYyGl2thdLgZjTUS348bP/3W4nnPvWcC0iR2lJyEMLbDtbF1dHRkZGfTq1Qswyldv2LDBdb+zfPVnn33GJZdcQkZGBtC4fPbIkSNJTEyka9eunHzyyfznP/8xfa7LLruM3Nxcjh49yp133glAWloaAwcOBGDNmjWsWbOGc889l379+lFUVMSuXbvIysri/fff5/bbb+fjjz+mU6dOfPfdd5x22mn0798fMIr6OUt7Dx06tFH73A0dOpTU1FQ6dOjA2LFj+eSTT7zO+eSTT5g0aRKxsbGccsopXHrppXz55ZcADBgwwPUamLWrqaTn0Iq5ehDjY9k53rQ8iitI9HqtkEEPriLlwGF+6XoC9RUVdDtufe0T7HDXe8fIOGcys96dxZO/flKmvbZnUbDtrK/S2E6JiQ05udjYWMvx+A8//LDR6uXDhw83ur7WmjvvvJMbb7zR67FbtmzhX//6F3/+85/Jz89nzJgxIbXZs4R3sCW93a/dq1cvr3bdc889QV3Pk/QcWrlAVlSDESSe33Yvfy97gtIfvqRrlf9rO3MSZcelBEe71wLbzsbGxlJSUsLu3bsB6/LVAwcOZMOGDRQXFwOBl88OxvDhw1myZAkVFRUAHDhwgJ9//pkff/yR5ORkJk+ezOzZs9myZQtnn302P/30k+sTvXObU3/ef/99fvnlF44fP86bb77JoEGDGpXzBrj44otZsWIFdXV1lJaWsmHDBgYMGOB1LbN2NZX0HNoAfyuq3Wk0qytX0717F1L2+/6j2ufRM3UGiWbpSRTbZNe6aNYC284mJSXx/PPPM378eGpra+nfvz/Tp0/3Oq9bt24sXryYsWPHUl9fz8knn8z7778ftnYADBs2jG+//da1B0PHjh1Zvnw5u3fvZvbs2cTExBAfH8+CBQtISEhgxYoV3HTTTRw/fpwOHTqwdu1av88xYMAAxo0bx/79+5k8eTJ5eY7KB4MGkZmZya9//WseeeQRPv30U3JyclBK8cgjj3Dqqae69rt22r59u1e7mirqSnaHoi2U7A6XQEt/93qtkBE3LrdcP6eBgrGe25I2SI5PZvF/Lw5PgPBMdgKg4FfTYYAkxZtL0CW7JYCHzdKlSyksLDTdra65SMnudi6YYabjnZMt7z/YwTowAFTaK8M39dUs2YmG3QubZbqkCFFGAfy2BK6qN75LYGjTJDi0QWbrIcx8NG8stfHevwLVsTDr1/6fJ2x7RlgmNXVYZ8MIES2mTJnSor2GUEhwaMP87Q+xc3we7z99FZWdkxtWVKemkrhsOSPvW05qh8A2L29yCQ5fSc0WnA3THrWFYWXhXyj/nyXn0A4UVRexvnI91RirTRumtR6ivHtnNt49kp3j81AohiUPc02RBbBttzHr3VmUHS8L6LlSO6QGn6wutsGnV2Na8CM5zRjCEGFXXFxMSkoKqampQU+jFK2H1pqysjLKy8td6yKcfOUcJDi0I0XVRZQse5j8m1/xWlHtXDgHkKSSuLTDpV5B4tp/XEudDqyuTdBB4ouZRo7BPUDEJsOAxTK23Uzsdjv79++nqiqAec2iVUtKSqJHjx5eq8UlOAgXe1p34vf96HX8aI/OPL/tXtftOOLIT873ChDT3p5Gpd0zeWwtqCAhs2GEaFESHESDmBgw+X+uMYr1OYeYgLAMM0GYp70KIcJGprKKBj3Nk78KOHH/IS6/eYWxgRANC+YWHV5EUbWx6KYgq4CDtx1kRt4MnzOhnCZ1hK+7VzJp22QqXusqU1OFaCUkOLQ3c+dCsvX6hvjjdgY9uKrRsSpdxbrKda4AATB/5HxeHPuizxlNkzrCs6dAejzEKOhoL6Ny42Q+2SAbCwkR7SQ4tDcFBbB4MaSlWZ5itoFQLbWsqVzTKEA4exHLx5pPe324K5zg8RuWHAM9ihdInSYhopwEh/aooABKSiwDhNUGQmbDTGAdJHpaVO7qGSfbkwoR7SQ4tGcmQ0zuGwVZqdJVfoNErIpln0V5J+dxjWZBofQihIhGEhzaM/chJqUgLY2fF8xl7/hBAT3cLBcBRpBYNmYZ9x+O55jHVrzH6uGug42PSUlwIaKPTGUVpgIp/+1kNuUVjGmvH62/kbtOPEbPOKPHcNdBeLnC9/VCWmUthAiaTGUVQfNXl8mdMxfxQcUHjY4XZBWw+KYKNvZbzskHUsko8R8YwOhJTHt7mvQihIggCQ7CUqDlv52227d7DTFB8GsjIMwlwYUQQZPgIHxyL/8dSJDwnO7qLpC1Ee7qdJ3MaBIiQiTnIIISaC7CrHifuyZVe5UaTEKEhdRWEmFVVF3E6srVAZ0b7iBxQ5cTmN/VTpyuaTgo1VuFCIkkpEVY9U7sTVZ8VkDnWk13dfJcG+HPXSceaxwYwNhiVHaMEyKsJDiIkAzpOMTvNqRgbCx0dfbdnN3hHOxp3cHmlmAutsGb6fBSDAV75rB+8DS/17NadS07xgkRXhIcRMj8TXft9Vohl9+8ghP3H0JpiN/3I7XXXUtt184wSMFHV0PlXkBD5V4u+mkZz2UP8RkgrFZdV8R3CcO/SAjhFJHgoJQar5T6WilVr5TK87jvTqXUbqXUd0qp4ZFonwicr+mugx5c1WjHOYA4ex1xZYfhd0CCR76rrpKparfPGU13HcR01fW0fWWywlqIMIpUz2EHMBbY4H5QKdUHmAj0BUYA85UKYCBaRJTVdFez6q4uXS2OV+7zWe315Qq44T9QYod6bXy/4T/GcVk8J0T4RCQ4aK2/1Vp/Z3LXFcArWutqrXUxsBsY0LKtE6FyDxIKZVndFYCDFseTGzYjsgoSL1dARgnE7sZr1bUsnhMiPKIt59Ad+MHt9n7HMdGKOHMRn909GnuHePOTXgWqPY7FJhtrFjwEu8K6TtdJIT8hmqjZgoNSaq1SaofJ1xVhuv40pVShUqqwtLQ0HJcUYdQ7sTc9r72Dj56YzNEendFAvaJh6dwm4DmgFKgHfRC2H8uj6PTzLK8Z7Apr2TNCiNBFdBGcUmo9cKvWutBx+04ArfVfHLdXA/dprT/1dR1ZBBfdDix7lJNn/Jn44zU+z6vsnMzzex4hPznfctGcU5NWWAshgNa1CO4tYKJSKlEplQGcBXwR4TaJJup+7zN+AwNAh0OVnPHaZz7rMzk5h5o+vmwGJelQ9ysoTjf2rTYje0YIEZxITWUdo5TaD1wArHL0ENBaf40xGv0N8B7wB611XSTaKMJoX2AL1BTG9Fer7Ui9FNu46KdlpMVDjIL0eHj2FOsAATLUJESgpLaSaH7p6bB3b0CnagVPlT3R6FhWfBZDOg7xPvnNdMciusZK7MYsJn9kqEm0d61pWEm0RSZ7VVsxm/663b7dvBdhUTLDssSGBxlqEsKa9BxEy7DZYM4cY4ipSxeoqoJjxxqdYu8Qz9onJgDG8FLK/kPo2BhUXT3lPTrz2d2j6XntHQ3JaoueQ0V8KunFBJysdpKehGhvpOcgIq+gAEpKoL4eDh6EigpYvhzS0tBKcbRHZ1dgcNVjAmLq6lHAifsPcdnNL1Gy7OGGHkTOXGNthLvYZDrmPWm5wtoXyUcI0UB6DiIqFFUXsb5yPVdl38WJ+63LbtTHxrB6/lXs+91Fxj4RP272u/HPzFUzWVi40O8GRe6kFyHaA9nsR7QaOiYG5ed30jn8tHN8nnWy2kOw6yIAkuOTWfzfiyVAiDYr5GElpdSjSqkbTY7fqJSaF64GCuGkevb0e078cTuDHlwF+EhWe/BVzM+K1GkS7Zm/nMMQYLHJ8WeBUeFvjmiXbDZjumtMjJGLSEjw+xD3iq/+dptzF2yQqNN1kocQ7ZK/4JCoTcadtNb1EEAFNCH8sdlg2jRjHYTWUFZmfI/x/avpOeW1ltqAVlY7BVPMT6NZULhApryKdsVfcDiulDrL86Dj2PHmaZJoV+bMgcrKxsfsdmNWkwUNbLx7pMnxAFdWuwmmmJ+sixDtib/gcA/wrlJqilIqy/F1HbDKcZ8QTRNgaQ13VV1OYOd40xyacb+uCipIuA81xQawt5RMeRXtgc/goLV+F/gtcBmw1PF1GTBOa/2vZm6baA+sEtCpqaa5h/r4ODb+5XcBXdoZJD6o+CCg8wuyClg2ZllAe0bIUJNo62Qqq4gsZ87BfWgpORkWO+ZBzJpl5CHACBhPPgkFBRRVF7Gmck3AaxeSVJKxLsJPKXCQdRGi/Qh5nYNS6m1o9BeiMTZ4/FBrvTysrWwCCQ6t3MyZRjCoq4PYWCNYzJ/v92FF1UWsq1xHLbUBPU0ccQHtFQGhrYtQKKbnTWf+SP9tFyIaNCU4XGpyuAswGdiltb4jPE1sGgkOrZivnkOB/0/hzpXV1V57jppTKIYlDwsoQEBoQUJ6EaK1CPsKaaVULLBZa53bxLaFhQSHVsyqnHdamlGLKUDBBolAV1Y7yVCTaIvCXnhPNuARYWM1WynQWUyOBXS9O/Rh+rnzuPwf/wnoYYGurHYKdv9qkFlNonXzN6zUxeRwZ+Aa4Fda66j4SCQ9h1asKT0HiyGpA/Pv4+3RKQH3IoJJVoMMNYm2oyk5h2KMJLRzbp8zIb0eeFBrXR7epoZGgkMrFmrOwWaDa681ktieHIGlOWc0QfBDTZKwFtGmWaqyKqVWaK0nNKllYSLBoZVz3wioZ09j5zh/gcEzoLhTyrXCuqi6iNWVq4NqTjD5COlFiNasuYLDPq21/xKaLUCCQzvjb09qjyGpDyo+YLt9e1BPMTx5eMA9CJAgIVon2QlOtC2+ktUJCUZl15gYI4jYbAzpOIThycNJJDHgpwimiB8EV8jPSRLWIpr5yzn0s7oLeEdrfVqztCpI0nNoZ6x6DjExxiI6u73hmEf+4sCuRzlx+zw6Vv1CeVJnNvYayc7u1nWags1DgPQiROvRlIT0h74urLW+rIltCwsJDu2MWc4hPt5ITptVc3UOMxXb4ItpUNfwOHtMPGszJ/gMEBD8ugiQtREi+sk2oaLtcU9id+kC5eVQU2N+rjNB/WY6VHr3OI4mdeb5y+71+5Qt1YuQWU2ipTRlm9Db3H4e73Hfw+FpnhAhKCgwegP19dCxo3VggIbKr5XmuYqUqsMB5QmCLQUOoW1PKhVfRTTwl5Ce6PbznR73jQhzW4QIja8EdXKyMTUWINl8cp1K7smw5GHEERfQ0wVbChwkYS1aH3/BQVn8bHZbiMiw2hMiNrah9Hd6Ojy6F2o8fm1jkyFnLr0Te5OfnB/UjKZgS3BA8GU4pBchIsVfcPAs1211nxCRM3eu0UPwdNJJsHFjwx7Vm4BnNRxUxm9vchoMWAwZRvK3d2JvpneeTlZ8VkBP2+tAIZM+uJOzXz+H8jdSObDr0YAeF8pQk/QiREvzN1upDjiG0UvoADineSggSWsd3+wtDIAkpAUzZ8LCheD5+6yU9zHwW7vJX5XXXgcKuXzHCuLrG6bN2mPi2Zl7K317B5eOC3ZWk8xoEuEis5VE2+avnIYZtxIbvrgHiV4HChm0cxUpVYfQxBCD9+OPJnXm5SF/afZZTTKjSYSDBAfRtvkrp2EmyP0ivi66i15bH2vUUzCjgad+/QQQ2tRX6UWIlhR15TOUUuOVUl8rpeqVUnlux9OVUseVUlsdXwsj0T7RygS694NTfHzDDKYA9S16yW9gAChP6uz62XRWU7HNWG/xUozxvbhxkjnYhHXZ8TImvzFZEtYi7CJVW2kHMBbYYHLfHq11ruNregu3S7RGVrOVrKgQJtpZrJFwZ4+JZ2OvkV7Ht9u3GzOanCu0K/cC2vj+xTSvACHTXkU0iEhw0Fp/q7X+LhLPLdogq9lKVmpqjNXVwbBYI1FPDBoj1+CrDMeayjXYt97WqHQHYNz+yrwtMu1VRFI0VmXNUEr9Wyn1kVLqYquTlFLTlFKFSqnC0tLSlmyfiDYFBcZ6hrQ0o1eQlgapft5Q9+41chXO6q0zZza+bfN4c82Za6yJcBebzE/957Ho1wt4/rJ7XYGh14FCrvvwfv707s1c9+H99DpQiEYTd/xH87b46JVIL0JESrMlpJVSa4FTTe6ao7X+p+Oc9cCtWutCx+1EoKPWukwpdR7wJtBXa33U13NJQlp4CWRDIF+/+2a70RXbjE/5lfuMnkTOXNcaCeesprQDG02nuK7NnMCgnas4seqQyXOlwW9L/P+TpNqrCLOona3kGRyCvd9JgoMwZbPBrFlQ5vFm6i8wOKWmwsGD/s9zCxr1ShGjzae4buw10itw1McmETPgOVeQCYRMexXhEnWzlawopboppWIdP58BnAV8H9lWiVaroMB4c1++vPGQU6AfiMrKvIeXPHkkmc0CA0BK1SF2ds9jbeYEjiZ1duUpVve9kg+6BbctSrBDTZKLEKGI1FTWMUqp/cAFwCqllHOT30uAbUqprcBKYLrW+pdItFG0Ie4VXEtKjAARKH+J66/meCeZTbhPcfUUSo0mCG3aq+QiRKBkEZxof6xKbZjxt5L6pRj8lRlz5hwAy3yEM5kdysI5kMVzIjStZlhJiGZns8GyZY0Dg1LG3tNm/K2hsJjiiooFFPYOp/NR5mR2ds9j0M5VXgvp4uvtDNq5ynU7lHLgIL0IEX4SHET7MmeO9wwmrSElxXuthPteEFYsprgycBlcVU/8mANcnrmE4cnDSTGbqQSmx0MZago1F6HuV5KPEF4kOIj2xarUxi+/eK+V8JzKaiajwCj7nZwGKK8y4E69E3ujks1zHVb5iJbqRYCU4RDeJDiI9sVqmKhnz4bE9YsvGseuvtp8QZynjAJjncJV9cZ3q2mpJr0Mq5Ib7lqiF+Ekw03CSYKDaF/MSm24Dx85F8/t3WsMN+3da9z2FyAC4dHLcM9H+OPsRTx56EmWHFkScKAIpRchU18FyGwl0R7ZbEbuYd8+o8cwd27D8FHXrt6L5iDoEt/B+KDiA7bbtwf9uKz4LIZ0HBLw+cHOaAJZQNfWRe0K6XCR4CDCwmaDyZPN7wtwc6BQ+dt5zkqwU19DKcEBMCNvhgSINkiCgxCB8LVpUHP0HExqNX3Q7bSQehEtESRkbUTbI+schAiEr02DgtwcyC+LvR2GlP7E8OThJJIY1OWCndnkTFjre3XASWtJVrcvEhyEcLKayZSaaj2l1WbzXerbilnZDcfeDr0TezO983Sy4rMCbblLKDObgklaS7K6/ZDgIIST1UymJ580P78pM5us9nBwOz6k4xBj8VxMSoD/AEMo6yPcp74GQnoRbZ/kHIRw52smkyerHEUg+Yk30x1DSh4893Zwy0vYO5zGR2cN5+vuOYH9WwitVlMos5okH9E6SUJaiOYQE2NevC+QmU3OnIP70FJscsPq6mIbFM4Cu0fCODaZA/3u4+2uKUHNbAp22qvMamofJCEtRHOwylHExPjPQfgqu+EMHJ6BAaCuku5fPxN0TiLYXESoK6wlH9F2SM9BiFD524oUjGqvKSlG7SZ/w1ROVkNOLsoo1UFo6yNaohchi+daBxlWEqK5uOcoYmKgrs73+WZ7U3vyt0eEigVd32gf61BWWQebj5BcRNsjwUGIlmCVgzAzYwbMt/hU7bfn4MYtT9ESq6ylF9G2SHAQoiX4WmFtJj8f1q71Pm6WrAaMFKFJottjhpNVL6LXgUIGf/sPkuzHADgel8xHfca6Cv8FM9xk227jxrdv5JjjWoFK65TG3Py50pOIEpKQFqIlBLuKet0684S1WbL6guVYDjVV7oWXFKzsCsU21/oI91XWvQ4UMnT7y3SwH0MZVyW5tpKh216i1wHjg1UwSeuCrAIq7qpg+djlQVV83Xtkr6yPaCUkOAgRLgUFxmrqYFxzjfnMpowCODYX7uoJY/fBZXNAd/F9rZoy+HwqFNu8VlkP2rmKOO2dD4mjvknblIYyq8m5yloCRHSTYSUhwslmg6lToaamadc54QSw2xtfZ3A8XK9A+bm2xzBTUXURZ79+juVbtwae+vUTXselmF/bJ8NKQrSUggJYsqRxDyIhIfjrHDvmHWDW2+HVFMdwkw8epTl8bVEK/rcpnX9ofsBDTcGU4AApwxHNJDgIEW4FBXDwoDFzSWuorg4tQJh5qwzG7IWDPs5JdizOK7YZM59eigF7Bag4r1NrifG7TakdO6srVwecj5g/cr4MM7UBEhyEaAlLlkB8fPiutwKwmxyvBY79xrskuL0MUBDXseHU+JNYn31tQNuUQnD5CGel17ROfno5bhYULkDdr2SFdZSQnIMQLcV9wVyXLnD0qJFXCNWFwNWAs2hrOfAi8KmCxzV0M3mMZ2E/QtumtCUW0EmdpuYn6xyEiEbOYBHM2ohALQfzUZ2G0hvuDux6lBO3z6Nj1S+UJ3VmY6+RAfcoUmJSuDDpQr+BQhLW0UcS0kJEo4ICo7S31rB8eeMkdseOTRuGsspJ6C7emxMV2+i+5T5Sqn5BASdWHeLyHStc6x/8Ka8vD2i4SRLWrYsEByGigWcSu7wcnn/e2BsiFK+CVxUNnQDPHfXenGjTLK/V2PH19kbrHwKx3b494HxEKAlrdb8i/Yl0yUe0EBlWEiLade0KZcHtqwAYOYnfAamASjUCxlsm1/ExBPXB6LVB5yMgsJxEqHtGSK2m8JGcgxCtmc0G113XtOR1cnJDaXFn0OiKMfyUCJxo8piEVIjriK7cR0VSZz7p9ZuA8xBOgQaJUOo0ScK66STnIERrVlBgDDEFW5rDXWUlxMYageF6jJlMyvE9GVAe+Y2YBLAfhcq9KDQpVb8w7OvXAs5DOAUy/TXUOk2yNqJ5RSQ4KKUeVUoVKaW2KaX+oZQ6ye2+O5VSu5VS3ymlhkeifUJEHWdOwjNxHYy6OpgAbvX4DHFAvd3YJwKM6a6xKaAb91Ri66q5fNcHpMSkEKzt9u08eehJlhxZYrmQLpSEtayNaD6R6jm8D2RqrbOBncCdAEqpPsBEoC8wApivlPM3VgjhlbieMcPoEQRidKqRfzCjAF1nFFo6ttco4mci/vhPTO00lVmdZwW1TalTIDObgk1YgzGrafIbk6UnEUYRCQ5a6zVa61rHzc+AHo6frwBe0VpXa62Lgd3AgEi0UYhWYf58qK01ehTJydbnDY6H35VbJJ7dKLcvM8kN+2ablQYPlL+ZTaGssAYZagqniCeklVJvAyu01suVUk8Dn2mtlzvu+3/Au1rrlSaPmwZMA+jZs+d5e5tjIZEQrYnnCmxw27u6AlQIM57cue065ynUXeggsKT1zFUzWVC4IKjrygI6/yIyW0kptRY41eSuOVrrfzrOmQPkAWO11jqY4OBOZisJ4Ye/fan90RiDwcswyokvWmS5D3Yo5TjA/050oZTgAJnV5EtEZitprS/XWmeafDkDwxRgFFCgGyLUAeC/3C7Tw3FMCNEUbsNBIVHAuY6fjx2DyZNh5kzv1dYYw02h5COcSWur6q/OoaZgZjSBDDWFKiLDSkqpEcDfgEu11qVux/sCL2HkGU4H1gFnaW2yhZUb6TkI4YfZvtTOP/1A8771GIX+rCgF06cbeRCMoaZNVZsory8PocG+exKyh3V4RN0iOKXUbowJdc5B0M+01tMd980BpmIUH75Za/2uv+tJcBAiAMU2+GqOsRlQck+jtHfZAmMxXCAqMf5qYzACxTpgF40X1L0K5Dimoi5caMyoAmo7duD9v45j5/jgFtGB75xEKENNssK6QdQFh3CT4CBEiGwzwb4QEvy8D9QCsTTuZZj1PKqB54BNbsccK7J1V6AM7O8kEP9+DTo2BlVXT3mPzmy8e6TfwGHVkwi1DIfkIiQ4CCF8ce9RxHcx3uyry4zegcLo36cSeIayFLjZ8bNzRbb7bFeTAKIVfHXdID56bLzfy1v1JEIZauqY0JGFoxa222EmCQ5CiOC57zdhWZzPRD2wgIbhJrPHuQcQB63gvYWTAx56supJhDLttb32IiQ4CCGaxhYLynuTIFNHMXoKvtbGaWA+jYefgKM9OvP8tnuDaprZZkOhTnttb2sjJDgIIZrmi5mwO4BP4xpju1KzKq9m52qMnoUjma3dgoX9hERqE2LpcLiS8u7+8xLxxDMkeYgrSNi225izbg57jwS/QLa99CQkOAghmu6LmbBnsVGDiRiMd3W3WeYa+DgBLq4JfAjKnVky2429Qzxrn5gQUuI6lKGm9pCPkOAghAg/z6mxOXON0hpvpkNliOVsTHIR7oIZdvJMXIcSIKBt9yIkOAghWo7Zgjuj7Kv/x9YDa4HLaeh9uA096VehfF9gU1+d3IebQl0811Z7ERIchBAty7NXcfpvoHiZ117VXiqBDlgPS9UCi8D+74Yhpl6vFTL4zn+Q9Ivxhn+8czIfzRtrGjycyevNOzfL2ggkOAghokGxDQpngd3iDbkaiMf/eopK4AZjiGnj3SMZetPLxNU0rrDjfFezWmDnzEuE2pNoK7OaJDgIIaKHq1ex19h9rr7OWGi3ApiJ/2S2YxqsdqyjUPUYAcVZvsMjoW2VyHYfbmqv+QgJDkKI6GazwaxZ8HiZUabDFw3UYL6OwjnjCRrVfKpcm8yzLzxsejlnkNi8c3O7y0dIcBBCtA6BrKdwJqitHMXIW8S7PURDzafxJDxj91nTKUkl8f133/PIe48E3fSgexFWs71akAQHIUTr8cVM2L0IY+qSh0DKjFsFD+cCvRdxDT1Z5ibq4dV1r7LpW4tFFxYC7kWYzejysdNec5HgIIRondwX3qlYOHMa/Pgv3+so/PUsNFAF2IEUGq3O9prpVA9vrH+DDTs2BNVsv70Iq7UgyWnw25KgnqspJDgIIdoO03UUDtVAAsGv0NYePzp6GFVFJ7D+L2PYOS6PQ2ueYUrNLnrGwb5auOsgvFxhfUmfvQjLbVsVXBVgDaswiMg2oUII0SwyCozhl+Q047ZyZLB1KrxygvHGHizV8KUUqBNBTYMOvY8x4sblXHXbX7i3ehfp8RCjID0enj0FJnW0vmRFTQWT35hMyl9SsG23Nb7TatvWpm7nGkbScxBCtC22mVC/wP+sp0AcBaqNjYqUSW/kcGIn8mvOZMvOLX4v1WioqRXkHKTnIIRoWwrmw0XLISG16ddKAbqZBwaATlVHeKj8HOZNn0e/Xv18XmpB4YKGXkSj3o8yvrdwYPBHeg5CiLbN38rsptCgHQnt2i9jiLMb+YKDHWDWr+HlbPOHRcvaCOk5CCHar4wCGH8QLlje8Ek9IRXiHT0Lq8/HgXxuVqC6gboe4vvXu1IX3Y7DC2/HctfPaaYP85mPiBLScxBCtG/uPQvXwgfH90A2LXI66vie0nCNylXJ/P25e3j1g1d95iUi1ZOQqaxCCBEoZymPs8vQ14Pytd2pO5P1FdoOLHbcmACkwk8qnlt/sptOg83PyGftNWtDbnqwZFhJCCECVVAABw/CRo1KmAGHYqHeKMHhk0nSWsWDmgFqJijHjKfTsWPrAr98GsOkbY3PX1e8jg4PdYiKoSbpOQghRCCKbfDhdEh0fOR3Dwb+VmWb0cbDau2x3JfQg4d3NV4x3RJDTdJzEEKIpsoogKnlsHEGLABKQdeDLiXkhXdKQXxCHQ/pvdQXQ+0Dir+/Y9ztTFpf/sLlYfxHBNE86TkIIUQT2GzULbuBmILjqHj/p1vSjb5xWMXyh5/qeLkCkmKTeO6K58Lei5CegxBCNJeCAmLXVKIuMRbeaYz8hA62RJJ7+Q4FnanDdirYq2HMv6tafOqr9ByEEKIZ1Iw/hfhRPzetNwGu3ATAayqVCbvKwpaPkJ6DEEK0sITX/mP0JuJTjZ6EDmDGkxm33sR4XUb9r+BozwrGvH51s+YjpOcghBAt5MCuRzn10zuIia23rNcUKNdbt4ZdR3rS6w8+9riwEHU9B6XUo0qpIqXUNqXUP5RSJzmOpyuljiultjq+FkaifUII0Ry6nzWb2GvqUMxAH1NN6lE4exMqBs46aR/1y5sYbTxEaljpfSBTa50N7ATudLtvj9Y61/E1PTLNE0KIZlQwH3VDPapA892V3/LD12ejq0McdqIhUIQzQEQkOGit12itax03PwN6RKIdQggRab0Te9Pz4SLUdZpqfWaTA0S4RENCeirwrtvtDKXUv5VSHymlLrZ6kFJqmlKqUClVWFpa2vytFEKIZpY0eTfqwuXUxp/UtCR2GDRbQloptRY41eSuOVrrfzrOmQPkAWO11loplQh01FqXKaXOA94E+mqtj5pcx0US0kKItqrshfPoEmtUdFWu/5jTGlRB4O/pvhLSccE0Mhhaa59zrJRSU4BRQL52RCitdTXGFuForTcrpfYAvQB55xdCtEup12w2frDZqF98DeqGetf0VnfOXka4RpYiNVtpBHAbMFprXel2vJtSxm7hSqkzgLOA7yPRRiGEiCoFBcR8VIearKn7lkbDTs6vmMnhGwlqtp6DH08DicD7ygh/nzlmJl0CPKCUsgP1wHSt9S8RaqMQQkSluIe8g0B4J7JGKDhorX9lcfx14PUWbo4QQggP0TBbSQghRJSR4CCEEMKLBAchhBBeJDgIIYTw0iaqsiqlSoFgSxJ2BQ42Q3PaGnmd/JPXKDDyOvnX0q9Rmta6m9kdbSI4hEIpVWi1MlA0kNfJP3mNAiOvk3/R9BrJsJIQQggvEhyEEEJ4ac/BYXGkG9BKyOvkn7xGgZHXyb+oeY3abc5BCCGEtfbccxBCCGFBgoMQQggvbT44KKVGKKW+U0rtVkrdYXJ/olJqheP+z5VS6RFoZkQF8BpdopTaopSqVUpdGYk2RoMAXqf/o5T6Rim1TSm1TimVFol2RloAr9N0pdR2pdRWpdQnSqk+kWhnJPl7jdzOG6eU0kqplp/eqrVus19ALLAHOANIAL4C+nicMxNY6Ph5IrAi0u2OwtcoHcgGXgCujHSbo/h1ugxIdvw8o739LgXxOp3o9vNo4L1ItzvaXiPHeSnABuAzIK+l29nWew4DgN1a6++11jXAK8AVHudcASxz/LwSyFcqnNt0Rz2/r5HWukRrvQ1jj432KpDX6UPdsHnVZ0CPFm5jNAjkdXLf9vcEoL3NignkfQngQeD/AlUt2Tinth4cugM/uN3e7zhmeo7WuhY4AqS2SOuiQyCvkQj+dfo98G6ztig6BfQ6KaX+4NgG+BHgTy3Utmjh9zVSSvUD/ktrvaolG+aurQcHIVqcUmoykAc8Gum2RCut9TNa6zOB24E/R7o90UQpFQP8DfifSLajrQeHA8B/ud3u4Thmeo5SKg7oBJS1SOuiQyCvkQjwdVJKXQ7MwdgfvbqF2hZNgv19egX4bXM2KAr5e41SgExgvVKqBBgIvNXSSem2Hhy+BM5SSmUopRIwEs5veZzzFnCt4+crgQ+0IxvUTgTyGokAXiel1LnAIozA8HME2hgNAnmdznK7ORLY1YLtiwY+XyOt9RGtdVetdbrWOh0jfzVaa13Yko1s08HBkUP4I7Aa+BZ4VWv9tVLqAaXUaMdp/w9IVUrtBv4PYDmtrC0K5DVSSvVXSu0HxgOLlFJfR67FkRHg79KjQEfgNcc0zXYXZAN8nf6olPpaKbUV42/uWvOrtU0BvkYRJ+UzhBBCeGnTPQchhBChkeAghBDCiwQHIYQQXiQ4CCGE8CLBQQghhBcJDkIEQSm1tD1XphXthwQHIYQQXiQ4COGDUuoax/4MXymlXnQcvkQptUkp9b2zF6GU6ujYw2GLY6+CKxzH05VS3yqlnnUs/FqjlOrguK+/49pblVKPKqV2OI7HOm5/6bj/xoj840W7JsFBCAtKqb4YReGGaK1zgFmOu04DLgJGAfMcx6qAMVrrfhj7OvzVrfT7WcAzWuu+wGFgnOP488CNWutcoM7tqX8PHNFa9wf6AzcopTLC/y8UwlpcpBsgRBQbArymtT4IoLX+xfF+/6bWuh74Ril1iuNcBTyslLoEY9+L7oDzvmKt9VbHz5uBdKXUSUCK1vpTx/GXMIINwDAg2y230QkjwBSH/58ohDkJDkIEz73aqrN3UAB0A87TWtsd1TSTTM6vAzr4ub4CbtJarw5DW4UIiQwrCWHtA2C8UioVQCnVxce5nYCfHYHhMsDn/tFa68NAuVLqfMehiW53rwZmKKXiHc/bSyl1Qoj/BiFCIj0HISw4KmXOBT5SStUB//Zxug14Wym1HSgEigJ4it8Dzyql6oGPMHYhBHgOY9/uLY68RSntb88DEWFSlVWICFFKddRaVzh+vgM4TWs9y8/DhGgR0nMQInJGKqXuxPg73AtMiWxzhGggPQchhBBeJCEthBDCiwQHIYQQXiQ4CCGE8CLBQQghhBcJDkIIIbz8f+0UEgExlFk3AAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -790,7 +3564,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 45, "metadata": {}, "outputs": [], "source": [ @@ -856,7 +3630,7 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 46, "metadata": {}, "outputs": [ { @@ -866,7 +3640,7 @@ "Even hypervolume: 19.883448199417447\n", "Perfect hypervolume: 20.450602282335318\n", "ESP hypervolume: 20.704040842702252\n", - "Torch hypervolume: 20.194989954632486\n" + "Torch hypervolume: 20.37706786923874\n" ] } ], @@ -890,7 +3664,7 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 47, "metadata": {}, "outputs": [], "source": [ @@ -915,12 +3689,12 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 48, "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZIAAAEKCAYAAAA4t9PUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAAmG0lEQVR4nO3de3SU5bn38e9FwASQIiAeKSTsIhZyAkLkUA4aEVp5cQuyRbGWao1oq9W3ovDGWrXGTZXWQ61CdCG2pjUKu4iiyKEgWkQMNEI4KGcE3TUgKBBOSe73j5mME5hkEp5MZgK/z1pZmbmf05VxDT+fuee5HnPOISIicrKaRLsAERFp3BQkIiLiiYJEREQ8UZCIiIgnChIREfFEQSIiIp7EbJCY2TAz+8TMNpnZxGjXIyIioVksXkdiZnHAp8AQYCfwEXCdc25dVAsTEZETxOoZSSawyTm3xTl3FHgFuCrKNYmISAhNo11ANS4EPgt6vhO4JHgFM8sGsgFatmzZ6+KLL2646kRETgErV67c7Zxr73U/sRokYTnn8oA8gIyMDFdYWBjlikREGhcz214f+4nVj7Z2Ad8Net7BPyYiIjEmVoPkI6CLmSWZ2RnAGGBOlGsSEZEQYvKjLedcmZn9AngHiAOmO+fWRrksEREJISaDBMA59xbwVrTrEDlVHTt2jJ07d3L48OFolyIRlpCQQIcOHWjWrFlE9h+zQSIikbVz505atWpFYmIiZhbtciRCnHPs2bOHnTt3kpSUFJFjxOociYhE2OHDh2nXrp1C5BRnZrRr1y6iZ54KEpHTmELk9BDp/84KEhER8URBIiJRExcXR3p6euBn8uTJETvWkiVLGD58eJWxcePGMXPmzHrZ/+eff84111xT7fJ9+/bx7LPP1nr9xkST7SISNc2bN6eoqCjaZXhWVlbGBRdcUGMoVQbJ7bffDhB2/cZEZyQiUiv5a/JJfDKRJg81IfHJRPLX5EfkOPPmzWP06NGB58FnEvPnz6dv37707NmT0aNHc+DAAQASExP5zW9+Q8+ePUlJSWHDhg11Pu7KlSsZNGgQvXr1YujQoXzxxRcADB48mMoWTLt37yYxMRGAGTNmMGLECC677DKysrLYtm0bycnJAKxdu5bMzEzS09NJTU1l48aNTJw4kc2bN5Oens6ECROqrF9eXs4999xDcnIyqamp/PGPfzy5Fy9KdEYiImHlr8kn+41sSo+VArD96+1kv5ENwNiUsSe930OHDpGenh54PmnSJEaNGkV2djYHDx6kZcuWFBQUMGbMGHbv3s0jjzzCwoULadmyJb/73e/4wx/+wAMPPADA2WefzapVq3j22WeZMmUKL7zwwgnHe++996ocb8eOHQwfPpxjx45xxx138Prrr9O+fXsKCgrIyclh+vTpNda/atUqVq9eTdu2bdm2bVtgfOrUqfzyl79k7NixHD16lPLyciZPnkxxcXHgDCx4/by8PLZt20ZRURFNmzblq6++qvNrGU0KEhEJK2dRTiBEKpUeKyVnUY6nIKnuo61hw4bxxhtvcM011zB37lwee+wx3n33XdatW0f//v0BOHr0KH379g1sM3LkSAB69erF//zP/4Q83oABA3jzzTcDz8eNGwfAJ598QnFxMUOGDAF8Zwjnn39+2PqHDBlC27ZtTxjv27cvubm57Ny5k5EjR9KlS5ca97Nw4ULGjx9P06a+f5JD7TOWKUhEJKwdX++o07hXY8aM4ZlnnqFt27ZkZGTQqlUrnHMMGTKEv/3tbyG3iY+PB3wT+GVlZXU6nnOO7t2788EHH5ywrGnTplRUVACccC1Gy5YtQ+7v+uuv55JLLmHu3Ln86Ec/Ytq0aXTu3LlONTUmmiMRkbA6tu5Yp3GvBg0axKpVq3j++ecZM2YMAH369OGf//wnmzZtAuDgwYN8+umn9XK8rl27UlJSEgiSY8eOsXatr71fYmIiK1euBKj15PiWLVvo3Lkzd955J1dddRWrV6+mVatW7N+/P+T6Q4YMYdq0aYEAbGwfbSlIRCSs3KxcWjRrUWWsRbMW5Gbletpv5RxJ5c/EiRMB31nF8OHDefvttwMT7e3bt2fGjBlcd911pKam0rdv35OaVA/ljDPOYObMmdx3332kpaWRnp7OsmXLALjnnnt47rnn6NGjB7t3767V/l599VWSk5NJT0+nuLiYG2+8kXbt2tG/f3+Sk5OZMGFClfV/9rOf0bFjR1JTU0lLS+Ovf/1rvfxdDSUm79leV7qxlUjdrV+/nu9///u1Xj9/TT45i3LY8fUOOrbuSG5Wrqf5EWlYof57m9lK51yG131rjkREamVsylgFh4Skj7ZERMQTBYmIiHiiIBEREU8UJCIi4omCREREPFGQiEjUVLaRT05OZvTo0ZSWlobfKMiECRPo3r37Cddl1Majjz5a7bLExMQq14yEakHvxc9+9jPWrVtX7fIZM2bw+eef13r9aFOQiEjUVPbaKi4u5owzzmDq1Km12q7yCvC8vDxWr17N448/Xudj1xQkkVReXs4LL7xAt27dql3n+CAJt360KUhEpFY2HNnA9K+n89Tep5j+9XQ2HKmfq8orDRgwgE2bNnHw4EFuuukmMjMz6dGjB6+//jpwYtv2ESNGcODAAXr16kVBQQElJSWMGjWK3r1707t3b/75z38CcODAAX7605+SkpJCamoqs2bNYuLEiYGr6seOrdu1MTXV94tf/CKw3vDhw1myZAkAZ555Jr/61a9IS0vjgw8+CLSmLy8vZ9y4cSQnJ5OSksITTzzBzJkzKSwsZOzYsaSnp3Po0KEqreznzZtHz549SUtLIysry+vLXi90QaKIhLXhyAYWlS6iDN+ZwP6K/SwqXQTAxfEXe95/WVkZb7/9NsOGDSM3N5fLLruM6dOns2/fPjIzM7n88suBqm3bwfcPdGX34Ouvv567776bH/zgB+zYsYOhQ4eyfv16fvvb39K6dWvWrFkDwN69exk1ahTPPPNMjTfVuvTSS4mLiwN8YXTxxb6/s6b6qnPw4EEuueQSfv/731cZLyoqYteuXRQXFwO+m1+dddZZPPPMM0yZMoWMjKoXnZeUlHDLLbewdOlSkpKSYqYnl4JERMJadnhZIEQqlVHGssPLPAVJ8P1IBgwYwM0330y/fv2YM2cOU6ZMAXwdd3fs8HUZrq5tO/hasQfPI3zzzTccOHCAhQsX8sorrwTG27RpU6vaFi9ezNlnnw345kgq65k/f3619VUnLi6OUaNGnTDeuXNntmzZwh133MGVV17JFVdcUeN+li9fzsCBA0lKSgJip928gkREwtpfEbprbXXjtRXqfiTOOWbNmkXXrl2rjH/44YfVtm0HqKioYPny5SQkJHiqKZzq6lu5cmWg3TxUbTmfkJAQOLsJ1qZNGz7++GPeeecdpk6dyquvvhr2ZlqxSHMkIhJWqyat6jTuxdChQ/njH/9IZUPZf/3rX7Xa7oorrqhyi9rKgBoyZAh/+tOfAuN79+4FoFmzZhw7dqze6ktMTKSoqIiKigo+++wzVqxYEXZfu3fvpqKiglGjRvHII4+watUqgGpbzvfp04elS5eydetWIHbazStIRCSsfgn9aHrcBxhNaUq/hH71fqxf//rXHDt2jNTUVLp3786vf/3rWm339NNPU1hYSGpqKt26dQt8A+z+++9n7969JCcnk5aWxuLFiwHIzs4mNTW1zpPt1dXXv39/kpKS6NatG3feeSc9e/YMu69du3YxePBg0tPTueGGG/jv//5vwHfnxvHjxwcm2yu1b9+evLw8Ro4cSVpaGtdee22dao8UtZEXOU3VtY38hiMbWHZ4Gfsr9tOqSSv6JfSrl4l2aRhqIy8iUXdx/MUKDglJH22JiIgnChIREfFEQSIiIp4oSERExBMFiYiIeKIgEZGoqWwjX/kzefJkAN5880169OhBWloa3bp1Y9q0aQA8+OCDXHjhhYHW83PmzDlhnzNmzKB9+/akp6fTrVs3nn/++Qb7ex544AEWLlxY4zqzZ8+O6ZbwJyPmvv5rZg8CtwAl/qH/55x7K3oViUikhGqRcuzYMbKzs1mxYgUdOnTgyJEjbNu2LbD87rvv5p577mH9+vUMGDCAL7/8kiZNqv4/8bXXXsszzzzDl19+Sffu3RkxYgTnnntuYHlZWRlNm9bvP3/l5eU8/PDDYdebPXs2w4cPr1Nb+EjUW59i9YzkCedcuv9HISISC/LzITERmjTx/c7Pj8hh9u/fT1lZGe3atQMgPj7+hL5WAN///vdp2rRplRtQHe+cc87hP/7jP9i+fXvgavFLLrmEe++9l82bNzNs2DB69erFgAED2LDB1xb/tddeC1wFP3DgQMAXEvfccw/JycmkpqYGWrEkJiZy33330bNnT1577TXGjRvHzJkzA8vuvfdeUlJSyMzMZNOmTSxbtow5c+YwYcIE0tPT2bx5M0VFRfTp04fU1FSuvvrqQAuXwYMHc9ddd5GRkcFTTz0Vsq5YEbsRJyKxIz8fsrOh8g6G27f7ngPUscVIsODuvwCTJk3i2muvZcSIEXTq1ImsrCyGDx/Oddddd8JZx4cffkiTJk1o3759tfvfsmULW7Zs4Xvf+x4AO3fuZNmyZcTFxZGVlcXUqVPp0qULH374Ibfffjv/+Mc/ePjhh3nnnXe48MIL2bdvH+C7gda2bdsoKiqiadOmVXpctWvXLtAja968eVWOX9m+/s9//jN33XUXb775JiNGjGD48OFcc801AIFgGjRoEA888AAPPfQQTz75JABHjx4N3IckJSXlhLpiRawGyS/M7EagEPiVc27v8SuYWTaQDdCxY8cGLk/kNJOT822IVCot9Y17CJJQH22B746Aa9asYeHChUyZMoUFCxYwY8YMAJ544glefvllWrVqRUFBAWZ2wvYFBQW8//77xMfHM23atEC79dGjRxMXF8eBAwdYtmwZo0ePDmxz5MgRwNcza9y4cfzXf/0XI0eOBHwt6sePHx/4eCm4fXtN/a6uu+66wO+77777hOVff/01+/btY9CgQQD85Cc/qVJT8L5D1RUrohIkZrYQOC/EohzgOeC3gPP//j1w0/ErOufygDzw9dqKWLEiAtXdbyPMfTi8SElJISUlhR//+MckJSUFgqRyjqQmlXMkx6tsQ19RUcFZZ50VMsSmTp3Khx9+yNy5c+nVqxcrV66s8Vg1tbYPDrlQgRdO8L5D1VX58V+0RWWOxDl3uXMuOcTP6865fzvnyp1zFcDzQGY0ahSRINWd9Ufg04ADBw4EblELvnbwnTp1qtdjfOc73yEpKYnXXnsN8N1j5OOPPwZg8+bNXHLJJTz88MO0b9+ezz77jCFDhjBt2rTAveJr2769oKAg8Ltv375A1RbxrVu3pk2bNrz33nsA/OUvfwmcnRwvVF2xIuY+2jKz851zX/ifXg0UR7MeEQFyc6vOkQC0aOEb9+D4OZJhw4aRk5PDY489xq233krz5s1p2bJl4GykPuXn53PbbbfxyCOPcOzYMcaMGUNaWhoTJkxg48aNOOfIysoiLS2N5ORkPv30U1JTU2nWrBm33HJLlfuzV2fv3r2kpqYSHx/P3/72NwDGjBnDLbfcwtNPP83MmTN56aWXGD9+PKWlpXTu3JkXX3wx5L5C1RUrYq6NvJn9BUjH99HWNuDWoGAJSW3kRequrm3kyc/3zYns2OE7E8nN9TQ/cqpLTEyksLAwcLveaDut2sg7534c7RpEJISxYxUcElLMBYmIyKkg+CLKU12sXpAoIiKNhIJEREQ8UZCIiIgnChIREfFEQSIiUbFnz55A+/jzzjsv0B4+PT2do0eP1nl/Dz74IFOmTAm7XmJiIikpKaSmpnLFFVfwv//7vydTfp19/vnngf5a1dm3bx/PPvtsg9RTnxQkIhIV7dq1o6ioiKKiIsaPH8/dd98deH7GGWdUu115ebnnYy9evJjVq1eTkZHBo48+WmWZc46KigrPxwhWVlbGBRdcEOgMXJ2TCZLKq+2jSUEiIrWzNR9mJ8Jfm/h+b63/NvKLFi2iR48epKSkcNNNNwUaKR7frn3evHn07NmTtLQ0srKyAtuvW7eOwYMH07lzZ55++umwxxs4cCCbNm1i27ZtdO3alRtvvJHk5GQ+++wzHn/8cXr37k1qaiq/+c1vADh48CBXXnll4Gr3yhYoH330Ef369SMtLY3MzEz279/PjBkzGDFiBJdddhlZWVls27aN5ORkwHfzrauuuorBgwfTpUsXHnroIQAmTpzI5s2bSU9PZ8KECTjnmDBhAsnJyaSkpASOt2TJEgYMGMCIESPo1q1btXU1FF1HIiLhbc2HFdlQ7m+RUrrd9xwgqX4uUjx8+DDjxo1j0aJFXHTRRdx4440899xz3HXXXcC37dpLSkro2bMnS5cuJSkpqUrfqw0bNrB48WL2799P165due2222jWrFm1x3zzzTdJSUkBYOPGjbz00kv06dOH+fPns3HjRlasWIFzjhEjRrB06VJKSkq44IILmDt3LuDr3nv06FGuvfZaCgoK6N27N9988w3NmzcHYNWqVaxevZq2bduecF3JihUrKC4upkWLFvTu3Zsrr7ySyZMnU1xcHGgmOWvWLIqKivj444/ZvXs3vXv3DtyLZNWqVRQXF5OUlMSsWbNOqKsh6YxERML7OOfbEKlUXuobryfl5eUkJSVx0UUXAb6W6kuXLg0sr2ypvnz5cgYOHEhSUhJQtaX7lVdeSXx8PGeffTbnnHMO//73v0Me69JLLyU9PZ1vvvmGSZMmAdCpUyf69OkDwPz585k/fz49evSgZ8+ebNiwgY0bN5KSksKCBQu47777eO+992jdujWffPIJ559/Pr179wZ8DSEr280PGTKkSn3BhgwZQrt27WjevDkjR47k/fffP2Gd999/n+uuu464uDjOPfdcBg0axEcffQRAZmZm4DUIVVdD0hmJiIRXWk27+OrGI6Cmdu2V4uPjA4/j4uKqnT9YvHhxlR5Y+/btq7J/5xyTJk3i1ltvPWHbVatW8dZbb3H//feTlZXF1VdffVI1H99Wvq5t5oP3fdFFF51Q1wMPPFCn/XmhMxIRCa9FNe3iqxs/CXFxcWzbto1NmzYB1bdU79OnD0uXLmXr1q1A7Vu618XQoUOZPn06Bw4cAGDXrl18+eWXfP7557Ro0YIbbriBCRMmsGrVKrp27coXX3wROFOovFVwOAsWLOCrr77i0KFDzJ49m/79+1dpMQ8wYMAACgoKKC8vp6SkhKVLl5KZeeKdNULV1ZB0RiIi4aXlVp0jAYhr4RuvJwkJCbz44ouMHj2asrIyevfuzfjx409Yr3379uTl5TFy5EgqKio455xzWLBgQb3VAXDFFVewfv36wD1EzjzzTF5++WU2bdrEhAkTaNKkCc2aNeO5557jjDPOoKCggDvuuINDhw7RvHlzFi5cGPYYmZmZjBo1ip07d3LDDTeQkeFrwtu/f3+Sk5P54Q9/yGOPPcYHH3xAWloaZsZjjz3GeeedF7i/fKU1a9acUFdDirk28idDbeRF6q7ObeS35vvmREp3+M5E0nLrbaL9dDNjxgwKCwtD3sUxUk6rNvIiEqOSxio4JCQFiYhIAxs3bhzjxo2Ldhn1RpPtIqexU+GjbQkv0v+dFSQip6mEhAT27NmjMDnFOefYs2cPCQkJETuGPtoSOU116NCBnTt3UlJSEu1SJMISEhLo0KFDxPavIBE5TTVr1ixwZbSIF/poS0REPFGQiIiIJwoSERHxREEiIiKeKEhERMQTBYmIiHiiIBEREU8UJCIi4omCREREPFGQiIiIJwoSERHxREEiIiKeKEhERMQTBYmIiHgSlSAxs9FmttbMKsws47hlk8xsk5l9YmZDo1GfiIjUXrTuR1IMjASmBQ+aWTdgDNAduABYaGYXOefKG75EERGpjaickTjn1jvnPgmx6CrgFefcEefcVmATkNmw1YmISF3E2hzJhcBnQc93+sdOYGbZZlZoZoW6VaiISPRE7KMtM1sInBdiUY5z7nWv+3fO5QF5ABkZGc7r/kRE5ORELEicc5efxGa7gO8GPe/gHxMRkRgVax9tzQHGmFm8mSUBXYAVUa5JRERqEK2v/15tZjuBvsBcM3sHwDm3FngVWAfMA36ub2yJiMS2qHz91zn3d+Dv1SzLBXIbtiIRETlZsfbRloiINDIKEhER8URBIiIinihIRETEEwWJiIh4oiARERFPFCQiIuJJjUFiZo+b2a0hxm81s8mRK0tERBqLcGckl+FvjHic54Hh9V+OiIg0NuGCJN45d0JnXedcBWCRKUlERBqTcEFyyMy6HD/oHzsUmZJERKQxCddr6wHgbTN7BFjpH8sAJgF3RbAuERFpJGo8I3HOvQ38J3ApMMP/cykwyjn3VoRrE2m08tfkk/hkIk0eakLik4nkr8mPdkkiERO2+69zrhj4SQPUInJKyF+TT/Yb2ZQeKwVg+9fbyX4jG4CxKWOjWZpIRNQYJGb2BhA82e6A3cBi59zLkSxMpLHKWZQTCJFKpcdKyVmUoyCRU1K4M5IpIcbaAjeYWbJzbmIEahJp1HZ8vaNO4yKNXY1B4px7N9S4mc3BN/muIBE5TsfWHdn+9faQ4yKnopNqkaLb34pULzcrlxbNWlQZa9GsBblZuvGnnJrCzZG0DTHcBrgRWBuRikQaucp5kJxFOez4egcdW3ckNytX8yNyyrIQF65/u9BsK74J9sqr2Csn25cAv3XO7Y90gbWRkZHhCgsLo12GiEijYmYrnXMZXvcTbo4kqYYCCoBrvRYgIiKNm5c28n3rrQoREWm0dD8SERHxJNxke8/qFgHN6r8cERFpbMJdkPj7GpZtqM9CRESkcQo32X5pQxUiIiKNU7hb7d4b9Hj0ccsejVRRIiLSeISbbB8T9HjSccuG1XMtIiLSCIULEqvmcajnIiJyGgoXJMe3kK9umYiInKbCfWsrzcy+wXf20dz/GP/zhIhWJtKIbTiygWWHl7G/Yj+tmrSiX0I/Lo6/ONpliUREuG9txTVUISKnig1HNrCodBFllAGwv2I/i0oXAShM5JSkK9tF6sPWfJidCH9tQoe3fkDnXcurLC6jjGWHl0WnNpEIC3vPdhEJY2s+rMiGct/tdc88tIfLiwsA+PTCbxur7q+IiWbZIvVOZyQiXn2cEwiRSs0qjtH/07lVxlo1adWQVYk0mKgEiZmNNrO1ZlZhZhlB44lmdsjMivw/U6NRn0idlIa+F3urw3sDj5vSlH4J/RqqIpEGFa2PtoqBkcC0EMs2O+fSG7YcEQ9adITSE+/RfrB5OwB9a0tOeVEJEufcegAzXdMop4C03CpzJADEteDM9Kf4ZRvdXldOfbE4R5JkZv8ys3fNbEB1K5lZtpkVmllhSUlJQ9YnUlXSWMjMgxadAPP9zszzjYucBiJ2RmJmC4HzQizKcc69Xs1mXwAdnXN7zKwXMNvMujvnvjl+RedcHpAHvnu211fdIiclaayCQ05bEQsS59zlJ7HNEeCI//FKM9sMXAQU1nN5IiJST2Lqoy0za29mcf7HnYEuwJboViUiIjWJ1td/rzaznUBfYK6ZveNfNBBYbWZFwExgvHPuq2jUKCIitROtb239Hfh7iPFZwKyGr0hERE5WTH20JSIijY+CREREPFGQiIiIJwoSERHxREEiUlv5+ZCYCE2a+H7n50e7IpGYoPuRiNRGfj5kZ0Opv5/W9u2+5wBjdUW7nN50RiJSGzk534ZIpdJS37jIaU5BIlIbO0Lfc6TacZHTiIJEpDY6dqzbuMhpREEiUhu5udCiRdWxFi184yKnOQWJSG2MHQt5edCpE5j5fuflaaJdBH1rS6T2xo5VcIiEoDMSERHxREEiIiKeKEhERMQTBYmIiHiiIBEREU8UJCIi4omCREREPFGQiIiIJwoSERHxREEiIiKeKEhERMQTBYmIiHiiIBEREU8UJCIi4omCREREPFGQiIiIJwoSERHxREEiIiKeKEhERMQTBYmIiHiiIBEREU8UJCIi4klUgsTMHjezDWa22sz+bmZnBS2bZGabzOwTMxsajfpERKT2onVGsgBIds6lAp8CkwDMrBswBugODAOeNbO4KNUoIiK1EJUgcc7Nd86V+Z8uBzr4H18FvOKcO+Kc2wpsAjKjUaOIiNROLMyR3AS87X98IfBZ0LKd/rETmFm2mRWaWWFJSUmESxQRkeo0jdSOzWwhcF6IRTnOudf96+QAZUB+XffvnMsD8gAyMjKch1JFRMSDiAWJc+7ympab2ThgOJDlnKsMgl3Ad4NW6+AfExGRGBWtb20NA+4FRjjnSoMWzQHGmFm8mSUBXYAV0ahRRERqJ2JnJGE8A8QDC8wMYLlzbrxzbq2ZvQqsw/eR18+dc+VRqlFERGohKkHinPteDctygdwGLEdERDyIhW9tiYhII6YgERERTxQkIiLiiYJEREQ8UZCIiIgnChIREfFEQSIiIp4oSERExBMFiYiIeKIgERERTxQkIiLiiYJEREQ8UZCIiIgnChIREfFEQSIiIp4oSERExBMFiYiIeKIgERERTxQkIiLiiYJEREQ8UZCIiIgnChIREfFEQSIiIp4oSERExBMFiYiIeKIgERERTxQkIiLiiYJEREQ8UZCIiIgnChIREfFEQSIiIp4oSERExBMFiYiIeKIgERERTxQkIiLiSVSCxMweN7MNZrbazP5uZmf5xxPN7JCZFfl/pkajPhERqb1onZEsAJKdc6nAp8CkoGWbnXPp/p/x0SlPRERqKypB4pyb75wr8z9dDnSIRh0iIuJd02gXANwEFAQ9TzKzfwHfAPc7594LtZGZZQPZ/qdHzKw4smXWi7OB3dEuohZUZ/1SnfWnMdQIjafOrvWxE3PO1cd+Ttyx2ULgvBCLcpxzr/vXyQEygJHOOWdm8cCZzrk9ZtYLmA10d859E+ZYhc65jPr9C+qf6qxfqrN+NYY6G0ONcPrVGbEzEufc5TUtN7NxwHAgy/nTzDl3BDjif7zSzDYDFwGFkapTRES8ida3toYB9wIjnHOlQePtzSzO/7gz0AXYEo0aRUSkdqI1R/IMEA8sMDOA5f5vaA0EHjazY0AFMN4591Ut9pcXsUrrl+qsX6qzfjWGOhtDjXCa1RmxORIRETk96Mp2ERHxREEiIiKexHyQmNkwM/vEzDaZ2cQQy+PNrMC//EMzSwxaNsk//omZDY3FOhu6LUwt6hxoZqvMrMzMrjlu2U/MbKP/5ycxWmN50Gs5J1I11rLO/2tm6/ytgBaZWaegZQ3yWtZDnbH0eo43szX+Wt43s25By2LpvR6yzlh7rwetN8rMnJllBI3V7fV0zsXsDxAHbAY6A2cAHwPdjlvndmCq//EYoMD/uJt//Xggyb+fuBisMxEojqHXMxFIBf4MXBM03hbfN+jaAm38j9vEUo3+ZQdi6LW8FGjhf3xb0H/zBnktvdYZg6/nd4IejwDm+R/H2nu9ujpj6r3uX68VsBRfh5GMk309Y/2MJBPY5Jzb4pw7CrwCXHXcOlcBL/kfzwSyzPdVsKuAV5xzR5xzW4FN/v3FWp0NKWydzrltzrnV+L41F2wosMA595Vzbi++fmnDYqzGhlSbOhe7b7/eHtwKqKFeS691NqTa1Bl8YXJLoPKbQjH1Xq+hzoZUm3+TAH4L/A44HDRW59cz1oPkQuCzoOc7/WMh13G+/l1fA+1quW0s1An+tjBm9q6ZDYhQjbWtMxLb1oXX4ySYWaGZLTez/6zXyqqqa503A2+f5LZeeKkTYuz1NLOfm+9C5ceAO+uybQzUCTH0XjeznsB3nXNz67rt8WKh19bp7gugowtqC2NmYdvCSLU6Oed2me+C1n+Y2Rrn3OZoFmRmN+BrBTQomnWEU02dMfV6Ouf+BPzJzK4H7gciOr90sqqpM2be62bWBPgDMK4+9hfrZyS7gO8GPe/gHwu5jpk1BVoDe2q5bdTr9J8+7gFfWxh8n0deFMU6I7FtXXg6jnNul//3FmAJ0KM+iwtSqzrN7HIgB18XhyN12TYG6oy51zPIK8B/nuS2Xpx0nTH2Xm8FJANLzGwb0AeY459wr/vr2RATPx4mjJrim4hM4tsJo+7HrfNzqk5iv+p/3J2qE0ZbiNwEnJc621fWhW9ibBfQNlp1Bq07gxMn27fimxxu439c73V6rLENEO9/fDawkRATjA3437wHvn8suhw33iCvZT3UGWuvZ5egx/8HKPQ/jrX3enV1xuR73b/+Er6dbK/z61nvf0AEXpAf4bv51WZ8nYMBHsb3f04ACcBr+CaEVgCdg7bN8W/3CfDDWKwTGAWsBYqAVcD/iXKdvfF9JnoQ35nd2qBtb/LXvwn4aazVCPQD1vjfBGuAm6P8Wi4E/u3/b1sEzGno19JLnTH4ej4V9F5ZTNA/jDH2Xg9ZZ6y9149bdwn+IDmZ11MtUkRExJNYnyMREZEYpyARERFPFCQiIuKJgkRERDxRkIiIiCcKEpE6MLMZx3ccFjndKUhERMQTBYlIDczsRv99Oj42s7/4hwea2TIz21J5dmJmZ/rv5bHKfy+Kq/zjiWa23syeN7O1ZjbfzJr7l/X277vIzB43s2L/eJz/+Uf+5bdG5Y8XqSUFiUg1zKw7voZ7lznn0oBf+hedD/wAGA5M9o8dBq52zvXEd3+P3wfdJqAL8CfnXHdgH74rnAFeBG51zqUD5UGHvhn42jnXG99V/LeYWVL9/4Ui9UPdf0WqdxnwmnNuN4Bz7it/Nsx2zlUA68zsXP+6BjxqZgPx3SflQqBy2VbnXJH/8Uog0czOAlo55z7wj/8VXzABXAGkBs3FtMYXRlvr/08U8U5BIlJ3R4IeV551jMXXlK+Xc+6Yv6NqQoj1y4HmYfZvwB3OuXfqoVaRiNNHWyLV+wcw2szaAZhZ2xrWbQ186Q+RS4FONe3YObcP2G9ml/iHxgQtfge4zcya+Y97kZm1PMm/QSTidEYiUg3n3FozywXeNbNy4F81rJ4PvGFma4BCYEMtDnEz8LyZVQDv4rtrJsAL+O7vvco/z1LCt/feEIk56v4rEiVmdqZz7oD/8UTgfOfcL8NsJhJzdEYiEj1XmtkkfO/D7dTTbU9FGprOSERExBNNtouIiCcKEhER8URBIiIinihIRETEEwWJiIh48v8BvQaXEE909uUAAAAASUVORK5CYII=", + "image/png": "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", "text/plain": [ "
" ] @@ -950,12 +3724,12 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 54, "metadata": {}, "outputs": [], "source": [ - "def trained_prescribe_and_predict(cand_id: int, results_dir: Path, context_df: pd.DataFrame, prescriptor: Prescriptor):\n", - " context_actions_df = prescriptor.prescribe_land_use(cand_id, results_dir, context_df)\n", + "def trained_prescribe_and_predict(context_df: pd.DataFrame, prescriptor: Prescriptor, **kwargs):\n", + " context_actions_df = prescriptor.prescribe_land_use(context_df, **kwargs)\n", " eluc_df, change_df = prescriptor.predict_metrics(context_actions_df)\n", " context_actions_df[\"ELUC\"] = eluc_df[\"ELUC\"]\n", " context_actions_df[\"change\"] = change_df[\"change\"]\n", @@ -964,33 +3738,33 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 55, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "757/757 [==============================] - 3s 4ms/step\n" + "757/757 [==============================] - 4s 4ms/step\n" ] } ], "source": [ "esp_unsorted_idx = esp_changes.index(esp_changes_sorted[esp_idx])\n", "esp_id = esp_all_pareto_df[\"id\"].iloc[esp_unsorted_idx]\n", - "esp_result = trained_prescribe_and_predict(esp_id, esp_results_dir, context_df, unileaf_prescriptor)\n", + "esp_result = trained_prescribe_and_predict(context_df, unileaf_prescriptor, cand_id=esp_id, results_dir=esp_results_dir)\n", "\n", "torch_unsorted_idx = torch_changes.index(torch_changes_sorted[torch_idx])\n", "torch_id = torch_all_pareto_df[\"id\"].iloc[torch_unsorted_idx]\n", - "torch_result = trained_prescribe_and_predict(torch_id, torch_results_dir, context_df, torch_prescriptor)\n", + "torch_result = trained_prescribe_and_predict(context_df, torch_prescriptor, cand_id=torch_id, results_dir=torch_results_dir)\n", "\n", - "even_result = trained_prescribe_and_predict(pcts[even_idx], None, context_df, even_heuristic)\n", - "perfect_result = trained_prescribe_and_predict(pcts[perfect_idx], None, context_df, perfect_heuristic)" + "even_result = trained_prescribe_and_predict(context_df, even_heuristic, pct=pcts[even_idx])\n", + "perfect_result = trained_prescribe_and_predict(context_df, perfect_heuristic, pct=pcts[perfect_idx])" ] }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 56, "metadata": {}, "outputs": [], "source": [ @@ -1014,12 +3788,12 @@ }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 57, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1048,7 +3822,7 @@ }, { "cell_type": "code", - "execution_count": 89, + "execution_count": 58, "metadata": {}, "outputs": [], "source": [ @@ -1062,7 +3836,7 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 59, "metadata": {}, "outputs": [], "source": [ @@ -1072,7 +3846,7 @@ }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 60, "metadata": {}, "outputs": [], "source": [ @@ -1097,7 +3871,7 @@ }, { "cell_type": "code", - "execution_count": 92, + "execution_count": 61, "metadata": {}, "outputs": [ { @@ -1114,7 +3888,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1132,7 +3906,7 @@ }, { "cell_type": "code", - "execution_count": 95, + "execution_count": 62, "metadata": {}, "outputs": [], "source": [ @@ -1154,7 +3928,7 @@ }, { "cell_type": "code", - "execution_count": 96, + "execution_count": 63, "metadata": {}, "outputs": [ { @@ -1166,11 +3940,10 @@ "Average difference in change for these points: nan\n", "Average difference in ELUC for these points: nan\n", "\n", - "Number less change better ELUC: 1\n", - "Max difference in ELUC with less change: -0.15837669372558594\n", - "Number of points where trained prescriptor prescribes less change than perfect heuristic AND produces better ELUC by more than predictor model MAE: 1\n", - "Average difference in change for these points: -0.09715202450752258\n", - "Average difference in ELUC for these points: -0.15837669372558594\n", + "Number less change better ELUC: 0\n", + "Number of points where trained prescriptor prescribes less change than perfect heuristic AND produces better ELUC by more than predictor model MAE: 0\n", + "Average difference in change for these points: nan\n", + "Average difference in ELUC for these points: nan\n", "\n" ] } @@ -1182,7 +3955,7 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 64, "metadata": {}, "outputs": [], "source": [ @@ -1207,12 +3980,12 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 65, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1241,7 +4014,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 66, "metadata": {}, "outputs": [], "source": [ @@ -1270,7 +4043,7 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 67, "metadata": {}, "outputs": [ { @@ -1296,12 +4069,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "[0.8388562303332646, 0.5854667554767994, -0.31130711025256974, -0.30117062501444974, 0.05660403913575969, -0.09030185555751513, 0.14726688429424883, 0.1491579890918708, 0.3947318678325992, -0.340249071090089, -0.20447384408636288, 0.01551225755486502]\n" + "[0.9059005993480254, 0.5011587606004066, -0.31973205797930904, -0.3059206272223369, 0.07049172159692892, -0.10795210782289759, 0.1576329101792274, 0.14580177100167327, 0.3985471113103744, -0.34303557055794415, -0.2238433660617915, 0.014087250251697304]\n" ] }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAbcAAAE5CAYAAAATLW5DAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAAwzElEQVR4nO3dd7wcVd3H8c83CUgN4ANGepCmIfTQQW4QFUXBQjUiRUVEBB+K4KMiYgOVh8eCAqJSBQEVIqChSCIgLaFJlQDBEIqUAJEiBH7PH+csmWx2793cO7ubO3zfr9d93Z2y55zZKb85Z87MKCIwMzOrkiHdLoCZmVnZHNzMzKxyHNzMzKxyHNzMzKxyHNzMzKxyHNzMzKxy+h3cJG0j6b4yCzOYSQpJa/Tzu+MkXV52mezNS9Ixks7udjm6TdLakm6TNEvSwd0uTysk3SWpJ38ubT1K6pH0yAC+f7qkb5dRlk7oM7hJmiZp+/rxEXFNRKzdnmLNP0lrSbpA0lOSnpN0h6RDJQ3tdtmKJI3MgXBYbVxEnBMR72tDXj2SXpf07/w3Q9I35+P7g2JjlvR+SX/NB7AnJU2StFMJ6ZZ5YFnggo2k1fL28fNul6UZSRMlfWYASXwZuDoiloyIHzdJ/+W8fzwl6feSlh9AfgMWEetExMRO56vkYEl3SnpB0iP5mLpup8tShkHXLFkMCoVxqwM3AtOBdSNiKWBXYAywZAnpzzNuEHk0IpaIiCWArYFPS/pIl8tUGkm7ABcAZwIrASOAo4EPd7Ncg8SngJnA7pLe0u3CtMmqwF19zHNQ3j/WApYGTqyfoRPHgAXgOPMj4BDgYOCtpN/jImDHLpap/yKi1z9gGrB9g/E9wCN18x0O3AE8B/wWWKQw/UPAbcCzwN+A9QrTjgIeAGYBdwMfLUzbB7iOtME9DXy7QVnOBi7tYzl2Im3kzwITgXfVlf3IXPb/AGsAAXwa+Cfw1zzffsA9pAPCBGDVQhoBrJE/7wjcCjxPCrjHFOb7Z5733/lvi7yM1xbm2RK4Of+ONwNbFqZNBL6Vf5NZwOXAsk2Wea51lMedD/xPYfidwBXAM8B9wG55/P7Aq8AruZx/BPYF/lj47v3ABYXh6cAGvaWbp70F+GH+LZ4ATgYWLZYZOAz4F/AYsG+T5VNO44he1vsQ4GvAwzm9M4Gl8rSReV3sndN5CvhqnrZDXvZX8/LfnscvBfwyl2sG8G1gKLAwafv+Yp5vaF5HRzdLq0FZ+9oPrs2/20zgIeADhemrAZPyd68Afgqc3cvvopzX5/M62KVuegAH5nU8i7TNrU7ad5/P29HChfk/C0zN63s8sELdbzysbhv+TF/LBXwHeA14Of9uP52ffRv4S93312rw3TfKkoe/ANzZ5LgwDNg8/wbPArcDPXXr6MH8ez0EjKv7fe4prNuNesljGvmYCxwDXEg6ns4CbgHWL6S7AvA74Mmc58GFaYsCp+ff9W7gCOqOB4V518y/1aa9bDOnAycBl+ay3AisXpj+I9Ix4HlgCrBNYdoxpG3mzPzdu4AxhekbkY6Zs0gnq7+lcKynl/jRtLx9zjB/we2m/GO/Na/IA/K0DUkHls1IO/3eef635Om75u8NAXYHXgCWL2wws4Ev5hW/aIOyPE6TA2CevlZO873AQqSmiqnknTOX5TZg5bxBjCTtkGcCi+dxO+fvvCuX42vA3+oOBmsUfpt18/KsRzp4fKSXnX0fcnDLv91MYK+cz555+L8KO+MDeZkWzcPHNVnu+nW0JumAvF0eXpy0Me6b89qQdIAfVdiYixvYO0gb15C8vh6upZ+nzczT+kr3RNIB8K2kmvUfge8VyjwbODavqw8CLwLLNFi+d+bfcrVe1v1+eb29A1gC+D1wVt26+EX+LdcnHWBqB8djqAsQwB+AU/Iyvo20zX8uTxudf4N3AV8FbgCGNkurQVn72g9eJR0kh5KC0qOA8vTrgf8lnTi8m3SQ6C24bZOXdRngJxROWgrb88XAcGCdPO9V+XdcinSw3DvPu11evxvl/H/CnBPC2m/cW3DrbbnemLef+3Zf3y+WZVlSQKxtH9OY+7iwIukE+4N5Hb03Dy+Xt4fngbXzd5cH1ims1xnAJqSTijXIJ8b1edQfc0nbzavALnn5DicFsYVyGaaQTqAWzuvmQeD9+bvHAdeQ9rOVgTtpHtwOAB7uY/s8PS/vpqT9+hzgvML0TwL/lacdRjouL1JYjpfzbzcU+B5wQ562MOlYckhero+RTga/3Ur8aFre3ibW/9B9HDinAZ8sDH8fODl//jnwrbrv3wds2yTP24CdCxv/P/so46vADr1M/zpwfmF4SN7Yegpl368wfSRph3xHYdyfgE/XpfEiczbSN4Jbg/z/Dzixl519H+YEt72Am+q+fz2wT2Fn/Fph2oHAn5vk2wO8TgpIz+d8f8+cHX934Jq675wCfKOwMX+7bvp00kFsD+BU0sH9naRANr6vdEk79wvMfca3BfBQocwv1f0+/wI2b7B8W+VlWqTR8ud5rgIOLAyvnbeXYYV1sVJh+k3AHoUd8uzCtBGkg/yihXF7kq7p1IYPI23bM4E1C+PnSquVP+bdD6YWpi2Wy/52YBXSCcHihem/6S0/4DTgosLv/yrwtsL0ALYqDE8BjiwMnwD8X/78S+D7hWlL5PRG0lpwa7hc9fP2c9/u6/sTSfvxs/l75wDLNTkuHEkOfIVxE0gH28VzGh+n7gQ8z3NIk/znyqMwrhjcbqhbvsdIJyebUXdsBL4C/Dp/fpDCcZHUGtMsuH21mE+TeU4HTisMfxC4t5f5Z5JrmXk5rixMGwW8lD+/O//2Kky/ljnBbb7iR+2v7Gtujxc+v0jayCG1ex8m6dnaH+lMYgUASZ/KPZpq00aTzqJqpveR79OkM6VmarUMACLi9Zzmin3kURy3KvCjQhmfIR2oV6z/kqTNJF2dOzc8RzorWrZ+vlbKmj1cl0+z37mRRyNi6YgYTrqe8BJwRmGZNqtbL+NIB8xmJpEC0Lvz54nAtvlvUgvpLkc6gE0pTPtzHl/zdETMbmEZn87/W173+fMwUqCqafX3XJV0ZvlYoeynkGpwNWfk+S6LiPt7Kdc8WtgP3ihnRLyYPy5BWsaZEfFCYd76baiYz6Kk2sQ5Oa3rSc2yn6ib9YnC55caDNd+p/r969+kdTPPvtFEs+VqRSv7dl8OzvvIihExLiKeLEyrPwbsWrddb02qXb9AOqk7gLR9XCrpnfl7K5NaW5rp6/j2xvS8fI+QlntVYIW68vwPc7btFerSbrpN0PcxtKbpviLpcEn35A59z5Jq+A233/zdRfJ1xhWAGZGjVlb/uzeNH810qkPJdOA7eQOq/S0WEedKWpXULHQQqeltaVL1WYXvx7xJzuVK0hlTM4+SfiAg9Qoi/Tgz+sij/sf+XN0yLBoRf2vwvd+Qmt1WjtS55WTmLE9fyzJXWbNV6sraLxHxXC5brbPFdGBS3TItERGf76WsteC2Tf48iXmDW2/pPkU6MK5TmLZUpAv68+u+nFfL6545tZwnGs8+l/rln06quS1bKPvwiFinMM/PgEuA90vaupe05tLiftDMY8AykhYvjFull/k/Smpu/JmkxyU9TgoGe7eQVyP1+9fipOapGaRaOqQTmpreTp7qzdf+0mTfHoj6Y8BZddv14hFxHEBETIiI95KCxL2k9Vn73uot5tHIyrUPkoaQOk49mtN9qK48S0bEB/PsjxW/S+/bxFXASpLG9FGWhiRtQ2oS3o10CWFpUp+BVrffFfO6qymWu2n86C3RVoPbQpIWKfzNb6+eXwAH5BqNJC0uaUdJS5Kq80G6IIqkfUlnrPPjG8CWkn4g6e05nTUknS1padKFzB0lvUfSQqSmo/+QLky26mTgK5LWyekvJWnXJvMuCTwTES9L2pS5z4ifJDUVvqPJdy8D1pL0CUnDJO1OqsJfMh9lbUjSEqTmxFrvsUtyXntJWij/bSLpXXn6Ew3KOQkYS2p6eYTUpr8D6WB2a1/p5jPPXwAnSnpbLteKkt4/v8uTz/QOBb4uaV9JwyUNkbS1pFPzbOcC/63U7X0J4LvAb+tqhs08AYzMBxQi4jFSB54TCnmtLmnbvBx7ARuTmtoOBs7Iec6TVgP93g8i4mFgMvBNSQvnoNpbb9G9gV+RrgtvkP+2AtZX/7p9nwvsK2kDpV6X3wVujIhpuRY0A/ikpKGS9qP3A329RttgURn7dqvOBj6sdOvJ0Hws7JG0kqQRknbOgf0/pA4sr+fvnQYcLmnjfPxbI5/MtGpjSR/Lx90v5fRvIDWhz5J0pKRFc5lGS9okf+980jFrGUkrkfotNJRbGX4GnJuXaeG8fHtIOqqFMi5JOml8Ehgm6WjSCVQrrid1ZjkoH/N2Jl3Xq+ktfjTVanC7jHS2Xfs7psXvARARk0kXjH9KaoedSjoAEBF3k9rvrydtyOuSepnNT/oPkK4bjATuUmoK/B1ph58VEfeRLnb+hFRz+DDw4Yh4ZT7y+ANwPHCepOdJZ9UfaDL7gcCxkmaRLvaeX0jnRVIvsOuUqtib1+XzNKln0GGkpoIvAx+KiKdaLWudFZTvcyM1S7yV1ERIRMwC3kcKeI+Smg2OJ3UKgHQtZVQu50X5O/8g7bjX5OHnSW3710XEay2meyRpG7gh/5ZXkq6FzbeIuJDUHLRfzusJUg/Gi/MsvwLOAv5KuhD/Mr3s5HUuyP+flnRL/vwp0gXwu0nb8oXA8pJWIV1b/VRE/DsifkPa/k7sJa3icgx0P/gE6RrMM6STvTMbzSRpReA9pOtljxf+ppCah+e79hYRV5Kuff2OdBa+Omnd13yW1FPvaVLnlPkJPD8CdpE0U9I896mVsW+3KiKmkzqW/Q/pID6dtFxD8t+hpG3wGVJLxufz9y4g7fO/IXX0uYi0H7bqYtI2PpN0Tf5jEfFq3t8+RDo5eYi0/KeRmgMBvkna5x8inZSd1Uc+B5OO0SeRrh8+QKrl/7GFMk4gbT//yHm+TN/NrQDkdfUxUu/0Z0nr8xJSEO81fvSm1iPJzMxsgSDpRlKHxF/3N41BdxO3mZlVi6RtJb09N0vuTbqF6s8DSbPbd8SbmZmtTbp8szjpMscu+Rp3v7lZ0szMKsfNkmZmVjkObmZmVjmVu+a27LLLxsiRI7tdDDOzQWXKlClPRcRyfc85OFQuuI0cOZLJkyd3uxhmZoOKpN4ezzXouFnSzMwqx8HNzMwqx8HNzMwqx8HNzMwqx8HNzMwqx8HNzMwqx8HNzMwqx8HNzMwqp3I3cQ/UyKMuLTW9acftWGp6ZmbWN9fczMyschzczMyscroa3CTtIOk+SVMlHdVg+iqSrpZ0q6Q7JH2wG+U0M7PBpWvBTdJQ4CTgA8AoYE9Jo+pm+xpwfkRsCOwB/KyzpTQzs8GomzW3TYGpEfFgRLwCnAfsXDdPAMPz56WARztYPjMzG6S62VtyRWB6YfgRYLO6eY4BLpf0RWBxYPtGCUnaH9gfYMSIEUycOLHfhTps3dn9/m4jAymLmZn1z4J+K8CewOkRcYKkLYCzJI2OiNeLM0XEqcCpAGPGjImenp5+Z7hP2bcCjOspNT0zM+tbN5slZwArF4ZXyuOKPg2cDxAR1wOLAMt2pHRmZjZodTO43QysKWk1SQuTOoyMr5vnn8B7ACS9ixTcnuxoKc3MbNDpWnCLiNnAQcAE4B5Sr8i7JB0raac822HAZyXdDpwL7BMR0Z0Sm5nZYNHVa24RcRlwWd24owuf7wa26nS5zMxscPMTSszMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHK6Gtwk7SDpPklTJR3VZJ7dJN0t6S5Jv+l0Gc3MbPAZ1q2MJQ0FTgLeCzwC3CxpfETcXZhnTeArwFYRMVPS27pTWjMzG0y6WXPbFJgaEQ9GxCvAecDOdfN8FjgpImYCRMS/OlxGMzMbhLoZ3FYEpheGH8njitYC1pJ0naQbJO3QsdKZmdmg1bVmyRYNA9YEeoCVgL9KWjcini3OJGl/YH+AESNGMHHixH5neNi6s/v93UYGUhYzM+ufbga3GcDKheGV8riiR4AbI+JV4CFJ/yAFu5uLM0XEqcCpAGPGjImenp5+F2qfoy7t93cbmTaup9T0zMysb90MbjcDa0pajRTU9gA+UTfPRcCewK8lLUtqpnywk4Vsh5ElB1CAacftWHqaZmaDVdeuuUXEbOAgYAJwD3B+RNwl6VhJO+XZJgBPS7obuBo4IiKe7k6JzcxssOjqNbeIuAy4rG7c0YXPARya/8zMzFriJ5SYmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnlOLiZmVnldDW4SdpB0n2Spko6qpf5Pi4pJI3pZPnMzGxw6lpwkzQUOAn4ADAK2FPSqAbzLQkcAtzY2RKamdlg1c2a26bA1Ih4MCJeAc4Ddm4w37eA44GXO1k4MzMbvIZ1Me8VgemF4UeAzYozSNoIWDkiLpV0RLOEJO0P7A8wYsQIJk6c2O9CHbbu7H5/t5FGZSk7j2b5mJm9WXUzuPVK0hDgf4F9+po3Ik4FTgUYM2ZM9PT09DvffY66tN/fbWTauJ6259EsH7NOGdmObfq4HUtP0948utksOQNYuTC8Uh5XsyQwGpgoaRqwOTDenUrMzKwv3QxuNwNrSlpN0sLAHsD42sSIeC4ilo2IkRExErgB2CkiJnenuGZmNlh0LbhFxGzgIGACcA9wfkTcJelYSTt1q1xmZjb4dfWaW0RcBlxWN+7oJvP2dKJMZmY2+PkJJWZmVjkObmZmVjkObmZmVjktBzdJi7WzIGZmZmXpM7hJ2lLS3cC9eXh9ST9re8nMzMz6qZWa24nA+4GnASLiduDd7SyUmZnZQLTULBkR0+tGvdaGspiZmZWilfvcpkvaEghJC5FeP3NPe4tlZmbWf63U3A4AvkB6iv8MYIM8bGZmtkDqs+YWEU8B4zpQFjMzs1L0Gdwk/RqI+vERsV9bSmRmZjZArVxzu6TweRHgo8Cj7SmOmZnZwLXSLPm74rCkc4Fr21YiMzOzAerP47fWBN5WdkHMzMzK0so1t1mka27K/x8HjmxzuczMzPqtlWbJJTtREDMzs7I0DW6SNurtixFxS/nFMTMzG7jeam4n9DItgO1KLouZmVkpmga3iBjbyYKYmZmVpZX73JA0GhhFus8NgIg4s12FMjMzG4hWekt+A+ghBbfLgA+Q7nNzcDMzswVSK/e57QK8B3g8IvYF1geWamupzMzMBqCV4PZSRLwOzJY0HPgXsHJ7i2VmZtZ/rVxzmyxpaeAXwBTg38D17SyUmZnZQPRZc4uIAyPi2Yg4GXgvsHdunhwwSTtIuk/SVElHNZh+qKS7Jd0h6SpJq5aRr5mZVVufwU3SeEmfkLR4REyLiDvKyFjSUOAkUgeVUcCekkbVzXYrMCYi1gMuBL5fRt5mZlZtrVxzOwHYGrhb0oWSdpG0SF9fasGmwNSIeDAiXgHOA3YuzhARV0fEi3nwBmClEvI1M7OKa6VZclJEHAi8AzgF2I3UqWSgVgSmF4YfyeOa+TTwpxLyNTOzimv1Ju5FgQ8DuwMbAWe0s1AN8v8kMAbYtsn0/YH9AUaMGMHEiRP7nddh687u93cbaVSWsvNolo9Zp3ibtgVNKzdxn09qQvwz8FNgUr41YKBmMPctBSvlcfX5bw98Fdg2Iv7TKKGIOBU4FWDMmDHR09PT70Ltc9Sl/f5uI9PG9bQ9j2b5mHWKt2lb0LRSc/slsGdEvFZy3jcDa0pajRTU9gA+UZxB0oakptAdIqKMplAzM3sTaOWa24Q2BDYiYjZwEDABuAc4PyLuknSspJ3ybD8AlgAukHSbpPFll8PMzKqnpWtu7RIRl5GeV1kcd3Th8/YdL5SZmQ16vdbclPhRW2ZmNqj0GtwiIqirWZmZmS3oWrmJ+xZJm7S9JGZmZiVp5ZrbZsA4SQ8DLwAiVerWa2vJzGzARraji/5xO5aeplnZWglu7297KczeZBx0zNqrz+AWEQ93oiBmZmZlaeWam5mZ2aDi4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXj4GZmZpXTyitvzBYIZb8mxq+IMasu19zMzKxyHNzMzKxyHNzMzKxyHNzMzKxyHNzMzKxyuhrcJO0g6T5JUyUd1WD6WyT9Nk+/UdLILhTTzMwGma7dCiBpKHAS8F7gEeBmSeMj4u7CbJ8GZkbEGpL2AI4Hdu98ac3MylX2rS3g21uKullz2xSYGhEPRsQrwHnAznXz7AyckT9fCLxHkjpYRjMzG4QUEd3JWNoF2CEiPpOH9wI2i4iDCvPcmed5JA8/kOd5qi6t/YH9AUaMGLHxeeed16GlWLD9fcZzpae57opLdS2fTil7ebq5LFXTqXXzZtwGxo4dOyUixnS7HGWpxBNKIuJU4FSAMWPGRE9PT3cLtIDYpx3NHuN6upZPp5S9PN1clqrp1LrxNjD4dbNZcgawcmF4pTyu4TyShgFLAU93pHRmZjZodTO43QysKWk1SQsDewDj6+YZD+ydP+8C/CW61Y5qZmaDRteaJSNitqSDgAnAUOBXEXGXpGOByRExHvglcJakqcAzpABoZmbWq65ec4uIy4DL6sYdXfj8MrBrp8tlZmaDm59QYmZmlePgZmZmlePgZmZmlePgZmZmlePgZmZmlePgZmZmlePgZmZmlePgZmZmlePgZmZmlVOJtwKYlckvfDQb/FxzMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzynFwMzOzyulKcJP0VklXSLo//1+mwTwbSLpe0l2S7pC0ezfKamZmg0+3am5HAVdFxJrAVXm43ovApyJiHWAH4P8kLd25IpqZ2WDVreC2M3BG/nwG8JH6GSLiHxFxf/78KPAvYLlOFdDMzAavbgW3ERHxWP78ODCit5klbQosDDzQ7oKZmdngp4hoT8LSlcDbG0z6KnBGRCxdmHdmRMxz3S1PWx6YCOwdETc0mWd/YH+AESNGbHzeeecNrPAV8fcZz5We5rorLtW1fMzK3taabWedymdBMnbs2CkRMabb5ShL24Jbr5lK9wE9EfFYLXhFxNoN5htOCmzfjYgLW0l7zJgxMXny5FLLO1iNPOrS0tOcdtyOXcvHrOxtzdvZHJIqFdy61Sw5Htg7f94buLh+BkkLA38Azmw1sJmZmUH3gttxwHsl3Q9sn4eRNEbSaXme3YB3A/tIui3/bdCV0pqZ2aAyrBuZRsTTwHsajJ8MfCZ/Phs4u8NFMzOzCvATSszMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHIc3MzMrHK68uBkqxa/E8vMFjQObhXmoGNmb1ZuljQzs8pxcDMzs8pxcDMzs8pxcDMzs8pxhxIzGzTcScpa5ZqbmZlVjoObmZlVjoObmZlVjoObmZlVjoObmZlVjoObmZlVjoObmZlVjoObmZlVjoObmZlVjiKi22UolaQngYc7kNWywFPOZ4HLw/ks2PlUaVmqls+qEbFcm/PomMoFt06RNDkixjifBSsP57Ng51OlZaliPlXiZkkzM6scBzczM6scB7f+O9X5LJB5OJ8FO58qLUsV86kMX3MzM7PKcc3NzMwqx8HNzMwqx8HNzMwqx8FtPkkaLmnJNqY/VNIP25j+8fn/ru3Ko4okvaXbZTCz1rlDSYskbQL8ClgSEPAssF9ETGlDXjdExOZlp5vT/juwHjAlIjZqRx4N8twSGAkMq42LiDNLzkPAOOAdEXGspFWAt0fETSWlf0tEbCTprIjYq4w0e8lrLeAIYFXm/s22a0NenVg3ywFHAqOARQr5lLo8kt4GbAWsALwE3AlMjojXS8xjJWAPYJu6fC4F/lRWXnkb+DkwIiJGS1oP2Ckivl1G+m8GDm4tknQH8IWIuCYPbw38LCLWa0NePwdWBC4AXqiNj4jfl5D2D4DPAksALxYnpSxi+EDzqMvvLGB14DbgtTw6IuLgkvP5OfA6sF1EvEvSMsDlEbFJSenfCXwX+BYp8MyljHVTyOt24GRgCnN+M8o+kergurkc+C1wOHAAsDfwZEQcWVL6Y4GjgLcCtwL/IgXRtUjLdyFwQkQ8P8B8fk3aLy8BJtflMxbYGDgqIv46kHxyXpNI29kpEbFhHndnRIweaNpvFg5uLZJ0a20jK4y7pR21n7wT1YuI2K/EPC6OiJ3LSq+XfO4BRkWbN7RCzerWwsHg9ohYv6T0tybVDHcDxtdNLnvdTImIjctKr5d8OrVupkTExpLuqJ0MSrq5xBOPHwA/iYh/Npg2DPgQMDQifjfAfEZHxJ29TF8YWCUipg4kn5zWzRGxSd32fFtEbDDQtN8shvU9i2WTJJ0CnAsEsDswUdJGABFxS4l5nRYR1xVHSNqqxPSpBTZJw5m7SeqZMvMhNdm8HXis5HTrvSppKGnd1JrCSmuOiohrgWvzM/5+WVa6TfxR0oHAH4D/FMowaNdN/v+YpB2BR0m1rFJExBEAklaLiIfqJq8cEReVlE/TwJanvwIMOLBlT0lanTnb8y60fz1VimtuLZJ0dS+To8zrB41qhGXXEiXtDxwLvEzegUjL8Y6y8sj5XA1sANzE3AfqnUrOZxzphGMj4AxgF+BrEXFBSel/rLfpJTdL1h+gcxaDdt18CLgGWBn4CTAc+GZE1NeAB5pPo/2m9FpwPtE8hjnXRGtN+qWtH0nvID2VZEtgJvAQ8MmImFZWHlXn4LYAkbQFaWP+EnBiYdJw4KNlNbHlvO4HtoiItr5GQ9K2jcZHxKQ25PVO4D2kg81VEXFPiWnXmorfRlpHf8nDY4G/RcSHysqrUzq5btopr/d1gO8z9/XQ4cAREbFOyfndC/w3814TfbrMfHJeiwNDImJW2WlXnZslWyRpKeAbwLvzqEnAsRHxXInZLEzq6DGM1Cuz5nlSTaRMDzB3h5K2qB0o65s/yybpraQL/OcWxi0UEa82/1brImLfnOYVpOtUj+Xh5YHTy8ijk7XDnF5HglgHev6tTbqutjTw4cL4WaTOU2V7LiL+1IZ03yBpaeBT5J6sqTMwlN3Zp8pcc2uRpN+RrlGckUftBawfEb0ekPqZ16oR8XD+PARYYqA9vRrksSHwa+BG5m6SKrunXLH583Xa0IST85lGavaamfNYGngceAL4bFk9DSXdExHvKgwPAe4qjhtA2h2tHUranNRM+C7SidVQ4IU29JjtSM8/SVtExPVlptkkn+NIv9XvmXvfKe26u6S/ATcAf6dw7Tgizmj6JZuLa26tWz0iPl4Y/qak29qU1/ckHUBq8rgZGC7pRxHxgxLzOIV08Jxr52mDI4DR7W7+BK4ALoyICQCS3gd8nBTAfwZsVlI+V0mawJwa4u7AlWUkXKgdXk6baod1fkq6Z+sCYAypprBWG/JZLCJuqtU+stltyOdWSV8gNVEW76crrSdrVtuWii8PDaDM+/YWiYhDS0zvTcfBrXUvSdo695qrXVR+qU15jYqI53MniT+R7uGZApQZ3Bbq0M7TkeZPYPOIeKMJKiIul/TDiPicSny6SEQcJOmjzGmePjUi/lBW+tnKtcCWPQGsUnIeAETEVElDI+I14NeSbgW+UnI2ner5dxZwL/B+UmvBOKC06641ETG27DQbOEvSZ0n31LWzx2xlObi17gDgzHztDVLz195tymshSQsBHwF+GhGvSiq7/fhPucnwj7R35/kK8DdJbW3+JHUzPxI4Lw/vDjyRbw8o8wkVq5GeRPGHPLyopJEl92JrW+2wzov53qzbJH2fFHDa8Ui+L5B6/r1T0gxSz79xbchnjYjYVdLOEXGGpN+QemmWqkPX318hncx+lUJvZqDU5vwqc3BrQT5A7hUR6+eOEZR9DazOKcA04Hbgr5JWJXUqKdOe+X/xLL0dO0+nmj8/QTrgXJSHr8vjhpJuvC7LBaTrYTWv5XGl3JAMHasdQrpuPAQ4iNT7b2VSU25p8r5zYERs34Gef7XOQ89KGk265vq2NuTzK9L199p2tRep+bvM6++HkYJ1u5vzK8sdSlqkNj7vscX8h0VEO65TtJUaPNllMGv0lIgyn4SS01sNeCwiXs7Di5J6Gk4rK49CXgsD7ySd2NyXb0QuO4+O7DuSPgP8jvTs1F+Teh4fHREnl5xPo22g1KeH5OuuH4mITjTpV5Jrbq27VdJ42vC8x0bykxzmujBOuo4w0HS3i4i/NOt23obl6UjzZ+5ufjjzPgS47IcNPylpp9oNyJJ2Bso+u2577RDe2MZOJl0XFbCapM+1oZt7R/adiDgtf5xEe5vvOnH9/QVSc/HVtLc5v7Ic3Fq3CPA0c/eIClJ34FJJOhlYjNQF/DTSPW6lPN0e2JbUTPjhBtPasTydav68gHSgPo3CjbVtcABwjqSTSMvxCKmXYZmGFWtQEfFKrmGV7QRgbORnIeZOH5eSOjGVqa37jqReO0ZFxP+WkU/B54Ez8rU3Ac8A+5Scx0XMaWK3fnBwa90Q4JCIeBZA6anzJ7Qpry0jYj2lB81+U9IJlHTAiYhv5Huz/hQR55eRZh/5rdbuPLLZEfHzdmcSEQ8Am0taIg//uw3ZdKJ2CDAr5n7I74OkG59LVbvFoY3a9n7FRiLiNqCt1999P9vAObi1br1aYAOIiJn5Ruh2qDVxvChpBdJZ7/JlJR4Rr0v6MtC24NaF5s+OPGxY0gjSq29WiIgPSBpFeoxZmQ9TbmvtsLBOJku6jLQdBLAr6b7KUklaBPg0bbr/LCK+WUY6fWlWQyw8PWTANURJ50fEbkrvXazvEBFlXtutOge31g2RtExEzIQ3HvfUrt/vkvz4ne+T7m+D1NxWpislHU56z1bxOkhZwaDTzZ+12zKKzxZsR/Pn6aTOCl/Nw/8g/YalBbcO1A6L6+QJ0roCeJK5r/GWpa33n0n6GnBSbd9sMH070o3klwwwq07UEA/J/+9h7m1ZpOOBtci9JVsk6VPA/5Cu7UA6y/1ORJzVhrwWJbXrb0M6QF8D/LzWe66kPB5i3jNDynwsVm7+3KUTzZ+dog68Z6sTtcPcRf/giDixz5kHntetEbFhbmZfL9/DeU1ZPShzs+2XSY94u4U5QXpN0lsPrgS+GxFPlpFfJ6jxGw7eeB+e9a0dN2xWUkScSbqP5Yn897F2BLbsDFITzo9Jz/4bBZxZch6jgJNI99LdlvMp9enpEfE66aDTEZJGS9pN0qdqf23I5gVJ/8Wcp21sDpR58y6k2uEEYIU8/A/SmyJKk59IsmefM5aj/v6zpSjx/rOIuDgitiI1595FurfxeeBsYNOI+O8yApukr+Vr7c2mb6f0ep+B5PH53CS5tqQ7Cn8PAXcMJO03G9fcFkCS7o6IUX2NG2Ae55MOAOfkUZ8AloqIMm94rj1k9ina1/xZy+cbQA8paF8GfAC4NiJKfZuC0stpfwKMJt3IuxypdlragacTtcOc5onAQsy7bsp88W7x/rN1SYF7CeDrEXFKmfnU5Vn6A8c7UUPMPTCXAb5HeuxezSw/emv++JrbgukWSZtHxA0AkjYDJpecx+i6YHm1pLtLzgPSo6MCOLBufNnXwnYB1gdujYh9c9Pe2SXnAbA6KXDWnuaxGeXvR52oHUI6IAPUOmSI8h8AXLz/7K80WO+S9i6jd6DS47ba9sDxiLgYuFjSmsBWpE5etRri/hEx4Hvd8iO8nqNzterKcnBbMG1Meh7jP/PwKsB9tR5UJbW7dyKAQqpJHQhszZzrh6U+MSJ7OfcCnZ27aP+LFIDK9vWIuCA3T40Ffkh6V1lZbx0AOBQYD6wu6Tpy7bDE9GsmNhjXjaacQ5jzKqmB6MQDx4mI+4H7Ya4aYrseom795OC2YNqhA3l0IoBCOmg9T7p+CKn58wxKfN6jUl/sO3IP01+QDmj/Btrxbq/aDeI7Ar+IiEsllfXSzZpO1A4h/UY1i5Be+Fn6U/RboL5naUknHjje9hqilcPX3N6klB7G3FTkl6WWkE/brx/mNP8eEevmzyOB4WVeByvkcwkwA3gvsBHpnsSbyrz/qNCrcGvgW6Ta4dERUWbtsFG+bwEmRERPO/NpkO88PQP7mc7BwJGkTlI7kk7Yzo6IbQaadl0+t0XEBrmGuBG5huiejAsW95Z8k4qIh3v7KzGrW/I1I6CtzZ+3SNoEICKmtSOwZbuRejK+P9/U/1bmvh+pDPPUDklvym63xYCVOpBPvVJqbhHx44hYMSI+GMnDpKbjshVriOMj4lW605xrvXCzpLVbp5o/NwPGSXqY1PNPJacPKcEXKdyAHumlomW/eHOGpFNItcPjc42q9BPRuqdgDCVd2xvww7n74boyEsmdcL7BnOu715KW5+ky0i/oxCupbIDcLGlt1cHmz4b5lFwL7QhJi5Guu/49Iu6XtDywbkRcXnI+xd9sNvBElPhapWaPq6op43FVdfldQeqRWeslOw7oiYjty8ynSd6D8pVUVebgZmZtke89bCpKfiakpDsjYnTduDeuxZaYT8MaYkSUXUO0AXBwM7NKkPS/pFdD1R73tgvpCSWHl5xP12qI1joHNzNrC0k/7m16lPTiTUmzSDUoAYszp0POUODfETG8jHwK+XWkhmgD4w4lZtYuU/qeZeAi4o2n9Su9rWNN2vN2g5rLJe3B3DXECW3Mz/rBNTcz6whJi+Xepu1K/zOkp52sRHoY+ObA3yLiPSWl39Eaog2M73Mzs7aStEV+bum9eXh9ST9rQ1aHAJsAD0fEWGBDSnwmZ0QsGRHDc01xWVKHku1J99I1em+hdZGbJc2s3f6P9KLS8QARcbukd7chn5cj4mVJSHpLRNwrae2yM2lWQwRKqSFaOVxzM7O2i4jpdaNeazjjwDySny96EXCFpIuBdtzn2NYaopXDNTcza7fpkrYEIj+26hDa8IDmiPho/niMpKtJL0X9c9n50KEaog2Mg5uZtdsBwI+AFUkPnb6ced/vV6qImNTG5OtriDNpTw3RBsC9Jc2srSSdAXwpImbm4WWAEyJiv+6WbOAkbUuuIUbEK90uj83hmpuZtdt6tcAGEBEzJW3YzQKVpc01RBsAdygxs3YbkmtrwBs3WvvE2trKG5iZtdsJwPWSLsjDuwLf6WJ57E3A19zMrO0kjQK2y4N/iYi7u1keqz4HNzMzqxxfczMzs8pxcDMzs8pxcLPKkfR2SedJekDSFEmXSVqrn2l9SdJi/fzu0pKa3qws6TVJtxX+RvYjj4/k61lmVuDgZpUiScAfgIkRsXpEbAx8BRjRzyS/BPQruAFL0/uTOF6KiA0Kf9P6kcdHgPkKbpLcS9oqz8HNqmYs8GpEnFwbERG3R8Q1Sn4g6U5Jf5e0O4CkHkkTJV0o6V5J5+R5DwZWAK7OzypE0vskXS/pFkkXSFpC0qqS7pe0rKQhkq6R9D7gOGD1XCv7QSuFl7SxpEm5xjlB0vJ5/Gcl3Szpdkm/k7RYfl7jTsAPch6r5+UYk7+zrKRp+fM+ksZL+gtwlaTFJf1K0k2SbpW0c0m/v9kCwWdwVjWjaf4G6I8BGwDrk97HdbOkv+ZpGwLrAI8C1wFbRcSPJR0KjI2IpyQtC3wN2D4iXpB0JHBoRBwr6Xjg58BNwN0RcbmkfwCjI2KDJuVZVNJt+fNDwG7AT4CdI+LJHHy/A+wH/D4ifgEg6dvApyPiJ5LGA5dExIV5Wm+/zUakp4U8I+m7pC75++XnJN4k6cqIeKG3BMwGCwc3ezPZGjg3Il4DnpA0ifTqkueBmyLiEYAccEYC19Z9f3NSE+B1OYgsDFwPEBGnSdqV9JDgDVosz0vFwCdpNCk4X5HTHwo8liePzkFtaWAJYEKLeRRdERHP5M/vA3aSdHgeXgRYhTY8rd+sGxzcrGruAnbpx/f+U/j8Go33DZECxJ7zTEidTlbKg0sAs/pRBgF3RcQWDaadDnwkv+hzH6CnSRqzmXO5YZG6acVamYCPR8R9/Sin2QLP19ysav4CvEXS/rURktaTtA1wDbC7pKGSlgPeTWpG7M0sYMn8+QZgK0lr5HQXL/TCPB44Bzga+EWD77biPmA5SVvk9BeStE6etiTwmNL70MY1KR/ANGDj/Lm3ID8B+GLugENVHmRsVuPgZpUS6ZE7HwW2z7cC3AV8D3ic1IvyDuB2UhD8ckQ83keSpwJ/lnR1RDwJ7AOcK+kOUpPkO5Vee7IJcHxEnAO8ImnfiHia1IR5ZysdSvIrU3YBjpd0O3AbsGWe/HXgRtL1wHsLXzsPOCJ3Clkd+CHweUm3kq4rNvMtYCHgjvwbfauv8pkNJn78lpmZVY5rbmZmVjkObmZmVjkObmZmVjkObmZmVjkObmZmVjkObmZmVjkObmZmVjkObmZmVjn/DzngfpzUfQN7AAAAAElFTkSuQmCC", + "image/png": "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", "text/plain": [ "
" ] @@ -1319,7 +4092,7 @@ }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 68, "metadata": {}, "outputs": [], "source": [ @@ -1339,12 +4112,12 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 69, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1356,7 +4129,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1368,7 +4141,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1380,7 +4153,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1392,7 +4165,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEWCAYAAABrDZDcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAABR90lEQVR4nO2dZ3hU1daA35VJaIp0VHovAZQmiJHOFRFRQFGwopQLiIIgCIIIiFSRoqJUFUWaIoLyiQp6uXIpoqFIU6SHIiAgSEvZ3499gpMwk8wkM3Om7Pd58mRmn7bOmXP2OnuttdcSpRQGg8FgiFyi7BbAYDAYDPZiFIHBYDBEOEYRGAwGQ4RjFIHBYDBEOEYRGAwGQ4RjFIHBYDBEOEYRGAwhhGjeE5HTIrLRbnk8QUReEpFZ1ucyIqJEJNpH+94vIi2yuG0TETnsCzlCHaMI0iEij4jIJhE5LyJHReT/ROROH+z3fREZ5SMZfbavcENEvrc6yZx2y+IKEeksIj9kYxd3Av8CSiil6rnZf7J1//4lIptF5N5sHC/bKKVGK6W62nFsEaknIitE5IyI/CkiG0XkKTtkCWaMInBCRPoBk4HRwI1AKWAacL+NYmUbX719BTsiUgZoCCjgPnul8Rulgf1Kqb8zWGedUup6ID8wG1gkIgXSrxSI+8LOe09EGgCrgf8AFYBCQE+glV0yBS1KKfOnZ1fnA84DHTJYJydaURyx/iYDOa1lTYDDQH/gD+Ao8JS1rDuQCFyxjrHcai8GfAqcAPYBz1ntBa19tbG+Xw/sAZ5wty8XsirgGeA3YJ/VNgU4BPwF/AQ0dFp/OLAImAucA7YDdZ2W1wbirWWLgYXAKKfl9wKbgTPA/4Bb3Mj1DvB6urbPgX7W5xeBBOs4u4HmXvyGw4C1wBvAF+mWvY9W6v9nXbe1wE3Wb3ga2AXUclq/KvC9dT7bgfucln0PdHX63hn4Id2172Fd+zPA24BY+7wEJFsynHFzHsWAZcCf1u/ezWrvkm77ES62TS/LdZY8da3f+BPgI+se6Iq+72ej79cEYBTgsLatgO5EzwIngYVO+60GfGPJeBx4yek+Sn+M4cBH1vIyljzd0c/QUeAFp/1GAYOA34FT6HuyoNPyx4ED1rIhwH6ghZvr+APwdgb3SxPcPLPW8tboe/4v9HMz3GlZ6nk8CRy0rs8Qp+W5gQ/Q99ZOYCBwON1vfM2zb1v/Z+fBg+kPuBtIAqIzWGcksB4oChRBd3ivOt1USdY6McA9wAWggLX8fdJ2nFHozngYkAMoB+wFWlrL7wKOWceaCXzitG2afbmRVVkPakEgt9X2GPqtKNq6+Y8Buaxlw9GdzD2AAxgDrLeW5bAevj7WubVHK6JR1vJa1oNU39r2SesBzelCrkbWQyXW9wLARevBqGwtK2YtKwOU9+I33AP0AuqgleWN6a7ZSWtZLvSb4j60cnWgO8DvrHVjrH29ZJ17M7Riqmwt/57MFcEX6DfyUuiH/W5X67o5jzVopZULqGlt38yT7Z2XW79zH0v2fNZvnAi0Rd9/uYHPgOlohVEU2Aj829p+PrqzjbJkudNqz4vuNPtb7XmB+k73UfpjDOdaRTDfOmYN6/xaWMv7oJ+xEugXr+nAfGtZLFoBNrKWvYF+5q5RBEAetMJsmsG1akLGz2wTS74o4Ba0wmub7jxmWud4K3AZqGotH4tWogWsc9mKpQjI5Nm3pf+z68DB9gc8ChzLZJ3fgXucvrdED9NTb5qLOCkSdOd4u/X5fdIqgvrAwXT7Hwy85/T9TWAb+k2tkFN7mn25kVVhdR4ZrHMauNX6PBz41mlZLHDR+tzIkkGclv/AP4rgHSyF6LR8N9DYxTEF/QbVyPreDVhtfa5gXbMWQIyXv9+d6A6osPV9F/B8ums20+n7s8BOp+81sN7Q0ealY0CU0/L5WG+EeKYI7nT6vggY5GpdF+dREt2B5XVqGwO87+H2ndGd2xm04lvPP53scGCN07o3ojuv3E5tnfhHIc4FZqD9EaRbJ97N8dMcw6ktvSKo4rR8PDDb+rwTp1EgcLP1u0ajO84FTsuuQ7+QuFIExdMfx8U6TcjgmXWx/mRgUrrzKOG0fCPQ0fqcpmNHj4xSFUGmz36g/4yP4B9OAYUzsWkWQ78Zp3LAaru6D6VUktP3C2izjitKA8UsJ9YZETmDfgO90WmdGUB1dCdwyrPTSMMh5y8i8oKI7BSRs9bx8gGFnVY5lk72XNb1KAYkKOuOdbHv0kD/dOdSkrTXBgBrHwvQnQnAI8A8a9keoC+64/hDRBaIyDX7cMOTwNdKqZPW94+tNmeOO32+6OJ76m9VDDiklEpxWn4A3bl4Svpr6e4+SE8x4E+l1LlsHHu9Uiq/UqqwUup2pdS3TsvS/24xwFGn3206emQA2pwhwEYR2S4iT1vtJdEvRe44lMEyV+s4P0elgc+c5NmJVow3Wutc3U5pP4m75+I0kIJWJBnh9pkVkfoi8p2InBCRs2hzX+F027v7ndPIyrXXPbNnP6AYRfAP69BvR20zWOcI+kdMpZTV5gkq3fdDaNt9fqe/vEqpewBExIFWBHOBXiJSIYN9ZXpMEWmIfrAfQg9986Ntv+LBfo4CxUXEed2S6c7ltXTnkkcpNd/N/uYDD4pIafTb0adXBVbqY6XUnejrrIBxmQknIrmt82osIsdE5BjwPHCriNzqwfml5whQUkScn49S6FERwN9o00MqN3mx78x+uyNAQRHJ6+bY2SW9Mr+MHkWl/m43KKWqASiljimluimligH/BqZZ9+EhtDnDk2O4w/n+cX6ODgGt0t1LuZRSCej78Op2IpIHbeq8VgClLqCf6Qc8kMUdH6N9NSWVUvmAd/HsecGStYTT9/TPi9tn3w6MIrBQSp1FDz3fFpG2IpJHRGJEpJWIjLdWmw8MFZEiIlLYWv8jDw9xnLQPz0bgnIi8KCK5RcQhItVF5DZr+UvoB+ppYAIw11IOrvblCXnRJoMTQLSIDANu8HDbdei3st4iEi0i9wPOoYszgR7WG5SIyHUi0jpdZ3YVpVQ82mwxC1iplDoDICKVRaSZFfp5Cf2WnuJqH+loa8kXi7ap10Q7Zv+L9gF4ywb0291A6x5oArRBj2RAO8XbW/dIBbQT11OOAyVEJIerhUqpQ2jf0xgRySUit1j79/Q+8xil1FHga2CiiNwgIlEiUl5EGgOISAcRSe3MTqPvxxS0/+NmEekrIjlFJK+I1Pfy8C9b168a8BQ6+AB0Z/ua9ZKA9azdby37BLhXRO60rt9IMu7DBgKdRWSAiBSy9neriCzIYBtn8qJHZ5dEpB569Oopi4DBIlJARIoDvZ2WZfbsBxyjCJxQSk0E+gFD0R3mIfQPuNRaZRSwCe342Qb8bLV5wmwg1hoKLlVKJaMjbWqinZapHWM+EaljyfGEtd449EM4yNW+PDz+SuAr4Ff0UPwSng3hUUpdQTuIu6Btz4+hO4PL1vJNaFv/W+gOYw/aVp0RH6N9AR87teVEO9lO8o+jfDCAiDwqItvd7OtJtH31oPUWe0wpdcyS51FvQxit822DDjM8iXbcPqGU2mWtMgltmz6OjgyZ58XuV6OjkI6JyEk363RC26CPoJ25r6Qz7/iSJ9AOyx3o3+4T/jGn3AZsEJHz6DfjPkqpvZbZ6l/oa3QMHR3V1Mvj/gd9n6xCR5F9bbVPsY71tYicQ/s46gMopbajI+E+Rr9xn0ZH/bhEKfU/tKO/GbBXRP5Ej7JXeChjL2CkJccwdOfuKSMt2fYB36Kva+rz4vbZ92L/PiU1csNg8AoR2QC8q5R6z25ZDIZgR0R6oh3Jje2WxRVmRGDwCBFpLCI3WaahJ9HhdF/ZLZfBEIyIyM0iEmeZ2yqjQ20/s1sud0TEjFODT6iMHhpfhw6Ne9CyMRsMhmvJgY7AKos2py5AmxiDEmMaMhgMhgjHmIYMBoMhwgk501DhwoVVmTJl7BbDYDAYQoqffvrppFKqiKtlIacIypQpw6ZNm+wWw2AwGEIKETngbpkxDRkMBkOEYxSBwWAwRDhGERgMBkOEYxSBwWAwRDhGERgMBkOE4zdFICJzROQPEfnFzXIRkakiskdEtopIbX/JYjAYDAb3+HNE8D66/KM7WgEVrb/u6CpXBoPBYAgwflMESqk16MLW7rgfmKs064H8IpJZNaHs8fvvcOmSXw9hMBgMvubvv/9m//79ftu/nT6C4qTNh38YN+X4RKS7iGwSkU0nTpzI2tGSkqB1a6hZE9auzdo+DAaDIcCsXr2aW265hfbt25OS4kmdJu8JCWexUmqGUqquUqpukSIuZ0hnTnQ0TJmiRwQNG8Jzz8H5874V1GAwGHzEmTNn6NatG82bNycqKopJkyYRFeWfLttORZBA2jqeJfBdXVbXtGwJv/wCvXvDW29B9eqwb59fD2kwGAzekpyczB133MGcOXMYOHAgW7dupXFj/9W0sTPX0DJ0DdwF6FJ0ZwOS3/7662HqVHj4YXj3XShVSrcrBeJpXWqDwWDwPadOnaJgwYI4HA5ee+01SpYsSd26df1+XH+Gj85HFz2vLCKHRaSLiPQQkR7WKivQBU72oIuf9/KXLC6Ji4MPPwSHA06cgFtvhSVLAiqCwWAwACil+Oijj6hUqRKzZs0CoF27dgFRAuDHEYFSqlMmyxW6ELX9nDmjfQgPPKD/3noLbrrJbqkMBkMEcOjQIXr06MGKFSu4/fbbiYuLC7gMIeEs9jsVK8KGDTBmDHzxBcTGwvvva3ORwWAw+In58+dTrVo1vv/+eyZPnswPP/xAbGxswOUwiiCVmBgYNAi2bIFq1WD5cuMzMBgMfqVAgQLUr1+fX375hT59+uBwOGyRI+RqFtetW1f5vTBNSgr8/TfkzQu//gorV8Izz4CfQrcMBkNkkJSUxKRJk7hy5QpDhgwBtH9AAvDSKSI/KaVcOh1Mz+aKqCitBECbiJ57Ts892LnTVrEMBkPosmXLFm6//far4aCpL+GBUAKZYRRBZrz2GsydC7t26VnJo0dDYqLdUhkMhhDh8uXLvPzyy9StW5dDhw6xePFiFixYEBQKIBWjCDJDBB5/HHbsgLZtYcgQeOMNu6UyGAwhwm+//ca4ceN45JFH2LFjBw8++GBQKQEIweL1tnHjjbBwoVYKTZvqtj17oHhxyJ3bXtkMBkNQcf78eT7//HMeffRRqlevzq5duyhXrpzdYrnFjAi85d574brr0iax++EHu6UyGAxBwjfffEONGjV4/PHH2Wn5FYNZCUCEKIKl8QnEjV1N2UFfEjd2NUvjfZDSKDoa3n4brlzRjuTeveHcuezv12AwhCSnT5+mS5cu3HXXXeTIkYP//Oc/VK1a1W6xPCLsFcHS+AQGL9lGwpmLKCDhzEUGL9nmG2XQogVs2wZ9+sC0aXr+wd692d+vwWAIKZKTk4mLi+ODDz5g8ODBbNmyhYYNG9otlseEvY9gwsrdXExMTtN2MTGZCSt307aWy/IH3nH99TB5sk5i9847ULq0bk9J8dm8g6XxCUxYuZsjZy5SLH9uBrSs7BvZDQZDtjh58uTVJHGjR4+mVKlS1K4delV3w35EcOTMRa/as0yDBjrMNDWJXY0asGhRttNU+HVEYzAYsoRSirlz56ZJEte2bduQVAIQAYqgWH7XET3u2n3C2bM6kujhh6F9ezhyJMu7ymhEYzAYAs+BAwdo1aoVTz75JFWrVqVRo0Z2i5Rtwl4RDGhZmdwxafN35I5xMKBlZf8dtEIFWL8exo+Hr77SSexmz87S6CC7Ixq/OMoNhgjlo48+onr16vzwww+8+eab/Pe//6VKlSp2i5Vtwt5HkGpLD7iNPToaBgzQk9C6dtUKoUsXr3dTLH9uElx0+pmNaJbGJzB82XbOXPxnFnSqWQnw6PyNb8JgSEuRIkWIi4tj+vTplE71B4YBEZ10LmAdXUoKXLigHcu7d2ul0Lu39id4IOPgJdvSmIdyxzgY076GW1ldbeNM8fy5WTuomc+PazCEG4mJiUycOJHExERefvllIHBJ4nyNSTrngoA6YaOitBIAXRWtb1+4806dtiIT2tYqzpj2NSiePzeC7sQz64xd+RWc8cSsZHwThkgnPj6e+vXrM3jwYHbs2BFUSeJ8TdibhtyRWUfnt5HCq69C1ap67kGtWjB0KLz4IuTI4XaTtrWKe3X8zDp6TxzlAYu2MhiCjEuXLjFy5EjGjx9P4cKF+fTTT2nfvr3dYvmViB0RuOvQUkcGfhspiMCjj+rRQPv2MGwYTJrkm31bZNTRe+ootyXaymAIAvbs2cPrr7/OE088wc6dO8NeCUAEKwJ3HZpDJDAmkaJFYf58+PJL7S8AXQTnwoVs79pVpBRAgTwxLs1KriKLbIm2Mhhs4vz583z44YcAVK9end27dzNnzhwKFChgs2SBISKcxa6cwoBLZ6g727oA+8a2zrLcmZKUpFNUpKTArFnQuHG2duepIzwjpzDYEG1lMASYlStX0r17dw4dOsT27dtDJj+Qt2TkLA57RbA0PoEBi7eQmPLPecZECRM63Apc29FNWLnbZbimJ5E22Wb1aujWTecr6tEDxo2DG27w6yHjxq6273wNBhs5deoU/fr1Y+7cuVSpUoVZs2YRFxdnt1h+IyNFEPbO4uHLtqdRAgCJKYrhy7az+ZW7XL7hunpDDohJpFkzncQu1W/wxRfwn/+AH1PYGqewIRJJTRK3Z88ehgwZwtChQ8mVK5fdYtlG2CsC5wlVnrTbNgEtlTx54PXX4aGH4N13/ZLEzpmsTlgzGEKREydOUKhQIRwOB+PGjaN06dLUrFnTbrFsJ2KdxRnRtlZx1g5qxr6xrVk7qJk9dvF69WDOHD3p7I8/oHp1WLAgS2kqMkozYZzChkhAKcV7771HpUqVmDlzJgD333+/UQIWRhFkg4Dl8Tl3Tk9I69RJp6xI8Pw4mU2cy8qENYMhlNi/fz8tW7bk6aefpkaNGjRNLTVruErYm4YEcPUOnd25gemjbbzN4+MV5cvDunUwZYqegBYbq81HXbvqeQkZ4Ek9Bm8nrBkMocKHH35Iz549ERGmTZvGv//9b6L8YGINdcL+irgzpGQ3VirgKRgcDujXTzuT69SBr7/OVAmAcQYbIpsbb7yRRo0asX37dnr27GmUgBvCfkTgL2zrYMuXh1Wr4O+/9fddu/SktL59XSaxM85gQySRmJjI+PHjSU5OZtiwYdx1113cdddddosV9IS9eswT4/oU3bV7iq0pGET+SWI3bx688IKukPbLL9esapzBhkjh559/5rbbbmPo0KHs3r2bUJsjZSdhrwhyRLtO9eyu3VOCpoMdOVKnqti3D2rXhuHD4cqVq4uNM9gQ7ly8eJFBgwZRr149jh8/zmeffca8efPCMkuov/CraUhE7gamAA5gllJqbLrlpYAPgPzWOoOUUit8KcNZN/MF3LV7iu3zDVIRgY4doUULbR4aMQJy5YJBg9LIajp+Q7iyd+9e3njjDTp37syECRMiJj+QL/GbIhARB/A28C/gMPCjiCxTSjkn4R8KLFJKvSMiscAKoIwv5fCnjTyoOtjCheGjj+Dxx6FhQ922ezeULKknqRkMYcRff/3FkiVL6Ny5M9WqVeO3334Lq4phgcafpqF6wB6l1F6l1BVgAXB/unUUkJpMJx+Q9SrvbggaE06gaNlSd/xJSXDffVCjBnz3nd1SGQw+Y8WKFVSvXp0uXbqwc+dOAKMEsok/FUFx4JDT98NWmzPDgcdE5DB6NPCsqx2JSHcR2SQim06cOOGVEP6wkYdEQfjoaJgxQ6elaNYMuneHs2ftlspgyDInT57k8ccfp3Xr1uTNm5e1a9eGbabQQOO37KMi8iBwt1Kqq/X9caC+Uqq30zr9LBkmikgDYDZQXSmV4m6/vqxZnBVCrpbvhQvagTxxItx0E6xZo0NQDYYQIjk5mdjYWPbu3ctLL73ESy+9RM6cOe0WK6Swq2ZxAlDS6XsJq82ZLsAiAKXUOiAXUNiPMmWbkKvlmycPjB8PGzZAq1ZQpoxuT3Graw2GoOH48eOkpKTgcDh4/fXX+emnnxgxYoRRAj7Gn4rgR6CiiJQVkRxAR2BZunUOAs0BRKQqWhF4Z/sJMCE7U7duXV3wJjWJXWwsfPxxlpLYGQz+RinF7NmzqVy5MjNmzACgTZs23HLLLTZLFp74TREopZKA3sBKYCc6Omi7iIwUkfus1foD3URkCzAf6KyCfBZIWNTyPX8eChTQtZPbtIFDhzLfxmAIEHv37qVFixZ07dqVmjVr0qJFC7tFCnv8OqFMKbVCKVVJKVVeKfWa1TZMKbXM+rxDKRWnlLpVKVVTKfW1P+XxBWERhVSuHPzwA0yerCOKqlXTtQ+CWwcbIoAPPviAGjVq8OOPP/Luu++yevVqKlSoYLdYYU/YzywG30b5hM1MXYcD+vTRSezq1dMKwczENNhMsWLFaNasGTt27DCZQgNIRNQs9iTKx9Ni72GJUnDxonYs79oFy5fD88/rEFQi/NoY/MqVK1cYO3YsKSkpDB8+3G5xwhq7ooaCAk+ifDIr3hL2iPwz+/jjj2HgQJ3EbutWc20MfuPHH3+kTp06vPLKK+zdu9ckibORsFcErtJLpG8PuZBQfzJiBCxaBAcPQp06nH5hEMkXL6VZJWKvjcEnXLhwgRdeeIHbb7+d06dPs2zZMubOnWuSxNlI2CsCh5uby7k9ZENC/YEIdOgAO3ZAp048tfojumxaes1qEXltDD5h3759vPnmm3Tr1o3t27fTpk0bu0WKeMK+ME2ym+Gmc7sp3uKCQoVg7lz6xlTnq/x6JnL5U4c4krcIF3PkiuxrY/Cas2fPsmTJEp566imqVavGnj17KFmyZOYbGgJC2I8IirvpsJzbwyIk1E806f0okuc6HCnJzPz0VVbOeYZmh7aaa2PwmC+//JJq1arRtWtXdu3aBWCUQJAR9orAk04+bEJC/UDqtbmp4PUMbvUcREcz5+OXaPvWMDh92m7xDEHMiRMnePTRR7n33nspUKAA69ato0qVKnaLZXBB2IePggl/9CkXL+qqaBMmQJEi8N//gpnwY0hHapK4ffv2MXToUAYNGkSOHDnsFiuiySh8NCIUgcEP/Pyzno38zjt6clpysv5viGiOHTtG0aJFiYqK4osvvqBMmTJUr17dbrEMRPg8AoOfqF1b1ztwOOD4cahaFT780KSpiFBSUlKYPn06lSpVYvr06QDce++9RgmECEYRGLLPhQvaTPTEE3DPPXoOgiFi2LNnD82bN6dHjx7cdttttGzZ0m6RDF5iFIEh+5Qtq30FU6fq/9Wqwdtvm9FBBPDee+9Ro0YNfv75Z2bOnMm3335LuXLl7BbL4CVGERh8Q1QUPPss/PIL3HGHroRmZoqGPaVKlaJly5bs2LGDrl27mtnBIUpEOIszixoyUUU+xjmJ3c6dsGwZ9O9/NYmdIXS5fPkyY8aMISUlhZEjR9otjsELItpZnFnSNJNUzQ84J7FbuBAGDYL69WHzZlvFMmSPDRs2UKdOHUaMGMHBgwdNkrgwIuwVQWYJ5UzCuX/wZd2GqwwfDp98AgkJulzmkCFw6VKmmxmCh7///pt+/frRoEEDzp49yxdffMH7779vzEBhRNiP1TNLKGcSzmnS121IHRkB2TeTPfAANG0KL7wAo0dD3rx6lJCJPMZcFxwcOHCAadOm0aNHD8aOHcsNN9xgt0gGHxP2IwJ3ydEUEDd2Nflyx3i1Xbji95FRwYIwZw6sWgXPPafbdu7U9ZPTYcx19nPmzBlmzZoFQGxsLHv27GHatGlGCYQpYa8IXOUaSiXhzEX+vpJETFTaIW4kJpwL2MioWTPtP0hKgvvvh+rV4eu0paqNuc5ePv/8c2JjY+nRo8fVJHElSpSwWSqDPwl7ReCcUM4VicmK63NFR3zCOXcjIL+NjKKj4b33IHduaNkSnnoK/vwTMOY6u/jjjz/o2LEjbdu2pUiRIqxfv94kiYsQwt5HALDpwJ8cO+veQXnmQiLxw+4KoETBx4CWlV3WdvbryCguDuLjYdQoGDsW/u//4IcfTH0IG0hOTiYuLo6DBw8yatQoBg4cSEyMa7OpIfwI+xHB0KXb+Gj9QbcFasB0MGBjKu5cubQi2LQJ2raFcuUY0LIy16Wz5kWiuS4QHDlyhJSUFBwOB1OmTCE+Pp4hQ4YYJRBhhP2EsvKDV2SoBHLHOILKFGSiZYDjxzlftz5Tbn+IWeUaUaxAnsi8Dn4kNUnciy++yNixY+nVq5fdIhn8TEYTysLeNJSREigeZB2tX0M4Q4mLF7m+TEmGfDKBIf/arLOclomg8/czv/76K926dWPNmjW0aNGCVq1a2S2SwWbC3jSUUfH6tYOaBVUHa6JlLMqUgf/8RyeuW7dORxZNnWqS2PmA2bNnc+utt7J161bmzJnD119/TdmyZe0Wy2AzYa8IOtV3XRvVXbudmGgZJ6KioFcvncSuYUOtEMxM1mxTpkwZWrVqxY4dO3jqqafM7GADEAGmoVFtawAwf8MhkpXCIUKn+iWvtgcTJlrGBaVLw4oV/6Sl2LEDPvsMBg4E49DMlMuXL/Pqq68CMGrUKJo3b07z5s1tlsoQbIS9IgCtDIKx40+PLSGcoYCInm8AsHixzl+0eLGeqVy7tq2iBTP/+9//6NKlC7t27eLpp59GKWVGAAaXhL1pKJSwLYQzlHjlFT0iOH4c6tXTOYsuRqDpLAPOnz9Pnz59uPPOO7lw4QJfffUVs2fPNkrA4Ba/ho+KyN3AFMABzFJKjXWxzkPAcHT6ny1KqUcy2qcpXm8A4PRpGDAAZs+GMWMyTWIXSezYsYPatWvTrVs3Ro8eTd68ee0WyRAEZBQ+6jdFICIO4FfgX8Bh4Eegk1Jqh9M6FYFFQDOl1GkRKaqU+iOj/RpFYEjD99/rWge5c8P27VCqlM5uGmGcPn2axYsX0717d0BPFCtWrJjNUhmCCbsK09QD9iil9iqlrgALgPvTrdMNeFspdRogMyWQVfySZ98QHDRpopVAUpKemVytmk5VEUF89tlnxMbG0qtXL3bv1qHGRgkYvMGfiqA4cMjp+2GrzZlKQCURWSsi6y1T0jWISHcR2SQim06cOOGVECalcYQQHQ1z58L118M998ATT8CpU3ZL5VeOHTtGhw4daN++PTfddBMbN26kcuUIDywwZAm7ncXRQEWgCdAJmCki+dOvpJSaoZSqq5SqW6RIEa8OYCZpRRANGugkdi+/DPPnQ9Wq8NtvdkvlF5KTk2nYsCHLly9n9OjRbNy4kdomgsqQRfwZPpoAOM/aKmG1OXMY2KCUSgT2icivaMXwo6+EMJO0IoycOWHkSHjwQXj3XShfXrcnJelRQ4hz+PBhihUrhsPhYOrUqZQtW9akijZkG3+OCH4EKopIWRHJAXQElqVbZyl6NICIFEabivb6UoiA59k3BAe33ALTpukZyseOQaVKOsIoRNNUpKSk8Oabb1KlShXeeecdAFq1amWUgMEnePSKJCJ5gP5AKaVUNyvap7JS6gt32yilkkSkN7ASHT46Rym1XURGApuUUsusZXeJyA4gGRiglPKpYddM0jJw+bKOJuraVZuMZsyAcuXslspjdu3aRdeuXVm7di0tW7bk3nvvtVukoCUxMZHDhw9z6ZL7+iPhTq5cuShRooRXqcQ9Ch8VkYXAT8ATSqnqlmL4n1KqZlaFzSpZCR81qZ0NpKTAzJl67kFyMrz2GvTpE/T5i2bNmkXv3r3JkycPkydP5vHHHzcTwzJg37595M2bl0KFCkXkdVJKcerUKc6dO3dNMkFfpKEur5R6WEQ6WQe7ICF0ldvWKm46/jDGI0UfFQX//je0bg09esCGDUGvBADKly9PmzZteOutt7jxxhvtFifouXTpEmXKlIlIJQAgIhQqVAhvoys9VQRXRCQ3evYvIlIeuOydiAaD7/G6hkOJErB8uTYXgU5i9+mn8OKLkCNHoMR2y6VLlxg5ciQAo0ePpmnTpjRt2tRmqUKLSFUCqWTl/D11Fr8CfAWUFJF5wCpgoNdHMxh8TJbCg0V0iUzQSmDYMKhbF370WbBalli7di01a9ZkzJgxnDhxglCrHmgIXTxSBEqpb4D2QGdgPlBXKfW9/8QyGDwj2+HBL78Mn3+uJ5/dfrtOb33hgg8lzJxz587x7LPP0rBhQy5fvszKlSuZOXNmxL/ZGgKHR4pARGoDpYGjwBGglIiUF5GQCMweunQb5QevoMygLyk/eAVDl26zWyTbCLd0Gz4JD77vPm0i6tIFJkyAKVN8JJ1nHD58mFmzZvHss8+ybds27rrrroAe3+A7hg0bxuTJk69+HzJkCFMyuZ/Onj1L5cqVr6YH6dSpEzNnzvSnmNfgaUc+DagNbAUEqA5sB/KJSE+l1Nd+ki/bDF26jY/WH7z6PVmpq99DoUaBLwnHmsg+Cw/Ol0+HlT72GNx2m2775RcoWVIv8zGnTp1i0aJF9OzZk6pVq7J3715uvvlmnx8n0mnSpMk1bQ899BC9evXiwoUL3HPPPdcs79y5M507d+bkyZM8+OCDaZZ9//33GR7v6aefpn379vTt25eUlBQWLFjA6tWrqVmzpsv1P/74Y2JjY3nrrbfo3Lkzffr04fTp03Tr1s3TU/QJniqCI0AXpdR2ABGJBUai/QRLgKBVBPM2HHTb7mtFEOxhqhnZ04NJTm9Ildtn171RI/0/ORnatdO1DqZP19FGPkApxaeffsozzzzDn3/+SbNmzahcubJRAmFCmTJlKFSoEPHx8Rw/fpxatWpRunRpNm/enOF2//rXv1i8eDHPPPMMW7ZsCYywTniqCCqlKgEApdQOEamilNob7HZMd/42X/vhQuFtO1zTbfglPNjhgHnztLno3nvhkUdg8mTwMteVM0ePHuWZZ57hs88+o06dOnz99dcmSZyfyegNPk+ePBkuL1y4cKYjAFd07dqV999/n2PHjvH0009z7tw5GjZs6HLd1BFBSkoKO3fuJE+ePJw+fZoSJUp4fdzs4Kki2C4i76BTSQM8DOwQkZxAol8kCyI8edPPztt2oEYSpiayl9SrBz/9pAvfvPYafP01/O9/ULGi17tKTRKXkJDA+PHjef7554kOg9xHhmtp164dw4YNIzExkY8//hiHw5HpiGDSpElUrVqV0aNH89RTT7Fu3TqvZgZnF0/vxM5AL6Cv9X0t8AJaCQR1kHOemCguJKa4bPcET9/0s/q2nd2RhDdKxKTbyAI5cujymA88oE1EqUnsEhPBgwf10KFDFC9eHIfDwdtvv03ZsmWpVKmSn4U22EmOHDlo2rQp+fPnx+FwZLr+7t27mTVrFhs3biRv3rw0atSIUaNGMWLEiABIq/E0fPSiUmqiUqqd9fe6UuqCUipFKXXe30Jmh/Z1XA+x3LWnx9M49axGr2QnTba3tRZMTeRsUL06vPlm2iR2M2e6tTEmJyczderUNEniWrZsaZRABJCSksL69evp0qWLR+tXrlyZnTt3Xi0p+sYbbwRUCYDn4aNxIvKNiPwqIntT//wtnC/4bpfrqdbu2tPj6Zv+gJaVyR2TVvt78radHbt9VpRI21rFWTuoGfvGtmbtoGZGCWSFK1egbFno3h2aN4fff0+zeOfOnTRs2JA+ffrQuHFj2rRpY5OghkCzY8cOKlSoQPPmzamYBROiXXg6s3g28AZwJ3Cb01/Qk10Hqadv+ll923a3/yiRTGP9w9X5G/SUKgWrVulw059+gho14I03QClmzJhBzZo1+fXXX/nwww/58ssvKVWqlN0SGwJEbGwse/fuZeLEiXaL4hWe+gjOKqVCshBsdh2k3tjVsxK94mr/oOc7QMY+A+P8tTFkVwS6ddNlMXv21ApBhIoVK9KuXTumTp1K0aJF/S+HweADPB0RfCciE0SkgYjUTv3zq2Q+Iqsmm1T8bVdPv3+Hi3Bcd+ae7J5bqBMM9agvFizIi1WqMNSaB9C0SBEWVKlC0fz5AyaDwZBdPB0R1Lf+O+eyVkAz34rje3wx4cjfaayd91920Jcu13Fl7vH5ZKoQw+4JcmvWrKFr16789ttv9OjRA6UU8vnnMGIEfPIJzJmjQ1ANhiDHI0WglArqENFwwltzTyTXWrDLR/LXX38xaNAg3nnnHcqVK8eqVato1sx6JxoyBGrW1DUPGjSAvn11DeXrrvOrTAZDdvC4ZrGItBaRgSIyLPXPn4L5imAwH3hDpJt7vMGuetRHjhzh/fffp1+/fmzduvUfJZBK69awfbsuhPPGGzB1ql/lMYQ+b731FhUqVEBEOHnyZMCP72n46Lvo2cTPopPOdUBnIw16shOnbwcm1t9zAqk0T548ybRp0wCoUqUK+/btY+LEiVzn7k3/hhtg2jT44Qc9KgDYtg3OnvW5bIbQJy4ujm+//ZbSpe3pVj31EdyhlLpFRLYqpUaIyEQgJKKIvDUfBEPiuEg293hDIHwkSikWLVrEs88+y5kzZ2jRogWVKlXyvGxkXJz+n5wM7dvrWgfvvgtmbkFYMmzYMAoWLEhfS/kPGTKEokWL0qdPnwy3q1WrVqb7Pnv2LPXq1WPZsmVUrlyZTp060axZM59kKvVUEaT2mhdEpBhwCgiJdIne2NxDIXGcIS3+VJpHjhyhZ8+eLFu2jLp167Jq1aqszwx2OGD+fHj6aV3/oGNHXffAhJj6FxdpqHnoIejVSytlF2mo6dxZ/508CenSUOOnNNSekC9fPr+lq/ZUEXwhIvmBCcDP6IihWT6RwM94Mw/A7iiU9ATD6CRSSU5OplGjRiQkJPD666/Tp0+f7CeJq1sXNm2C8ePh1Vfhm290EjuTdiJsyGoaak/xV7pqT6OGXrU+fioiXwC5lFIhYez0xnwQTDN1zejEHg4cOECJEiVwOBxMmzaNcuXKUaFCBd8dIEcOGDpUm4mmT4fUfXuYxM7gJRm9wefJk/HywoUzHQG4IitpqN3RsmVLjh8/Tt26dZk1a5bf0lWLpwWyReQOoAxOykMpNdcnUnhB3bp11aZNm/yy77ixq12akYrnz83aQYGdMhFMskQCycnJTJkyhaFDhzJ+/Hh69+4duIMfOQK3387mx3rS+/rbSPjrshkBZpGdO3dStWpVW2W4cuUKNWrUIDExkd9++82jDKSplClThk2bNlG4cGGXyydOnMju3bt5/PHHef75592mq3Z1HUTkJ6VU3WtWxvOooQ+B10mba8jlDoMRT+v0BlPoZjCNTsKdX375hTvuuIP+/fvTvHlz2rZtG1gBkpP5o1gZao55iYnvPk/pPxOCPszZ4J7UNNQPPfSQx0pg6tSplChRgsOHD3PLLbfQtWvXa9ZJTVc9ceJEGjZseDVdtS/waEQgIjuBWOXp8MGPeDsiSG9iAd25uwvJDBa7vBkRBIZ3332X5557jnz58jF16lQ6duyIHVX34sas4o7/Lmfo6lnkTE5k0p2PML3eAxQvkMf83l4QDCOClJQUateuzeLFi23LQOrtiMBT79cvwE3A0eyJF3i8dQAHS+imKSLjX5RSiAhVq1alQ4cOTJ48mSLZKEOZXY6cvcTiW/7F9+Xq8Oo371Dlj/0gYkaAIcaOHTu49957adeuXUiloc5QEYjIcnSEUF50acqNwOXU5Uqp+/wrXvZx9VadUXuwEOl5hPzFhQsXGDZsGA6Hg3HjxtG4cWMaN25st1hXw5xPXF+QHm1fIkdyEgBxl47BsGE6dUXOnDZLaciM1DTUoUZmI4JlwI3Af9O1NyRERgcOkaspndO3uyJYTEMQPKOTcOH777+na9eu/P777/Tq1evqqCAYSDMCFOFKdAy5Yxy8dP43eHWcTmI3e7bOX2Qw+JjMFMH9wGCl1DbnRhH5ExiNLlgT1LhSAu7aMwvZDCYl4WvC+dzOnj3LwIEDmTFjBuXLl2f16tU0beo6j6Jd18HdCDC21t3QurHOWxQXB889B6+9ZpLYZUAwKXg7yIorNzNFcGN6JWAdaJuIlPH6aDZQ3M3M4uIuZhZnlpcoXOP6w33OwtGjR/noo4944YUXGDFiBHny5HG5nt3Xwe0IsFUrncRu8GA9G/mmm2DQIL/LE4rkypWLU6dOUahQoYhUBkopTp06Ra5cubzaLsOoIRH5TSnl0uMhInuUUhnOtBGRu4EpgAOYpZQa62a9B4BPgNuUUhmGBPkzaqjsoC9xdTUE96kqwiGKJxwjlE6cOMGCBQt49tlnr37PzBkcEtdh3TqoVQty5YItW3TZzAIF7JYqaEhMTOTw4cNcunTJblFsI1euXJQoUeKa+QXZiRraJCLdlFIz0+2wK/BTRhuKiAN4G/gXcBj4UUSWKaV2pFsvL9AH2JCJLFmiba3ibDrwJ/M3HCJZKRwiPFDH9ZtXRnmJwjmuP5zOTSnF/Pnzee655/jrr79o2bIllSpV8igiKCSuQ6qPIDlZ58E5f15nOW3Xzl65goSYmBjKli1rtxghR2YTyvoCT4nI9yIy0fr7D9AF3XlnRD1gj1Jqr1LqCrAA7XNIz6vAOMAvKnxpfAILNx666hNIVoqFGw+5nKiT0YQyu3LfB4JwObdDhw7Rpk0bHn30USpUqEB8fLxXSeJC6jo4HLBwoTYTtW8PHTrAsWN2S2UIUTJUBEqp40qpO4ARwH7rb4RSqoFSKrO7rjhwyOn7YavtKlbd45JKKdf1Gf9Zr7uIbBKRTSdOnMjksGkZvmw7iSlpDT6JKYrhy7Zfs25GtQCCadaxrwmHc0tKSqJJkyZ89913TJo0ibVr11KtWjWv9hFy16F2bdi4EUaPhuXLITYWfv3VbqkMIYinSee+A77z5YFFJAp4A+jswfFnADNA+wi8Oc6Zi4letbtz2IVzXH8on9v+/fspWbIk0dHRTJ8+nXLlylGuXLks7Sskr0NMjHYit2sHM2b8k8TuyhWd4M5g8ACPk855vWORBsBwpVRL6/tgAKXUGOt7PuB34Ly1yU3An8B9GTmMvXUWl3FTDB5g/9jWHu/HEFwkJSUxefJkXn75ZcaPH3/VKWxAJ7GrX19HFvXsCVEeV6Q1hDHZTjqXRX4EKopIWRHJAXRET1ADQCl1VilVWClVRilVBlhPJkrAYADYunUrDRo0YMCAAbRs2ZIHHnjAbpGCi5QUbSbq3RsaN4bdwVmW1RA8+E0RKKWSgN7ASmAnsEgptV1ERopIwFJT5IlxfYru2g3BzbRp06hTpw4HDhxg4cKFfPbZZxQrVsxusYKLEiXgq6/g/ff1/INbb4WxY8H+nJGGICWbJZcyRim1AliRrm2Ym3Wb+EOGHNEOLiSmuGw3hA6ps0WrV69Ox44dmTRpktuc7QZABJ58Elq21COD7dt1m8HgAr8qgmDgrBunsLt2Q3Dx999/M3ToUKKjo5kwYQKNGjWiUaNGdosVOtx0k85TdOWK/r51KyxYoBPZeTn71BC+hL19JKRiww1pWLVqFTVq1GDy5Mlcvnw5SzlUDBapEUQrVsCYMVCzJqxda6tIhuAh7BWBq9hwgAtXkkz1pyDlzJkzdO3alRYtWhAdHc2aNWuYOnVq2OeO8bSSXrYYNAhWroRLl6BhQ3j2WTh3zvfHMYQUYa8IUieJ5c+dNu/G6QuJphRgkHL8+HEWLFjAiy++yJYtW9wW/g4nUnNiJZy5iAL/lqq86y745RetBN5+G956y/fHMIQUYa8IQCuD63Je6w5xzixqsJfjx48zZcoUACpXrsz+/fsZO3YsuXNHhgkvs8y3Puf663Um03Xr4PnnddvmzfDnn/45niGoiQhFACGSUCwCUUrx0UcfERsby8CBA/ntt98AIi4iyLb7s3597TROTtb5imJj4dNP/XtMQ9ARMYrAnXM4f54Yl+0G/3Pw4EFat27N448/TuXKldm8efPVOq8BsZcHEbYHNTgcsHgxFC+us5o+8AAcDYkihAYfEDGKYEDLysQ4rnU2nr+UudM40jqlQJCaJC7VEfzf//6XqlWrAgG2lwcJQZHwrmZN2LBBTz778ks9OjCzkiMCv+Ua8hfe5hpypuaIr10mm8uo8Ig3hW0M/+Cu5OPevXspXbo0DoeDVatWUb58ecqUKZNmW7sKxNhdrtPu46fh119h+nSYMEHnKrp8GXLmtEcWg0/IKNdQRCmCjCqQ7XOTgC4kqlYFGa6UZy4H1Du/lkXT32D8+PE899xzbrfPyu+UXYzCz4CEBKhXD158EZ55RpuRDCFHdiqUhRUZVSBzRzA6mYPqzdEF6SNgrhzfy9H/m8Lu47/Trl07OnTokOH2WfmdsktGUTvBdG1TCeg9IKLzFfXpo2clz54NlhnPEB5EjI8AsmaHtd2Jl45QsJ87K8m/flrO0bnPk3T+FEXaDmbJkiXcfPPNGW5vh708GBW+OwJ+DxQrpn0GH36ofQY1a8KoUSaJXRgREYpg6NJtlB+8gr4LN3MpKZk8MVHXVCBzR1A48ZwIeLx5FiiWP/fVdBA5ipblutgmFOvyDhXrt8h029Q33YuJyTismcSe/E6+kNmbdjux5R4Qgcceg507oW1b7UMI85nekUTYm4aGLt3GR+sPXv2uFFxITOGx20sxqm0NIONhdrBVrQr2N9fz589TYOs8du07Q97GT5OrZHVylazukfJMb6dPVurqdv6+3gNaVnbpIwjGMpW+uAeybFoqWlTXSk60gi62boWPP4ZXXoEImfwXjoT9iGD+hkMZtnsyzG5bqzhrBzVj39jWrB3UzFabcTC/uX799ddUr16dFQveo0HZ/BTLl8vjkRfYO9rJqF51sJHde8AnpqUYa/7NV1/BuHHah7BmjefbG4KKsB8RJLuxY6a2h5qTMBjfXE+fPk2/fv14//33qVy5MmvWrOHOO+/0ej92j3bc1avOLr527Gb3HvDpPT9wINSpA9266WpovXrpeQh583q3H4OthP2IwOHGjpnabnfn4y3B+Ob6xx9/8MknnzB48GA2b96cJSUAwT3aySr+cOxm9x7w+T3fvDls2wZ9+8I77+hEdoaQIuznEaT3EThTPH9uLlxJ4vQF7yaZGeDYsWPMnz+f562EZadOnaJQoULZ2mc4xvIH4zwUv8r0449wyy168ll8PJQsCRGWNypYsat4fVAwqm0NHru9lMuRQcKZi5y/lHRN6gm7TS3BjFKKDz74gNjYWAYPHnw1SVx2lQAE52gnuwTjiNOvkXC33aaVQHIyPPSQTlOxaJEJNQ1ywl4RgFYGv4+5h+IuTAyJKYrrckSHVefjL/bv38/dd99N586diY2NTZMkzlcEk2PeFwSjuSsgCtfhgCVLoHRpePhhaNcOjhzx3f4NPiXsncWpLI1PcDkcBl2/ePMrdwVYItcE66zhpKQkmjZtysmTJ3n77bfp0aMHUVHB8R4RrNcMgtO5D/5zjKehRg1d72DKFBg6VI8ONmyAyma0HWxEhCIYunQb89z4CSB4nJHpbeSpjkXAto5tz549lC1blujoaObMmUO5cuUoXbq0LbK4IhivmTPBNg8l4ERHQ//+cP/9MGMGVKqk2y9d0nUQDEFBcLzS+ZGl8QnMW3/QZRIzCI63s1SCadZwYmIio0ePplq1arxtRYE0bdo0qJQABNc1c0e4mbuyRIUKMH68no2ckADlysHkydqXYLCdsFcEE1budqsEgKDyB7hzICacuRjQXEI///wz9erVY8iQIdx///08/PDDATu2twSjM9aQCSJQu7YukRkXB9u32y1RxBP2iiCjDqF4/txBowQgYxNVoBLLTZ06lXr16nHs2DGWLFnCokWLuPHGG/1+3KzirsJcsJj7DC4oVgyWL4d582DPHqhVC0aONJFFNhL2isBdhyAQNCahVFyF9aXib3NH6nySWrVq8cQTT7Bjxw7atWvnt+P5gqXxCZy/lHRNe4xDgu63TSUSq925PGcReOQRncTuwQfh9999msQuEq9zdgh7Z7GrqA0BHr29VMBHA5lFt6R+7rtws8vt/WHuOHfuHIMHDyZnzpxMnDiRhg0b0rBhQ58fxx9MWLmbxJRr3yKvyxEdVCO9VILdse0PMj3nIkV00rrUJHZbtsBHH8GIEZAnj3+OabiGsB8RuIqZnvRwzauZRwOFp6kG2tYq7nK+A/je3PHVV19RvXp1pk2bhlKKUJtl7k4xnnVRjjQYCGbHtr/eoD0+59Qkdl9/Da+/rmcnf/99luQM5uscrIT9iAACFDOdCd4k+vJ37PmpU6fo168fc+fOpWrVqqxdu5YGDRr4ZN+BxI5KZtkhK47tQMyR8NUbtCtZPTnntNvVYdz0hdw5/iVo2hS6d9fRRvnyuZVz04E/+W7XiavHdTdfyAQQuCfsRwTBgjedgL9nfp46dYrPPvuMl19+mfj4+JBUAhB8RYMyw52CypfbtcM7UJXIfPEG7U7WzJz5rrbrdugGls/9Cl54AWbNgmnTMpRz3vqDabZ352kI1heEYMCvIwIRuRuYAjiAWUqpsemW9wO6AknACeBppdQBf8pkF96+vfp6FHP06FHmzZtH//79qVSpEgcOHKBAgQI+278dhNpkrQEtKzNg8ZZr/Bp/X0liaXzCNXIHKkW6L0Jw3cmaMzqK3DEOt6Nbd9uNXXOQNhMmQKdOUK0aAAV3bePiDUX4M0++NOunN2gqtB/Qud35mME8E90u/DYiEBEH8DbQCogFOolIbLrV4oG6SqlbgE+A8f6Sx27sentVSjFnzhyqVq3Kyy+/zJ49ewBCXgmkEkqTtdrWKs71ua5990pMVi7fvr3poLNj4/dFPqSM/DUZjW4zPcfata8msZv2xQS+mdWT+3b8J9NQU2UdK/0xQ6Hmtx34c0RQD9ijlNoLICILgPuBHakrKKW+c1p/PfCYH+WxFTveXvft20f37t359ttvadSoETNnzvR5kjiDd5xxkfIcXHeIno4is2vj94VPKiNZMxrdejxSdjj49Z0PKNz3GaYun8B9O75n6F3PcPyGwi4njLpLqZ2VUZYvRxDBOhrxpyIoDjjXiTwM1M9g/S7A/7laICLdge4ApUqVypIwwfADBNJpnZSURLNmzTh16hTvvPMO3bt3D5okcZGMNyZCTzvo7JqQfPGSklVl4ul2S+MTmPC7cPTR8Tz903L6r/mQb+c8w6zXP2b68RweH9dbM5grJdt34WZGLN/OK22qeaU8gKANaw2KqCEReQyoCzR2tVwpNQOYAbowjbf7j6S44t9++41y5coRHR3Ne++9R/ny5SlZsqTLdYNBOUYa3nSYnnbQvrDxe/KSktH9klVl4sl2aZ7fKAezbmvLmioNeOvCT/R9pg1lNh9hyhdb2f93SqbH9dZX50rJApy+kOi2D3HX3+SMjsqywn505jrW/v7n1e9x5Qsyr5vvgjz8VqFMRBoAw5VSLa3vgwGUUmPSrdcCeBNorJT6I7P9eluhDIKzSpSvSUxMZNy4cbz66quMHz+ePn36ZLh+OFYDCxV8rYD9eX+nypoajZPeARuI+yXT8zt8WBfE6d9fl8uMdv9+6+19X3bQlxnmKnN1jd3J6w4B9o1t7Xb5v974nt/++Puadm+VQUYVyvw5IvgRqCgiZYEEoCPwSDrBagHTgbs9UQJZJdzjijdt2kSXLl3YunUrHTt2pFOnTpluE6iIlEAQaiMbX5sI/TXvJH2nmb5DDNT9kumIJzoa6teHAQNg4UKYPVtPSHNBRiMQV/dRRvMS3Mnmbb+SkVN+aXyCSyUApBkhZBe/KQKlVJKI9AZWosNH5yiltovISGCTUmoZMAG4HlgsOs/IQaXUfb6U49GZ69wucxfjHEpMmTKFfv36cdNNN/H5559z332eXb5wydoZSWY/d/grEMGdWcSZQNwvmZpzbroJPvtMl8R89lmoUwdeegmGD3eZv8iVInZ3Hz1Qpzif/pTg9jq46kPcyVsgTwyXElO8UtiBmg3tVx+BUmoFsCJd2zCnzy38eXzIWGueuZDoMn47FFBKISLUrVuXLl26MH78ePLnz+/x9qE2K9cd4TSyyQ7+CETwpJMPxP3i0YhHRJfEbN5cp7c+cMCrJHbu7qP5Gw6RnIH53NUid/K+0qba1WN5qrAD9WIWFM5iu1DoBG99F26meAiYFAD++usvXnzxRXLlysWkSZOIi4sjLi7O6/0EawlFbwmXkU0wkplZJFD3i1cjnsKF4cMPIcnKSrtlC8ydq9NcX3ddmlWdTUHuuvqMlAC4zmuVmbze9DEZ/QZx5Qt6vJ/MiGhF4EwomBRWrFjBv//9b44cOUK/fv2ujgqyQqjNynVHuIxsghF3mXtTJ2sF8n7xesST6jD+9lt44w1YuhRmzoRm2rHrymmcFfydGcDVbwBQseh1Po0aCntFEFe+oMdOlWA1KZw8eZK+ffsyb948qlWrxieffEL9+hlNyfCMYEjGl13CZWQTjITFy0L//jqiqGtXbTbq2hUmTPDI/5EZgbjPAvUbhL0i6FC3lFfe9WA0KZw+fZrly5fzyiuv8NJLL5EjRw67RQo47iKDwqKzCmLC4WWBRo20iWj4cJ3iunx5jpxxn4ZegCgRl2YhhwgpSgX0PgvEbxD2imDIZ9u8Wj+QJoWMwh4TEhKYN28eAwYMoGLFihw4cMArZ3A4kVlkUFh0Vn4g1MJq0+NT+XPnhnHjoGNHiI2l2KS1FNy5laM3FObkdf/k3UqdF+DKdBTjEK7LER209S6yQ9grgr+veD78C6RJwV3nppTi5E//xwsvvEBiYiLt27enQoUK5M+fP+Qf7KwyfNl2ExnkJaEeVus3+WvVAmBAiwrUGv84N1w8x4gW3Vka24TcOaKvPv/pR5r588Rw+kIiZywlkHDmIv0Wbc6+PEFCRCefeez2Un7L+Z8ZrmyUf/1xmM4d2tC9e3dq167N1q1bqVChAhC43PTBxtL4hKsPX3qC0YwXLIR6lS5/y9+2bil+mzmPw0VLMvmLicxf+iqTGxS8pnRsambbyy78CSkKXlqy1Sfy2E1EK4JRbWuwdlAzJj1cE4DnF24OWKHr9J2YSknm+IIhnDu8m+nTp7Nq1aqrSgCy9mCEQwHvjM7PRAa5J9TDagMhf4sHmlBj71aYMoUGh3+h5cPNYdcul+teSEzxqj3UCHvTUGYsjU9IUywk4cxFBizeAvh3yJca9ph46jDRBW5GohwUbv08JUqXpXv3h69Z3xdZE0PJNJBKRg++iQxyT6iH1QZMfocDnnsO2rTR1dAqW/fUxYvarxAhRPSIYGl8AsOXbb+mYlRiimL4su0e7yMrb919m5Xl73ULODKnN+d+/gKAAuVrMvShO12u723xkFA3DaTi7vwK5IkJKYUWaEKtjGd6Ai5/2bLw2mt6NvKhQ1CmjK6VnDoxLcyJaEUwYeVut/Znd+3OZNVuv3HjRkZ2uY+Taz6icI3GXB/bJFMfhbcPRqibBlJxd96p0/UNrvF33Wt/Y6v8OXJAXBy8+KJOZrdlC7ljXHeV7tpDjYg2DWW3U8xKnpvJkyfTv39/br75ZpYvX869997r0bG8jZcPddNAKuE+T8CfkWChHlZrm/w33giffqr/nnkG6tZlaednaFWwBSlOM/mjgDHtXWc5DTXCXhE8dnspPlp/0OWyYvlzc+FKEqddlA8s4EFmUm/eulPTQdSrV49u3boxbtw48uXL52Jr93jzYGR1xm0whqiGeofmjnDx44QlIvDgg9C0KfTrR+Wks7zRsVbQPRu+IuwVwai2Ndh34vw1s4udO8UBn2whMfkfP0GMQzwyPXjy1n327FkGDhxI7ty5mTx5MnfccQd33HFHVk/HY7LyJm06psBiMqeGAIUKwQcfQHIybR0O2vIHfLAMeo+C66+3WzqfER4GrkyY160Bkx+u6dbeeF2Of/RhgTwxTHjwVo+Lfmdkt1++fDmxsbHMmjWLnDlz4q9qcO5wjoNeO6hZpucULg7mUCFc/DgRgcN6zr/7DqZMgRo14Jtv7JXJh4T9iCAVT4pRAFxyExeckckkfXtciRw88sgjzJ8/nxo1arB06VJuu+02/52cj/BFx+RP01Iwmq2yQ7j4cSKKfv3+SWJ3113w1FMwcSIUKJD5tkFMRCgCdx2Ip0NzT3LdOLNnzx5WrFjBiBEjGDRoUMgkictux+RP01I4mq1M5tQQpWFDncRu5EgdYlqxIgwebLdU2SLsTUNL4xMY8MmWNCGeAz7ZwtL4BI/fgD0xmRw6dIgxY8aglKJChQocOHCAYcOGhYwSgOzHbvvTtJTVfQfz7OpQD/GMaHLlgtGj4eef9SgB4Mcf4dgxe+XKImE/IhixfHsaRzBAYrJixPLtHr8BZ6QwUlJSmDFjBgMHDiQ5OZkOHTpQoUIFryOCgoHshmr60+adlX2HwigiXCOiIoZbrPDR5GR45BE4dQomTYInnvCqVKbdhP2IwFVoaGq7p2/Abme3Jp2iWbNm9OzZk3r16rFt27Y0+YFCEW8dzM54O/vZG7Kyb+P8NgQMhwOWL4fYWOjcGVq10nWTQ4SwVwQZ4enQ3JXCUCnJ/DJrID/+FM/s2bP55ptvKFeuXAClDz78mRYgK/s2UTmGgFKlCqxZA2++CT/8ANWqwc6ddkvlEWFvGsqfO8Zluoj8ufWEMXfRRMOXbb+6XYE8MTxQpzif/ZzAmSP7iS5YDIlyULD181xfpAQFazXJcu3gQOPvmazgn1nAWdm3icoxBJyoKOjd+58kdlWq6PYLFyBPHntlywAJdGx7dqlbt67atGmTx+unzy4KEBMlTOhw7VyBpfEJjFi+3aU5KSoliT/XLuTs+kUUaPI0N9x2/9VlqVWNgh1X4bK5Yxxh66CMtPM1BCmHDkGdOtqp3L8/xGSetcAfiMhPSqm6rpaFvWmoba3iTOhwaxrzjzslMHjJNpdK4HLCLg7PeY6z/5vPdVUbcV31pmmWh4qpIdJs5iYqxxAU5MwJjRvrENP69SE+3m6JriHsTUPgWWSGq04S4K+NSzj93Xs48ham6IPDyV3+WoUaKqaGSLSZm6gcg+0ULQqLF8OSJTqJ3W23wcCB/6S9DgIiQhFkZhdfGp9wjS1ZqRREoshRrCrX12pFgcadicp5rY1PCJ0CKcZmbjDYSPv2Oold//7wxx9BowQgAkxDmdUMSF2eSsql85xcMYXT384AIFeJqhS6qxcxua8jJirtDyfAo7eXCpk3zlAvVmIwhDwFCsCcOTB9uv4eHw/PPgvnztkqVtgrAnd28dQKZM7LL/y6jiOze/H3L6uQHLmvJokrkCeGiR1uvcbXMOnhmoxqWyOg55MdjM3cYAgSUpPYrVkDb78N1avDypW2iRP2UUNlBn3pdllqaGny32f485t3ubD7B2KKlqNQq+fIeVMFJj9c03SSBoPBv/zvf9ClC+zapWckT5oEBQv6/DARHTUUlYEZLnWeQMqVC1zaH0/+Rk9w8xNvkPOmCqYmrsFgCAx33KFNREOGwMcfw4wZARch7J3FKW4GPEl//cHfv3zHDQ0eIqZAMYr3fC+NMzjEBkoGgyGUyZULRo2Chx+GypbPbuNGKFkSbr7Z74f364hARO4Wkd0iskdEBrlYnlNEFlrLN4hIGX/KAzoa6NzPX3Jk9jOcXb+IpDNHAa6JCDrrQfF6g8Fg8Ck1akCOHDqJ3aOP6txF773n9zdTvykCEXEAbwOtgFigk4jEplutC3BaKVUBmASM85c8AImnDnP848H8+c075CxWhWJdphFToJjLdU1IpcFgsA2HA778UiuGp5+Gli1h3z6/Hc6fI4J6wB6l1F6l1BVgAXB/unXuBz6wPn8CNBc/Je1RKckcXzSMxBP7KXRPX4o+NJLofDe6XNeEVBoMBtupVAm+/x6mTYN166B1a0hxXUExu/jTR1AcOOT0/TBQ3906SqkkETkLFAJOOq8kIt2B7gClSpXKkjAS5aBwm/5E57+Z6Ov/8cjHRAkP1yvJd7tOhE0JRIPBECZERUHPnloJHD2qv/uBkHAWK6VmADNAh49mdT+5SlS7ps1V3iGDwWAIKkqV0n9+wp+moQSgpNP3Elaby3VEJBrIB5zyo0xpiCtf0CgBg8EQ8fhTEfwIVBSRsiKSA+gILEu3zjLgSevzg8Bq5eMZbvvHtnbZHle+IPO6NfDloQwGgyEk8ZtpyLL59wZWAg5gjlJqu4iMBDYppZYBs4EPRWQP8CdaWfgcd8rAYDAYDH72ESilVgAr0rUNc/p8CejgTxkMBoPBkDFhn2LCYDAYDBljFIHBYDBEOEYRGAwGQ4RjFIHBYDBEOCFXj0BETgAHsrh5YdLNWo4AzDlHBuacI4PsnHNppVQRVwtCThFkBxHZ5K4wQ7hizjkyMOccGfjrnI1pyGAwGCIcowgMBoMhwok0RRD4GnD2Y845MjDnHBn45ZwjykdgMBgMhmuJtBGBwWAwGNJhFIHBYDBEOGGpCETkbhHZLSJ7RGSQi+U5RWShtXyDiJSxQUyf4sE59xORHSKyVURWiUhpO+T0JZmds9N6D4iIEpGQDzX05JxF5CHrt94uIh8HWkZf48G9XUpEvhOReOv+vscOOX2FiMwRkT9E5Bc3y0VEplrXY6uI1M72QZVSYfWHTnn9O1AOyAFsAWLTrdMLeNf63BFYaLfcATjnpkAe63PPSDhna728wBpgPVDXbrkD8DtXBOKBAtb3onbLHYBzngH0tD7HAvvtljub59wIqA384mb5PcD/AQLcDmzI7jHDcURQD9ijlNqrlLoCLADuT7fO/cAH1udPgOYiIgGU0ddkes5Kqe+UUhesr+vRFeNCGU9+Z4BXgXHApUAK5yc8OeduwNtKqdMASqk/Aiyjr/HknBVwg/U5H3AkgPL5HKXUGnR9FnfcD8xVmvVAfhG5OTvHDEdFUBw45PT9sNXmch2lVBJwFigUEOn8gyfn7EwX9BtFKJPpOVtD5pJKqS8DKZgf8eR3rgRUEpG1IrJeRO4OmHT+wZNzHg48JiKH0fVPng2MaLbh7fOeKSFRvN7gO0TkMaAu0NhuWfyJiEQBbwCdbRYl0ESjzUNN0KO+NSJSQyl1xk6h/Ewn4H2l1EQRaYCuelhdKZVit2ChQjiOCBKAkk7fS1htLtcRkWj0cPJUQKTzD56cMyLSAhgC3KeUuhwg2fxFZuecF6gOfC8i+9G21GUh7jD25Hc+DCxTSiUqpfYBv6IVQ6jiyTl3ARYBKKXWAbnQydnCFY+ed28IR0XwI1BRRMqKSA60M3hZunWWAU9anx8EVivLCxOiZHrOIlILmI5WAqFuN4ZMzlkpdVYpVVgpVUYpVQbtF7lPKbXJHnF9gif39lL0aAARKYw2Fe0NoIy+xpNzPgg0BxCRqmhFcCKgUgaWZcATVvTQ7cBZpdTR7Oww7ExDSqkkEekNrERHHMxRSm0XkZHAJqXUMmA2evi4B+2U6WifxNnHw3OeAFwPLLb84geVUvfZJnQ28fCcwwoPz3klcJeI7ACSgQFKqZAd7Xp4zv2BmSLyPNpx3DmUX+xEZD5amRe2/B6vADEASql30X6Qe4A9wAXgqWwfM4Svl8FgMBh8QDiahgwGg8HgBUYRGAwGQ4RjFIHBYDBEOEYRGAwGQ4RjFIHBYDBEOEYRGAwGQ4RjFIHBkAnWxB3zrBjCFnNzGwwuEJEyVg78ucAvwGwR2WTl+B/htN5+ERkhIj+LyDYRqWK1FxGRb6z1Z4nIAWumLyLymIhsFJHNIjJdRBz2nKXBoDGKwGBwT0VgmlKqGtBfKVUXuAVoLCK3OK13UilVG3gHeMFqewWduqQaOtV5KbiaAuFhIE4pVRM9+/fRQJyMweCOsEsxYTD4kANWvneAh0SkO/qZuRldAGWrtWyJ9f8noL31+U6gHYBS6isROW21NwfqAD9aqT5yA+GQ+8kQwhhFYDC4528AESmLftO/TSl1WkTeRyc2SyU1k2symT9TAnyglBrsY1kNhixjTEMGQ+bcgFYKZ0XkRqCVB9usBR4CEJG7gAJW+yrgQREpai0rKGFQP9oQ2pgRgcGQCUqpLSISD+xCV4Za68FmI4D5IvI4sA44BpxTSp0UkaHA11YkUiLwDHDAP9IbDJljso8aDH5ARHICyVYa5QbAO5Zz2GAIOsyIwGDwD6WARdZb/xV0UXmDISgxIwKDwWCIcIyz2GAwGCIcowgMBoMhwjGKwGAwGCIcowgMBoMhwjGKwGAwGCKc/wdla38TYKfcJAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -1404,7 +4177,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1416,7 +4189,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1428,7 +4201,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1440,7 +4213,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1452,7 +4225,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEWCAYAAABrDZDcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAAx90lEQVR4nO2de5xdVXX4v2smk2QC/DIiiDIkJGqE8lIwEiz+FBAFQUNqpYD4RKTWatXS2KBUA6JG01b5tahFfKHIW6dBsPEBWksNkjjEGDA2BSQZQcIjCGSASbJ+f+x9J2funHPvufee5z3r+/nMZ+45Z99z1tl37732XmvtvUVVMQzDMKpLT94CGIZhGPliisAwDKPimCIwDMOoOKYIDMMwKo4pAsMwjIpjisAwDKPimCKoOCKiIvLCvOUwQESOFpH/EZEnRGRR3vLEwcv6fP/56yJyUUL3fYeI/FcH3/+JiJydhCxVwBRBm4jIm0Vkta8I94vI90XkFQncN8nKlOS95nilMSWJ+7Xx/GP88/8+j+fHQUTuFZHjO7jFhcC/quruqjoUcf9RX+b+4H/f3Tt4Xsd4We/O+rkiMlVElnrF+aTPm6+KyJysZekGTBG0gYj8LfB54FPAPsBs4AvAKTmK1e28HXgEeFvegqTI/sD6JmneoKq7A0cA84Hz6xNkoazz6hAEuA5YCLwZmAm8GFgDvDpPoUqLqtpfC3+4QvcEcGqDNNNwiuL3/u/zwDR/7RhgM3Au8CBwP/BOf+0cYAx4xj/jBn9+X+B6YAtwD/A3/vye/l5v8Me7AxtxjWXovUJkVeCF/vPJwDDwR2ATsDSQ7j6f9gn/9/K6++wLjAJ7Bs4dDjwE9AEvBH4KPObPXd1Cnu8GPA6c7t9nfuDaHC/XO73MjwLvAV4G/ArYiutl19L34BrP3/n8vxyYGfxt6p59L3C8/7wUuMZ/53Fcoz3fX/smsNPnwRPAhyPe5d3+N3oEWAHs68//b933p4V8d1wWf7wc+F7gd/xr4H+Ae/y51wN3+Dz4b+CwwHf/Hhjx77EBeLU/3wt8xMvzOK5xndXgGcHy83XgS8AP/Xd/CuwfeOaB/toj/pl/Ebj2bJ8ffwR+AXwC+K+IPDze59OsBmXmJ/4et3pZfgDsFbh+LfAArjz+J3Bw4NrXgUuAG/13bwNeELj+Wi//Y7gO4E+BswPXzwLuwpXFlcE8KOpf7gKU7Q84EdgOTGmQ5kJgFfAcYG9fCT/hrx3jv38hroE8CdgGPEt3FcKLAvfq8ZXxY8BU4PnA3cAJ/vprfYF+DvBl4LrAdyfcK0LWYEU+BjjUP/Mw4A/AIn9tjk/b6L1vBt4dOF4OfMl/vhL4qL/3dOAVLeT5W3EKsxe4AfiXwLWaXF/y930t8BQw5PNkENfgv8qnPwvXED8fpzi/A3wz8P7NFMFT/jfrBT4NrApLG/Eex+GU4BG4zsK/AP/ZwveDsszCKaJauVJcI7sn0I9Twg8CC7ysb/ffnwYcgFOa+wby8AX+82JgnU8juJ72s8OeEVJ+vo5rOF/pn3MxvjHHKfNNOIU9hV2dhIP89atwSnY34BCckopSBMuAnzYpMz/BKbMX+fz4CbAscP0sYA92ddruqKs3DwNHelmvAK7y1/bCKas3+msfwHW4zvbXT8GVrz/x188H/jvvdqtpHctbgLL9AWcCDzRJ87/ASYHjE4B7/edjcL2ZKYHrDwJH+c9fZ6IiWADcV3f/84CvBY7/xVfekVqlDbtXhKzjFTnk2ueBz/nPc2iuCM4GbvafxVf8V/rjy4FLgf3ayPMfAZ/3n8/AjYz66uQaDKR/GDgtcHw98EH/+cfAewPXDvAVeQrxFMGPAtcOAkbD0ka8x1eAzwaOd/fPnhPz+/fiRgtbcSOaLzCxQT4ukPaLeCUROLcBeBVudPYgrmfdF5LmlAZl5biQc0FFcFXd++3AKa3TgJ/VffffgI/jFNUYcGDg2qeIVgRfDj4nIs1PgPMDx+8F/iMi7YB/j5mB97gscP0k4Df+89uAnweu1cp5TRF8H3hX4HoPrqO3f6vlPss/8xG0zsPAXk1spPviKmqN3/lz4/dQ1e2B4224ShPG/sC+IrK19ocbuu8TSHMprhf1dVV9ON5rTEZEFojILSKyRUQew5lY9mrhFtcDLxeR5+F6hTuBn/lrH8ZVml+IyHoROSumTLOAY3G9MoB/x/X8T65L+ofA59GQ41r+hv02U5iYn414IPB5GzC9BXv5hGer6hO48jQY8/vgRmgDqrq/qr5XVUcD1zYFPu8PnFtXbmbhRgEbgQ/iFNuDInKViNTK5yxcRyaKTQ2uTbju3+8R3HvvDyyok+dM4Lm4UfOUunsHf6N6Hgae10QOmPxb7Q4gIr0iskxE/ldE/ohTsDCxrId+179L8B0VZ56tsT9wceAdH8GV+1Z+48wxRdA6PweeBhY1SPN7XIGoMdufi4PWHW/C2WMHAn97qOpJ4Ao1ThFcDry3LhS0/l7N+DbOTjtLVWfizC0S916q+ijOFnsazol3lda6jaoPqOq7VXVf4C+BL8QMW30rrpzeICIP4Mxi03GmjnYI+2224xTHk8CM2gWft3u3cO9meTTh2SKyG842PtLCM+I+fxPwybpyM0NVrwRQ1W+r6iu8PAp8JvC9F8R8Rhizah98RNOeuPfehDPnBOXZXVX/CjfC2x78Lu53ieJHwJEisl8TWaJ4M86EczzO5zenJnKM794PjD9XRCR4jHvPv6x7z35V/e82Zc0EUwQtoqqP4ez1l4jIIhGZISJ9IvI6EfmsT3YlcL6I7C0ie/n034r5iD/g7Nc1fgE8LiJ/LyL9vjdziIi8zF//CK5ynoWzyV/uG7CwezVjD+ARVX1KRI7EVZgaW3A9/Gb3+zZu+Pwm/xkAETk1UHEf9TLvjCHT24ELgJcE/v4cOElEnh3j+/VcCXxIROb6hupTOMf1duC3uB7+ySLSh7PvTmvh3s3y+0rgnSLyEhGZ5p99m6re28Z7NOPLwHv8KE9EZDf/XnuIyAEicpyX4SnciKn2W1wGfEJE5vnvHdZiPp8kIq8Qkak4Z+0qVd0EfA94kYi81deXPhF5mYj8iaruwPlqlvr6dBANFL2q/gjnq/iuiLxURKb493pPzJHmHrjO3MM4xf+pFt7vRuBQX/en4Jznzw1c/xJwnogcDCAiM0Xk1BbunwumCNpAVf8J+FtcQ7EF1wt4H85BCXARsBoXtbIO+KU/F4evAAf5oeWQrySvxzWA9+AcbJcBM0XkpV6Ot/l0n8E1sEvC7hXj2e8FLhSRx3HK65rAO28DPgnc6u93VMQ9VgDzcH6UtYHzLwNuE5EnfJoPqI8/96aiM+tv5J+xP3CJH1HU/lbgHHJnxHiner6Ki/D5T1x+PgW837/jYz4PLsP10p9k4rC/GZ/GdQC2isjf1V/0Ddg/4Exo9+N63qe38Q5NUdXVuAilf8Up3o3AO/zlaTiH60PsCjQ4z1/7Z9zv/gOcU/QrOGdrXL6Ns/s/ArwUeIuX53GcI/903AjhAVx5rSna9+HMLw/gbPRfa/KcNwE3AVfjond+jQun/VEMGS/HmZ5GgDtxgR2xUNWHgFOBz+IUyUG4uv60v/5d3Htd5c1OvwZeF/f+eSF+5G4YhmG0iIj04DoLZ6rqLXnL0y42IjAMw2gBETlBRAa8ae0jON9C7FFFETFFYBiG0Rovx0VWPQS8ARfJNdr4K8XGTEOGYRgVx0YEhmEYFSfvhaNaZq+99tI5c+bkLYZhGEapWLNmzUOqGjovpnSKYM6cOaxevTpvMQzDMEqFiETO1jbTkGEYRsUxRWAYhlFxTBEYhmFUHFMEhmEYFccUgWEYRsUpXdSQYbTL0PAIy1du4PdbR9l3oJ/FJxzAosMLvUy8YWSCKQKjEgwNj3Ded9YxOrYDgJGto5z3nXUApgyMymOmIaMSLF+5YVwJ1Bgd28HylRtyksgwioONCIxK8Put4WuCRZ034mHmtu7ARgRGJdh3IHxvlajzRnNq5raRraMou8xtQ8NJ7bxpZIUpAqMSLD7hAPr7eiec6+/rZfEJB+QkUfkxc1v3YKYhoxLUzBVmxmiNRqYfM7d1D6YIjMqw6PBBa/g9Q8MjLF2xnq2jYwA8a0YfH3/DwRPyp1mk1b4D/YyENPpmbisfZhoyjIoxNDzC4mvXjisBgEe3jbH4urUT7PvNTD9pmtuGhkc4etnNzF1yI0cvu9n8DiljisAwKsbylRsY2zl5Z8KxHTrBvt/M9LPo8EE+/cZDGRzoR4DBgX4+/cZDOx51mRM6e8w0ZBgFJo3wzEY2/OC1OKafNMxtjUYiZtpLBxsRGEZBSatn3MiGH7yWV6SVOaGzxxSBYRSUtMIzF59wAH09Mul8X69MaOTTMv00w+Z8ZI+ZhhLEZlkaSZJWz7hWJptFDdXSZl2GF59wAIuvW8vYjl1+jHolZSSLKYKEsEXNjKRJMzyz8KG09b7syb5tI0HMNJQQNsvSSJqyz4ZuNwQ0LKppbKdaXUoRGxEkhDm4jKQJmw197IF7s3zlBj509R2FNj92MkK2upQ9pggSwmZZGmkQNOGUyfzYSQio1aXsMdNQQmQxjLfZltWmTObHsIYc4vXqy24SKyM2IkiItBY1q0UijWwdRdjlMytyb9BIh05MJllGtA0Nj0woq0Hi9OptgcDsMUWQIElHYtSbAuorls22rBbtmkyyNiktX7khVAkIxO7VFz6qqcsw01CBCTMF1GMOtOrQrskka5NSVJlUbPRaVEwRFJg4jbw50KpDuzN9s47CiSqTg1ZWC4spggLTrJE3B5oRh6yXbDBnb/kwRVBgwipUbYWYrNZ9MYpDu4vQZd0w57VGkdE+qTqLReRE4GKgF7hMVZfVXZ8NfAMY8GmWqOpNacpUJix6wgjSbmx+HuXInL3lIjVFICK9wCXAa4DNwO0iskJV7wwkOx+4RlW/KCIHATcBc9KSqYxYhTJqdGLrt3JkNCJN09CRwEZVvVtVnwGuAk6pS6PA//GfZwK/T1Eewyg1tjyzkRZpKoJBYFPgeLM/F2Qp8BYR2YwbDbw/7EYico6IrBaR1Vu2bElDVsMoPOaENdIi7wllZwBfV9V/EpGXA98UkUNUdWcwkapeClwKMH/+fFuQ1uh6Gs0ENp+RkTRpKoIRYFbgeD9/Lsi7gBMBVPXnIjId2At4MEW5DKPQNJsJbA2/kTRpmoZuB+aJyFwRmQqcDqyoS3Mf8GoAEfkTYDpgth+j0pRpcTmjO0hNEajqduB9wErgLlx00HoRuVBEFvpk5wLvFpG1wJXAO1TVTD9GpbH1+I2sSdVH4OcE3FR37mOBz3cCR6cpg2GUDVuP38gam1lsGAXDooOMrMk7asgwjDosOsjIGlMEhlFA0owOynKTmqQoo8xlwhSBYWRMno1aXvsed/LOZdqruayYj8AwMqTdFUSTIo/Q1E7f2cJp08cUgWFkSN6NWh6hqZ2+s4XTpo8pAsPIkLwbtTwWruv0nW2xvfQxRWAYGZJ3o5ZHaGqn72zhtOljisAwMiTvRi2P3cM6fWfb8Sx9pGwrOsyfP19Xr16dtxiG0TZVDIWs4jsXDRFZo6rzQ6+ZIjAMw+h+GikCMw0ZhmFUHFMEhmEYFccUgWEYRsUxRWAYhlFxTBEYhmFUHFt0zjBKhoViGkljisAwSkS3rMRpyqxYmGnIMEpE3ovWJUHeK7Aak7ERgWGUiLwXrUuCRsqs2ajARhLpYIrAMEpE3I3ti9xgtqvMusUsVkTMNGQYbTI0PMLRy25m7pIbOXrZzZmYNuIs4FZ000u7q5F2g1msqJgiMIw2yKuxjbMSZ9EbzHZXI+0Gs1hRMdOQYbRBJ3buTmm2sX3RG8ya7K2aruKaxYzWMUVgGG1Q5Ma2DA1mM2UWxuITDpjgIwDboCYpTBEYRh1xHK1FbmzL3mBG5X+7IwmjOaYIDCNA3MiUIje27TaYRYg0apb/7YwkjObYxjSGEeDoZTeH9vQHB/q5dclxE84VoeFMivoGGJxiy3pLyFby32iNRhvT2IjAMAK0Yvvvpt5pns7vIEX2vXQzFj5qGAHajXEvO0VpgKua/3ljisAwArQb4152itIAVzX/88YUgWEEiDNhqxspSgNc1fzPG3MWG4YBdJfz25iMOYsNw2hKNzm/jdZI1TQkIieKyAYR2SgiSyLS/IWI3Cki60Xk22nKYxiGYUwmtRGBiPQClwCvATYDt4vIClW9M5BmHnAecLSqPioiz0lLHsMwDCOcNE1DRwIbVfVuABG5CjgFuDOQ5t3AJar6KICqPpiiPIZReMxOb+RBmqahQWBT4HizPxfkRcCLRORWEVklIiemKI9hFJqi7yNgdC95h49OAeYBxwBnAF8WkYH6RCJyjoisFpHVW7ZsyVZCw8iIou8jYHQvaSqCEWBW4Hg/fy7IZmCFqo6p6j3Ab3GKYQKqeqmqzlfV+XvvvXdqAhtGnhRldq9RPdJUBLcD80RkrohMBU4HVtSlGcKNBhCRvXCmortTlMkwCktRZvca1SM1RaCq24H3ASuBu4BrVHW9iFwoIgt9spXAwyJyJ3ALsFhVH05LJsMoMkWZ3WtUD5tZbBgFwqKGjLSwmcWGURJsdq+RB6YIDMOIhY1WuhdTBIZhNCXuFp5GOcl7HoFhGCXA5jh0N6YIDMNois1x6G7MNFRRzN5rtMK+A/2hm8rX5jhYeSo3NiKoILamjdEqjeY4JF2ehoZHOHrZzcxdciNHL7vZymUGmCKoIGbvNVql0RaSS1esT6w8WSclH8w0VEHM3mu0Q9gch6HhEbaOjoWmb6c8XXBDtFIxU1N6xBoRiMgMEfkHEfmyP54nIq9PVzQjLWxNGyMpGvX6Wy1PQ8MjPLotXKmMbB01M1GKxDUNfQ14Gni5Px4BLkpFIiN1bE0bo0an9vhGvf5Wy1MzU5KZidIjriJ4gap+FhgDUNVtgKQmlZEqjey9VaLqTsmh4REWX7d2gj1+8XVrW8qHqF7/s2b0tVye4piSzJeVDnF9BM+ISD+gACLyAtwIwSgpVV/TxmbKOnv82I6Ji06O7VAuuGF97DxYfMIBE/IR3Ojy4284uGV5okJU6zFfVvLEHRF8HPgPYJaIXAH8GPhwalIZRspY5BSR9vio82EkOboMM1mGYb6s5Ik1IlDVH4rIL4GjcCahD6jqQ6lK1oXYpJviYJFTyZHU6LJ2j1odmdnfx5PPbJ8wajFfVjrEUgQicoT/eL//P1tEZgK/8xvQGE0wU0SxaDZTtgoM9PeFhn4O9Pel9sxmnaF6pWKdp2yI6yP4AnAE8CvciOAQYD0wU0T+SlV/kJJ8XUMjU4QV7OyJsm1Xqbe5dOHBLL52LWM7d/W4+3qEpQtbt+/HoZ3OUNV9WVkR10fwe+Bwv4H8S4HDcXsLvwb4bFrCdRNmiigWFjnl8mD5qS+ekAfLT31xanlgfpniEndE8CJVXV87UNU7ReRAVb1bxKJI49ANpohuG6ZbbzPbPLDOUHGJOyJYLyJfFJFX+b8vAHeKyDT83AKjMWWfxGVrwBidYjPai0tcRfAOYCPwQf93tz83BhybvFjdR9lNETasNzql7J2hbkZUtXmqAjF//nxdvXp13mJUjrlLbiSspAhwz7KTsxbHKAFhpkSgq8yLZUJE1qjq/LBrccNHjwaWAvsHv6Oqz09CQKP4dIOPw8iOqAihT7/xUG5dclzO0hn1xDUNfQX4Z+AVwMsCf0ZFsGG90QpmSiwXcaOGHlPV76cqiVFoasP3C25YP74EwbQptq+REY5FCJWLuIrgFhFZDnyHwGJzqvrLVKQyCstTYzvHP28dHbPZ0UYoZkosF3EVwQL/P+hoUMCMfRWiSrOju23ORNbYzO1yEXfROQsRNSoz3D9/aB1XrLpvPErK1oVqnfoF5EyZFpvYexaLyMnAwcD02jlVvTANoYxiUoXh/tDwyAQlUKNbRz5pYjO3y0PcPYu/BJwGvB8XOn4qLpTUqBBViBxavnJD6HwJ6L6RT1Go+k5xRSDuiOBPVfUwEfmVql4gIv8EWBRRxajCcL9RY99NI5+iYMuzF4O4iqBWO7aJyL7Aw8Dz0hGpe+kGB2S3D/ejzF9C65uxG82pUgBCkYmrCL4nIgPAcuCXuIihy9ISqhuxnk84RVOOYdEuApx51Oyu+J2Klt9VCUAoOnGjhj7hP14vIt8DpqvqY+mJ1X1Yz2cyeSjHODtkQXeav4rYGalCAEIZaCVq6E+BObXviAiqenmT75wIXAz0Apep6rKIdH8OXAe8TFW7ckU56/lMJmvlGLch7FbzVxE7IzbfoBjEjRr6JvCPTFxrKHQVu8B3eoFLgNcBBwFniMhBIen2AD4A3NaS5CXD1mKfTNbKserr3xShM1IfIQSUenn2biHuiGA+cJC2tmb1kcBGVb0bQESuAk4B7qxL9wngM8DiFu5dOqznM5mszQJFaAjzJG8zjK1IWlzirhr2a+C5Ld57ENgUON7sz40jIkcAs1T1xhbvXTrKujFNmjHeWc9LqPqoLO95IFUfkRWZhiMCEbkBFyG0B25ryl8wcdG5he0+WER6cEtbvyNG2nOAcwBmz57d7iNzp2y257Sdi3Eds0lFulR9VJa3I7zqI7Ii08w0tALYB/hZ3fn/C9zf5LsjwKzA8X7+XI09gEOAn4gIuBHHChFZWO8wVtVLgUvB7VDW5LlGQmThXGymHJNURnk3hEUgz85I3qYpI5pmiuAU4DxVXRc8KSKPAJ/CbVgTxe3APBGZi1MApwNvrl304ad7Be75E+DvujVqqIwUoQeXtDIq26ism6j6iKzINPMR7FOvBAD8uTmNvqiq24H3ASuBu4BrVHW9iFwoIm2blIzsKIJNvQjKyEiGsvrJqkCzEcFAg2tNWwNVvQm4qe7cxyLSHtPsfka2FKEH143mhKLN7s0SG5EVk2YjgtUi8u76kyJyNrAmHZGMolCEHlzekS5JU/N5jGwdRdnl87AVN408kUZTA0RkH+C7wDPsavjnA1OBP1PVB1KXsI758+fr6tXmRqgS3dSDPnrZzaEjnMGBfoulN1JFRNaoauhE4IamIVX9A/CnInIsLsIH4EZVvTlhGQ0jkm4yJ5jPwygicReduwW4JWVZDKPr6Uafh1F+Yi86ZxhFJWnTUZqmqCI44A2jHlMERqlJevZzUWZTG0aWmCIwSk3SE86KMJvaMLIm7qJzhlFIkna+mjPXqCI2IjBKTdLO1yo7c7spTNdoDVMEBhDeCEDxbdlJO1+r6swt4jaWRnaYIqgwtcZ/ZOsogltvHFwjsPjatSAwtkPHzxWxYUja+VpVZ24Rt7E0ssMUQQHIY0he3wOsn18+tnPyjPOiNgxJO1+r6Mw130i1MUWQM3kNycN6gHGwhqE4JNmBqLJvxLCoodzJa/u+dht0axiKQdKL16W9uF+aW54anWOKIGfyGpI3a9D7eoS+XplwrgpO07KQdAcizZVmbcXV4mOmoZzJa0geFh1TcxgPlihqqKrE6UC0ajrqxDdy/tA6rrxtEztU6RXhjAWzuGjRoUDrjmgLY80eUwQ5k1e4YtzoGKuA6dFJg9esA5Gl7+n8oXV8a9V948c7VMePL1p0aEujXgtjzQczDeVMnpu/LDp8kFuXHMc9y07m1iXHWUXLkE7NJc1s+ln6nq68bVPD861seZqXz6zq2IigABQ1XNGG6OnRadx+sxFdlr6nHRGbW9XOtzLqtTDWfDBFYIRiQ/R0SaLBa9SByNL31CsSqgx6xQUbtDJJz8JY88FMQxUkTiifDdHTpRVzSTtkudfzGQtmNT0f1wzZbXtUlwVTBBUjrm3ahujpknaDl6Xv6aJFh/KWo2aPjwB6RXjLUbPHo4ZaIU+fWZVpuHl9EbHN6zsj7ubptsl6+pgPxsiStjevN7qPuD39VsNarVFrnaIGCZQFK3PJYYqgYsR1xrXi4DPHcjXJsyG2MpcspggqRis9/bg9VlvCuHqk2RDHUTBW5pLFnMUVIw1nnDmWq0daUWUWzJAPNiKoIEnbpi32u3qk1RBHKZilK9ZPKLNW5pLFRgRdQN5L/Frsd/WIanB7RDoqf1GKZOvo2IT7WplLFhsRlJzzh9Zxxar7JmwzmbTTrJnNtqrbO5aNJJ27Yb4mcMtKdFL+onr6wAT7v5W5ZLF5BCVmaHiED119x6RtJiG5eP96pyC4npdN8ikXafyOQ8MjnHvN2tDlJdotf0PDI3zw6jtCrwlwz7KTW76n4Wg0j8BMQyVm+coNoUoAknOaFX2pibzNYmUhjd9x0eGD7IzoSLZb/hYdPsizZvSFXjP7f3qYaahD8oylblTZFDc7uFHsf73cMHmoXeToDIslj09av2MaTtuPv+HgXPboqDKmCDog74aokT21kTxhci++bi0ojO3UCd+d2d/H1tGx0GfnTR6x5EWezdpItrSibNLYWMns/9ljiqADsmiIGlXuKIddM3nC5B7bMXmIPzq2g+l9PfT39Rayd5b1aCVvxd+IZrKltRNeWo22Lb+RLakqAhE5EbgY6AUuU9Vlddf/Fjgb2A5sAc5S1d+lKVOSpN0QNavc9ZUwrr+gFfm2bhvjc6e9pJC9s6xjyYs8m7WZbGn2sq3RLj+pKQIR6QUuAV4DbAZuF5EVqnpnINkwMF9Vt4nIXwGfBU5LS6akSbohqu/9P/n09qYNT7ASRq0YWi9PM5NSfdqiVvSs93uOUqBx8jJtk1KcTklRf0cjf9KMGjoS2Kiqd6vqM8BVwCnBBKp6i6pu84ergP1SlCdxkpzUEja1Psw2D9GVPq48Yen6eoW+Hpn03WMP3LuwUTlZr10fpeAF9/tFRTB1uj9xJ7IVwZdjFJ80TUODQHBX683Aggbp3wV8P+yCiJwDnAMwe/bspOTrmCSH22FD+yiiKndceaLS1Z879sC9uX7NSCFt4jWy6uUODY/w5NPbQ68pcMEN63lqbGdoXmVhUupkdFRkB7iRDalNKBORNwEnqurZ/vitwAJVfV9I2rcA7wNepapPN7pvt04om7vkxkgbf5C+HmH5qS+OVVE7reDdtjlNu/kRNhkrLoMD/ZH+m6QnSLXzfjZhsDrktTHNCBDczHQ/f24CInI88FFiKIFuJq7dfuqUnrYar3Z680WeQ9AqneRHK6O1emqNcthv2yPC3CU35hppk7UD3EYfxSRNRXA7ME9E5uIUwOnAm4MJRORw4N9wI4cHU5Sl8MQJBQV48pl4DVISFTyuM7wMlbuT/Gim+Pr7epk2pSfUpzMwo6/hujzg53Fcu5YLbljP1m1jDMzoQxUeGx1LPT/bVfZJjD6KaGqsKqk5i1V1O87csxK4C7hGVdeLyIUistAnWw7sDlwrIneIyIq05Ck6QcdnEiTRm4/jfM7CEZoEneRHI4drzUG9dOHB9PXKpOtPPOX8CkGndm2T9yBjO5VHt42hwKPbxtg6OpZJfvb3hTcBUeeh/d+86MuVVJlU5xGo6k3ATXXnPhb4fHyazy8btaF9lG0eYKA/fB2WepIIbY3jfC5ybH2NoeERekRCF0eLkx9Rjth6O/rSFesnjQrGdirLV27g1iXHjaedu+TGluRvJz/j9thHt+8Mf2bEeWjeoEc9t5tMjd2GzSwuIItPOIDF162dNNu3B1i68ODY90gixr6Z3bnolbvWew1TAnHzI2401mMxw30HZvTx6LbwtFG0kp+tmGCiYkUaxZA0mk/R6LlR720hrvljiqCA1CrrBTesH684A/19LF14cOxeYVbrtRR9p6goR2+vSEuRMXEcsXHyYmh4ZNxc1Aqt5Gcro7TeiJFSmPkqKEvUiLXRSCHsvft6pRDLlVQdUwQFJYn4+Cxi7LOe3dsqUb3XnaqJ502cvFi+csP4wn5xaTU/WxmlnbFgFt9adV/o+SjiBjYEnxv13rtNnVIYE2KVMUXQpWQVyVP0lSKzGLEMDY9MGL0JbpLZYEheNDLx1OYcDMzo46mxHYyOOTv99AaO2zBaeeeLFh0KwJW3bWKHKr0inLFg1vj5MOp/8yj/S/C5Ue8dZU4zssV2KOtCunmSUKsKLu28GBoeCfXnRE38izNJr1OZs/79G02GrD13+coNoe/dK8JO1cJ1ILoR26GsoKS1u1a3hum1E7aY9npEy1duCF3CuxYtVE+ckNxOf78k3zlOGY0aXQX9MGHvDW4uRZHDjquCmYZyIs1N54seyROklR5+u6GqafpKGuVp2LU4prQkfr8k3jlu9FGjCXMfvPoOPnj1HQwO9PPnLx3klt9siTQnFS3suEqYIsiBoeGRCUqgRlIVoeiRPDXiNjQ1ZREVqZKngmsUQdNoccDg+50/tG58E/joWJ3sf7+4ijeo3KLyYmTrKNevGRkfIUTNpShiZ6UKmGkoB9LedD7J5bHTJI4JJGgOiiJPBXfsgXuHnu/riRcWef7QOr616r7x3rH6v3qifr8kzItR92hlZLLo8EFuXXJcw7DT4G9ry2YXCxsR5ECjxj6JipB3JE9cc0+chqbZgm95Krih4RGuXzO54Z3R18On3nhYrPy+8rZNTdNEzXlIYu2eRvdoZ2TZKHoIdv22eYQdl2FNrLwwRZADURVMILGKkNduVHEap1qFjGoygg1Ns3DLPCtzlJJ61m7TYsvUrOGE6DkPSSzv0ege7TTWURPUatR+26w7K7bgXWNMEeRAWAUT4MyjZpe+UDZrnJqt7V/f0EQpzSLsiZCEU7dZwwnRPfAknt/oHu001lET1GDyb5tlZ6UMa2LliSmCHMjbdJMmzRqnRqaesB5+kWcuJ+GUb9RwQuN3TeL5ze5R31jX/AlR5bZ+glqNvEdvZYqkywNTBDmRl+kmbZo1LFEVTyC0h19kpZmEkqpvOAWYMbWXbc/saPquSTy/lXvENa9ctOjQhjOT86AskXR5YYqgS8nLMdasYWmnQhZVaSalpNptOJN4fiv3KLN5pcgjyyJgS0x0IXkvMdFICeUtm9E+UUtJJLH3chYdl6pHDeW1Z3FhqFoByLvn1qgHX2RTj9GYtMwrWUX0FHVkWQS6XhEkVcjKpEyK7hizCllO0jKvRHVcLrhhfWnqXNnpekWQRO+4bDHI3eQYK5MC7nZq+R7ckrPVJbLDiOqgPLptbHxp76LXubLT9Yogid5x3qaWVimzYyzY8M/s7+PJZ7aPr+5pjUExeDqwn/Gj28Y6/k0ardcUpMh1rux0/VpDSaxpUnRTSz1pL72cFvXLTG8dHZu0xHM3LKddZtJY4jxqieowilrnyk7XjwiS6B2X0dRSRjt8s3WFalhjkB9pdIrCAgiefHr7uPkpSJHrXJnpekWQRJRKmU0tZSJuY2KNQXK06oNJq1MUNoPZ6lx2dL0igM57xxbymA1xbMVVbwySdJ63skBg7XnHHrg3168ZSb2BDqtzxx64N8tXbuBDV99hdTBhbEKZURjCeoF9PcLu06ewddtYYpW/rJFISU/Ga7Z/ctTzgjuNZZV/NhGxcyo/ocwoB1mMvMoWChwkylF77jVrgdblb2eBwNGxHdzymy2Zr/xatsi9smGKwCgUaTu5y9ygRDXcO1TbUmbtLhCYh7O+SLJ0I10fPmoYNYaGRwq573FcGjlk2wnhbLalaZG2k8xSliS2/ywbpgiMSlAzCUVRhkikZvH2rSqzZvNNirT3dVay1M9lqZkOu10ZmGnIqASN5iiUJRKp1kCfe83a0F3N2lFmZVkgMCtZymw67ARTBEbhCUb5DMzoQxUeG20tiqhRb7nokSf1UU5nLJiVSQgnFGtiYhayVNUXYYrAKDT1UT61Rchg17B99e8eaRrO2Gjv46I0dGGERTldv2YklxDObiWoaHsi9pAug+mwE0wRGIWm2bITo2M7uGLVfeMbpkSFg5Z1dniRQjiTIM4cjiznedQr2jAlUIZy0immCIxIijDxKs6QvL7qhtl0i2TvboVuMlUMDY+w+Nq1jO3ctZrs4msnzoFoZZ5HWPmEXb/xzP4+xnbs5Mln3L36+3qY3tc7YXJiVEejV4SdqqUpJ52S6sxiETkRuBjoBS5T1WV116cBlwMvBR4GTlPVexvdsxtnFrfS4DbbBrKdhi6qQnU6y3doeIQLblg/bs4Z6O9j6cKDY1eq84fW8a1V98VKW0/99olFUGrt0Gz2bxok4ZMJ3mdk6yi9ESYX2FUugvsc1BN836HhkdC0vT2C7lR2ht0gAwSYMbV3XPFEMbVXmDF1Co+Njk3I39rnraNj4/nVI+D1JiKg6vKinfLbaGZxaopARHqB3wKvATYDtwNnqOqdgTTvBQ5T1feIyOnAn6nqaY3u222KoJWp843SwuSGO84U/Kh7TpvSE1kp49x/aHiExdetnbSMdF+PsPzUFzctxHGVgDB5RACTG46yLk+QtexhzwsS99nN7lNPX4+MjxSiuHfZyS3ft1tppww0UgRpziM4Etioqner6jPAVcApdWlOAb7hP18HvFpEJEWZCkcr67s3StvuOvFR32umBJrdf/nKDZOUAMDYTo018enK2zZFXhvo7xuPez/zqNlN48vTWEM/K7LeWyKOTyZOvsVdUrxGMyXQ65uFVu/brSRdftP0EQwCwdq8GVgQlUZVt4vIY8CzgYeCiUTkHOAcgNmzZ6clby60YgNux17czJbcqa05DZkg3GlX446Pv3bC8fz992xo9im7nT3LEM44eZJUmlaolYey/GZZkGRelMJZrKqXApeCMw3lLE6itLK+e7O07awTH3XPZ83o46mxnU17X42m/kct5xAnFC/KptwbMmBs1lCWcWOhvIizFHicfIu7/WRfr7Db1ClNR6CD/plx71sFkiy/aZqGRoBZgeP9/LnQNCIyBZiJcxpXhlamzjdK2+4U/KjvffwNB08wSQz099HXK5PSRd1/8QkHTEoPzhYcJxTvjAWzWjrfiCItlVB0mi1jETffGt2nVioGB/pZ/qYXs3ThwfT1RFuEg89sdN8ecX9VIOnym+aI4HZgnojMxTX4pwNvrkuzAng78HPgTcDNWrYNEjqklbDGOGlbjYxpds/6XaPi3r92vt2ooYsWOQf4lbdtYocqvSKcsWDW+PlWKGvoaB7U51W7UUPB+wSjhhpFvAQjgWrRMvXpm903KHt/Xw+j23eSVYtS9KihhrKnHD56EvB5XPjoV1X1kyJyIbBaVVeIyHTgm8DhwCPA6ap6d6N7dlvUkGEYRhbktjGNqt4E3FR37mOBz08Bp6Ypg2EYhtEYW4baMAyj4pgiMAzDqDimCAzDMCqOKQLDMIyKk2rUUBqIyBbgd3nL4dmLulnQJcJkz56yyg0me14kKfv+qrp32IXSKYIiISKro8Kxio7Jnj1llRtM9rzISnYzDRmGYVQcUwSGYRgVxxRBZ1yatwAdYLJnT1nlBpM9LzKR3XwEhmEYFcdGBIZhGBXHFIFhGEbFMUXQASJyroioiOzlj0VE/p+IbBSRX4nIEXnLGERElovIb7xs3xWRgcC187zcG0TkhBzFjERETvTybRSRJXnL0wgRmSUit4jInSKyXkQ+4M/vKSI/FJH/8f+flbesYYhIr4gMi8j3/PFcEbnN5/3VIjI1bxnDEJEBEbnOl/O7ROTlJcrzD/my8msRuVJEpmeV76YI2kREZgGvBYI7rL8OmOf/zgG+mINojfghcIiqHgb8FjgPQEQOwu0XcTBwIvAFEYnenSQHvDyX4PL4IOAML3dR2Q6cq6oHAUcBf+3lXQL8WFXnAT/2x0XkA8BdgePPAJ9T1RcCjwLvykWq5lwM/IeqHgi8GPcOhc9zERkE/gaYr6qH4JbuP52M8t0UQft8DvgwEPS2nwJcro5VwICIPC8X6UJQ1R+o6nZ/uAq3axw4ua9S1adV9R5gI3BkHjI24Ehgo6rerarPAFfh5C4kqnq/qv7Sf34c1yAN4mT+hk/2DWBRLgI2QET2A04GLvPHAhwHXOeTFFXumcArga8AqOozqrqVEuS5ZwrQ73drnAHcT0b5boqgDUTkFGBEVdfWXRoENgWON/tzReQs4Pv+cxnkLoOMoYjIHNzmS7cB+6jq/f7SA8A+ecnVgM/jOjk7/fGzga2BTkRR834usAX4mjdrXSYiu1GCPFfVEeAfcRaG+4HHgDVklO+l2Lw+D0TkR8BzQy59FPgIzixUOBrJrar/7tN8FGe6uCJL2aqIiOwOXA98UFX/6DrXDlVVESlU/LaIvB54UFXXiMgxOYvTKlOAI4D3q+ptInIxdWagIuY5gPdbnIJTZluBa3Fm2kwwRRCBqh4fdl5EDsX9WGt9pd4P+KWIHInbmzm4u/p+/lxmRMldQ0TeAbweeHVgf+jc5Y5BGWScgIj04ZTAFar6HX/6DyLyPFW935sNH8xPwlCOBhb6bWanA/8HZ3cfEJEpvnda1LzfDGxW1dv88XU4RVD0PAc4HrhHVbcAiMh3cL9FJvlupqEWUdV1qvocVZ2jqnNwhe8IVX0AWAG8zUcPHQU8FhiS5o6InIgb8i9U1W2BSyuA00VkmojMxTm7f5GHjA24HZjnoyim4hxpK3KWKRJvV/8KcJeq/nPg0grg7f7z24F/z1q2Rqjqeaq6ny/bpwM3q+qZwC3Am3yywskN4OvgJhE5wJ96NXAnBc9zz33AUSIyw5edmuyZ5LvNLO4QEbkX5+l/yP+A/4ob0m0D3qmqq/OUL4iIbASmAQ/7U6tU9T3+2kdxfoPtODPG98Pvkh++l/p5XETFV1X1k/lKFI2IvAL4GbCOXbb2j+D8BNcAs3HLqf+Fqj6Si5BN8Kahv1PV14vI83EO+j2BYeAtqvp0juKFIiIvwTm5pwJ3A+/EdXgLn+cicgFwGq4ODgNn43wCqee7KQLDMIyKY6YhwzCMimOKwDAMo+KYIjAMw6g4pggMwzAqjikCwzCMimOKwDDaQESeaHJ9QETem5U8htEJpggMIx0GAFMERikwRWAYHSAiu4vIj0XklyKyzi9ICLAMeIGI3CEiy/OU0TCaYRPKDKMNROQJVd29tmSwX1BuL9zy3vOA/YHv+bXlDaPQ2KJzhtEZAnxKRF6JW0pikAIuc2wYjTBFYBidcSawN/BSVR3za09Nz1ckw2gN8xEYRmfMxK3fPyYix+JMQgCPA3vkJ5ZhxMcUgWF0xhXAfBFZB7wN+A2Aqj4M3Oo3IjdnsVFozFlsGIZRcWxEYBiGUXFMERiGYVQcUwSGYRgVxxSBYRhGxTFFYBiGUXFMERiGYVQcUwSGYRgV5/8DwEjgQtgUGXAAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -1464,7 +4237,7 @@ }, { "data": { - "image/png": "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", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEWCAYAAABrDZDcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAAsTAAALEwEAmpwYAAAzM0lEQVR4nO2de5gdVZXofyudA3QQ04mJCA0hESEIoolERaNXYMQgDBBFbkC8yIzKOPPp+MwYLnyCyAwZM446d1AHH+NbXkqMgBPU4MyYESUxiZFANICSdAKER1BIA51k3T9qn1BdXXVO1TlVp17r93399an3qr137bX3WmvvLaqKYRiGUV/G5S2AYRiGkS+mCAzDMGqOKQLDMIyaY4rAMAyj5pgiMAzDqDmmCAzDMGqOKYIaIyIqIi/KWw5jNCJyhYg8LCIP5C1LHETkPBG51bedWrkSkZ+KyLs6vHa6k2V8GrJUGVMEHSAibxORVSLyhIhsE5EfishrU7jvV0XkipRkTO1eRcK91y4ROShvWcIQkRNEZEsX108DPgwcraoviLj/Hlf2/iQiG0XkL7qRuVtU9Vuq+sY8ni0iR4rI9U5xPi4ivxaRD4lIXx7ylBVTBAkRkQ8BnwH+ATgQmAZ8DjgzR7FqgYjsD5wFPA68PWdxsmIa8IiqPtTinK2q+hzgucBHgS+KyNHBk3rREs6ztS0ihwO/ADYDx6rqROBsYA5wQF5ylRJVtb+Yf8BE4Ang7Bbn7IunKLa6v88A+7pjJwBb8Fp8DwHbgL9wxy4ERoBn3DN+4PYfDHwX2A7cB/yt2z/Z3et0t/0cYBNwftS9QmRV4EW+d/u6e84fgEuAce7YBcDPgH8CHnNyvCninh8Fbgjs+yzwL7573Qv8yd3nvATpfz7eR/9+4DeBY5cB1wPfdPdeDxwJXOTSejPwRt/5BwPLgEddur3bd+yrwBW+7ROALb7t3wMfAX6Np5SuBfYD9geGgT0u3Z8ADo4oR2PSGnhD4Pqvhlw7Sha3bzvwVpe2K4FPA48AV+CVx38C7gceBL4A9LvrpgA3ATtcOvy3L88PBb7n7v0I8K++/As+4wLgZ4Fy9bcunx8GljTv647/JXCXK0vLgcN8x04G7nbp+q/AfwLviigP3wRublFepjtZ3uHe/2HgYt/xVwI/d++/zT1vn8B7vAf4nTvnKkDcsT7gU+6e9wHvdeeP9+Xxl919h1w69eVdh0WmVd4ClOkPOAXY1czsiHMuB24Hng9MBf4H+IQ7doK7/nKgAZwK7AQmueNfZXQFNA5YDXwM2Ad4ofu45rnjbwQecM/6Ir4KOHivCFn9iuDrwPfxWlLTgd8C73THLsBTLO92H8Bf4yk5CbnnYe6dDnDbfe5jOB6vovwjMNMdOwg4JkH6/wT4JF5PbBdwnO/YZcBTwDxgvHuf+4CLXVq/G7jPd/5/4fXk9gNm4VV4J0XkwwmMVQS/xFMmk/EqtfeEnRvxHq3SuuX1/uOufLzZ5c1Ml0+7gPe5NOjHq7CXOTkPAH4AXOmuvxJPMTTc3+sAcXm2zl27v0uj1/rKQvAZFzBWEdzmnjnNvd+73LEz8RTvi931lwD/445NwVPib3XyfNA9K0oRPIBrSEUcn+5k+aKT82XA08CL3fHj8MrleHfuXcAHAu9xEzDg3mM7cIo79h5gA3AIMAn4MaMVwY3Av7n0e74rL3+Vdx0WmVZ5C1CmP+A84IE259wDnOrbngf83v0+Aa/FN953/CHgePf7q4yugF4F3B+4/0XAv/u2/x9e63cIeJ5v/6h7RciqwIvch/8Mnl26eeyvgJ+63xcAm3zHJrhrXxBx358B57vfJwP3uN/747WszsK1ShOk/TS8lvIst70c+Kzv+GXAj3zbp+O1qvvc9gFO5gG81u5unLJyx6/EtcBD8uEExiqCt/u2Pwl8IezckPdol9btrj/BpcMOvFb8WuAcXz7d7ztXgCeBw337Xo1TiHgNku/jGgOBc7YT0uAJPsO3L6gITvFt/w3wE/f7hzil57bH4TUcDsPr8d0ekH8L0YpgxP+ckOPTnSyH+Pb9spleIed/ALgx8B6v9W1fByxyv1fgq9jxenOKp1QOxFM4/b7j5wK3JSnzvfwzH0EyHgGmtLGLHozX3W/yB7dv7z1UdZdveyeeWSeMw4CDRWRH8w/4v3gFrcnVwEvwKrFH4r3GGKbgtcCCcg/6tvdGsKjqTvczSu5v4xV8gLe5bVT1SWABXmtqm4jcLCJHxZTx/wB3qepat/0t4G0i0vCd86Dv9zDwsKru9m03ZT4YeFRV/+Q7P/i+7fBH9LTKwyBx0rodW1V1QFUnq+osVb3Gd2yz7/dUPKW92ld+/sPtB89kswm4VUTuFZFFbv+hwB8C5dTP5oj9Uef4v4HDgM/65HkUr8IfdOfsvU69GrTVsx7B61W2IzSvnKP5JhF5QET+iOf3mxLn2qCsgd+H4eXxNt97/htez6CQmCJIxs/xNP38FudsxSsITaa5fXHQwPZmvNbbgO/vAFU9FcBFRlyNZ2r4m0DIXvBerXgYr3UVlHsowT38XA+cICKH4Jkuvr1XKNXlqnoy3gd8N163PQ7nAy90H+0DwD/jfbSndiDfVmCyiPgdiv73fRKvAm0yJnqnBe3SPe20bvX8h/EU4DG+8jNRPUczqvonVf2wqr4QOAP4kIj8GV65m9aiwROnbB3q++3/BjbjtaT9ZbpfVf8Hz4S49zoRkcB9gvwYr3fZKZ/HK4NHqOpz8RpZEvPabXhmoSZ+OTfj1RNTfO/4XFU9pgtZM8UUQQJU9XE8e/1VIjJfRCaISENE3iQin3SnfQe4RESmisgUd/43Yz7iQTw/QJNfAn8SkY+KSL+I9InIS0TkFe74/8X7KP8Sr3X3dV/YXPBerd5rN1639+9F5AAROQz4UAK5g/fbDvwU+Hc8RXYXgIgcKCJnuuifp/FMN3va3U9EXg0cjufcm+X+XoKnYM7vQL7NeL6bK0VkPxF5KfBOnn3ftcCpIjJZRF6AZzKIy4PA80RkYsSzU03rVqjqHjxF+2kReT6AiAyKyDz3+89F5EWuwn0cz1y2B6/cbQMWi8j+Lo3mJnz8QhGZJCKH4jn3r3X7vwBcJCLHOBkmisjZ7tjNwDEi8hanhP6W1kr4UuA1IrLE5RPufb4pIgMxZDwAz2f1hOuZ/nWC97sOeL9LzwG8IAkAVHUbcCvwKRF5roiME5HDReT1Ce7fU0wRJERVP4X34V6CZ0fdjBcxsNSdcgWwCi+iZD3wK7cvDl8GjnbdyaWu0vhzvIrvPrwW3peAiSJynJPjfHfeP+IphUVh94rx7PfhtYTvxbPxfxv4Sky5w/g2nt30275945zMW/FMAq/HfXwi8joReSLiXu8Avq+q61X1geYfXjTSn4vI5A7kOxfPhrwVz7F3qar+2B37Bp6z9Pd4H/S1IdeHoqp34zUG7nVpf3DIaWmndSs+imf+ud2ZP36M51gGOMJtP4HX2/2cqt7mytPpeP6j+/Hs9AsSPvf7eIEOa/Eq+C8DqOqNeGX1GifPb4A3uWMP44V/LsYz+xyBF6EUiqreg+fPmA7cKSKP40XYrcJzOrfjI3imyz/hKczY+ezOvxXvO18D3ILn2G6aIs/HC/DYgBcddQPxzFi50AyFMgzDMDpERN6EFzBwWNuTC4j1CAzDMBLiTLWnish4ERnEM1PdmLdcnWI9AsMwjISIyAS8wW5H4Tnkbwber6p/zFWwDjFFYBiGUXPMNGQYhlFzSjc965QpU3T69Ol5i2EYhlEqVq9e/bCqTg07VjpFMH36dFatWpW3GIZhGKVCRP4QdcxMQ4ZhGDXHFIFhGEbNMUVgGIZRc0wRGIZh1BxTBIZhGDWndFFDhpEWS9cMsWT5RrbuGObggX4WzpvJ/NlJlgUwjGpgisCoJUvXDHHR99YzPOJNFjm0Y5iLvrcewJSBUTvMNGTUkiXLN+5VAk2GR3azZPnGnCQyjPywHkHJMHNGOmzdMZxov2FUGesRlIimOWNoxzDKs+aMpWvSWuWwPhw80J9ov2FUGVMEJcLMGemxcN5M+ht9o/b1N/pYOG9mxBWGUV3MNFQCmuagITNnpEbTnGZmNsMwRVB4gtEtYZg5ozPmzx5MXPH3ykdjviCjl5giKDhh5iA/Zs7oHb0KOW31HLBejJE+pggKTiuzz6BVBD2llY8mzTyIes7Hf3AnT43ssbEPRuqYIig4Bw/0h/oGBgf6WbnopBwkqi+9CjmNut9jO0fG7MtCEYVhpqpqY1FDBceiW4pDr0JOk94v62ABC1uuPqYICs782YNc+ZZjGRzoR/B6Ale+5VhrjeVAr5Ry1HMG+huh52cdLGBhy9XHTEMloJPolrQwk8Cz9CrkNOo5wJgIskaf8OTTu5ix6ObM5LFR2NXHFIERiU3MNpZeKeVWz2kqiIEJDZ54ahc7hj3fQVb5E+WnsrDl6mCmISMSMwkUj/mzB1m56CTuW3waE/YZz8geHXU8i/ypqp9q6Zoh5i5ewYxFNzN38Ypa+zxMERiRmEmg2PQqf4J+qoH+Bvs1xvHBa9eWtgI1B/hoTBEYkdjEbMWml/nT7Il8esEsnt61h8d2jpS6ArXe7mhMERihLF0zxJNP7xqzvwomgaqQh8mmrBVo0Axk83aNxpzFxhii5jeaNKHBpacfM8oRaVFF+ZHHxHlFMxfGKX9hQQ8CaMj96trbNUVgjCFqfqMJ+4wfowQsqihfeh1aXKQIorjlL6w8K4xRBnXu7ZppyBhD3FZfWc0ERucUKYIobvmLKs8KNlDTYT0CYwxxW31FMxMY2VOkdRzilj+br6s91iMwxhC31WdRRfVk/uxBFs6bycED/WzdMcyS5RtziRqKW/6K1IspKqYIjDHEnd/IPrB6UpQY/Ljlz+brao+ohvnOU7q5yCnAZ4E+4EuqujhwfBrwNWDAnbNIVW9pdc85c+boqlWrshHYSIxFDdWPqPDLPEwtVv7iIyKrVXVO2LHMfAQi0gdcBZwMbAHuEJFlqrrBd9olwHWq+nkRORq4BZielUxG+uQ5IZ6RD0XyDVn5S4csTUOvBDap6r2q+gxwDXBm4BwFnut+TwS2ZiiPYRgpYL6h6pGlIhgENvu2t7h9fi4D3i4iW/B6A+8Lu5GIXCgiq0Rk1fbt27OQ1TCMmJhvqHrkHT56LvBVVf2UiLwa+IaIvERV9/hPUtWrgavB8xHkIKdh1I4o+3uRQkiNdMhSEQwBh/q2D3H7/LwTOAVAVX8uIvsBU4CHMpTLMIw2tBu1a7b5apGlaegO4AgRmSEi+wDnAMsC59wP/BmAiLwY2A8w249h5IyNGq8XmSkCVd0FvBdYDtyFFx10p4hcLiJnuNM+DLxbRNYB3wEu0CzjWQ3DiEWRIoOM7MnUR+DGBNwS2Pcx3+8NwNwsZTAMIzlFmlzOyB4bWWwYxhgsMqhe5B01ZBhGAbHIoHphisAwjLahokWSyUgfUwQ1wD6o3lK29C7iAkNFlKnKmI+g4hRlpsi6UMb0LmKoaBFlqjKmCCqOfVC9pYzpXcRQ0SLKVGVMEVQc+6B6SxnTu4iTyBVRpipjiqDi2AfVW8qY3kUMFS2iTFXGFEHFsQ+qt5QxvYu4glcRZaoyma5QlgW2QllyyhbFUnYsvY0i0mqFMlMEhmEYNaCVIjDTkGEYRs0xRWAYhlFzTBEYhmHUHFMEhmEYNccUgWEYRs2xSecMwwjFwmDrgymCgmIfoZEnNvtnvTDTUAEp4wyWRrUo4+R5RueYIigg9hEaeRM1Sd7QjmFmLLqZuYtXWMOkQphpqICUcQbLsmAmt3hELV4PjOqlgpmKqoD1CApIGWewLANmcotP2OR5QYZHdvPh69ZZ+lUAUwQFpIwzWJYBM7nFJzj7ZxS7VU2ZVgBTBAXEpuDNBjO5JWP+7EFWLjqJ+xafxmCL3qgp0/JjPoKCMn/2oFX8KRNl9zaTW3sWzps5Kpw0iCnTcmOKwKgNYZVZmMmtnUO5jg7n5vt9+Lp17A6Zut6UabkxRVAS6lj5pE0zvdpV8q0GUtV5oFXz/eIoU6Nc2MI0JSBY+YD38ZnfIH3mLl4Raj4aHOhn5aKT2h6vA9YoKSetFqaxHkEJaBXtYh9gurRzKJvD2fxXVcSihkqAVT69o90YDhvjYVQRUwQlwCqf3tFuDIeN8TCqiCmCEmCVT+9oN4bDxngYVcScxSXBHHSGYXSDOYsrgDnoDMPIikxNQyJyiohsFJFNIrIo4pz/LSIbROROEfl2lvIYhmEYY8msRyAifcBVwMnAFuAOEVmmqht85xwBXATMVdXHROT5WcljGIZhhJOlaeiVwCZVvRdARK4BzgQ2+M55N3CVqj4GoKoPZSiPYRg5YP6t4pOlaWgQ2Ozb3uL2+TkSOFJEVorI7SJySobyGIbRY2wNiHKQd/joeOAI4ATgXOCLIjIQPElELhSRVSKyavv27b2V0DCMjrE1IMpBlopgCDjUt32I2+dnC7BMVUdU9T7gt3iKYRSqerWqzlHVOVOnTs1MYMMw0sVGxZeDLBXBHcARIjJDRPYBzgGWBc5ZitcbQESm4JmK7s1QJsMweoiNii8HmSkCVd0FvBdYDtwFXKeqd4rI5SJyhjttOfCIiGwAbgMWquojWclkGEZvsVHx5cBGFhuGkSkWNVQMbGSxYRi5YaPii48pggJhLSfDMPLAFEFBqPMSiIZh5Eve4wgMh8VbG4aRF6YICoLFWxuGkRdmGioIBw/0hy6Knme8dR19FnV8Z8OwHkFBKFq8dR3niMninZeuGWLu4hXMWHQzcxevqHT6GeXFFEFBKNoSiHX0WaT9zpcsXc8Hr11bK2VqlBMzDRWIIsVb19FnkeY7L10zxLduv5/gcM2mYilKPpcNM91lQyxFICITgA8D01T13W5BmZmqelOm0lWMMhXiIvossibNd16yfOMYJdCkyso0SyzEOjvimob+HXgaeLXbHgKuyESiilI2m3vRfBa9IM13blXZF02ZlsWPUUdzZa+IqwgOV9VPAiMAqroTkMykqiBlK8RF81n0gvmzBznruEH6xCvafSKcdVwyc12zUo3qDQgUSpmWqYFSR3Nlr4jrI3hGRPrBK98icjheD8GISRkLcZF8Fr1g6Zohvrt6iN1uIsbdqnx39RBzDpscKx2CposgApx3/LRCpWmrBkqR5IR6mit7RdwewaXAfwCHisi3gJ8Af5eZVBXE5mUvPt322sKubzI40M+nF8ziivnHdi1nmpSpgVJHc2WviNUjUNUficivgOPxGjbvV9WHM5WsYiycN3NMa9EKcbHotlKMOk+AlYtO6lSsTClTK7vZQylCwEWZAj/iEDdq6OXu5zb3f5qITAT+4BagMdoQVYgB5i5eUZkCVWa6rRTLVKk2KVsDpQjmyipGL8U1DX0OuB24Gvgi8HPgemCjiLwxI9kqx/zZg6xcdBL3LT5tbwuxLI66OtCt6aGMpos6BgV0S9kCP+IQ11m8FXinqt4JICJHA5fj+Qm+B9yajXjVpkyOujrQremhSKaLJBShlV0myuRXiUtcRXBkUwkAqOoGETlKVe8VsSjSTqligSo73VaKnVxfNXtz1SmjCbAdcU1Dd4rI50Xk9e7vc8AGEdkXN7bASI5FEhlliuM3PMpoAmxHXEVwAbAJ+ID7u9ftGwFOTF+selDFAmUko4r25qpTRb9K3PDRYeBT7i/IE6lKVCPKalOuE1mbbcw8WE6q5leJGz46F7gMOMx/jaq+MBux6kPVClSV6EWYYBXtzUb5iGsa+jLwz8BrgVf4/gyjsvTCbGPmQaMIxI0aelxVf5ipJIZRMHphtvGbB4d2DNMnMkrZWG/R6AVxFcFtIrIEb8zA3snmVPVXmUhlGAWgV2abZmVftdGqRnmIqwhe5f7P8e1ToJgTqBhGCiSZfqFbp7INLjTyJG7UkIWIGqWj28o5blRXGk5lix4y8iT2msUichpwDLBfc5+qXp6FUIbRLWlF/MSJ6kqjNW/RQ0aexIoaEpEvAAuA9+HNqns2XiipYRSSXg7USqM1b9FDRp7EDR99jaqeDzymqh/HW7v4yOzEMozu6KWpZWJ/I9H+MKo4WtUoD3FNQ82vZ6eIHAw8AhyUjUiG0T29NLVEzbuYdD5GG1zYPTaBX2fEVQQ3icgAsAT4FV7E0JeyEqruWGHunl4uuLJjZ/i8i1H7w7A8754qLhjTK+JGDX3C/fyuiNwE7Keqj2cnVn3pZWGucuXTy3mcuu19WAWWDhaC2zlJooZeA0xvXiMiqOrX21xzCvBZoA/4kqoujjjvLOAG4BWquiquTFWkV4W5DpVPr0wt3fY+rAJLBwvB7Zy4k859AzgcWAs0S6wCkYpARPqAq4CTgS3AHSKyTFU3BM47AHg/8IukwleRXhVmq3zC6aSX1G3vwyqwdLAQ3M6J2yOYAxytqprg3q8ENqnqvQAicg1wJrAhcN4ngH8EFia4d2XpVWG2ymcs3fSSuul9WAWWDr30C1WNuOGjvwFekPDeg8Bm3/YWt28vIvJy4FBVvTnhvStLr+LJbXW0seS1SEyneb50zRBzF69gxqKbmbt4Re1XNbMQ3M5p2SMQkR/gmYAOwFua8peMnnTujE4fLCLj8Ka2viDGuRcCFwJMmzat00eWgiycnGHmDms9jSWvXlIneV4HH08nWAhuZ0gra4+IvBs4EPjvwKHXAdtU9cstrn01cJmqznPbFwGo6pVueyJwD8+ucPYC4FHgjFYO4zlz5uiqVbX2JyciWGGAV+Ff+ZZjAVsdzc/cxStCTTSDA/2sXFSs+RXLJKtRDERktarOCTvWzkdwJnCRqq4P3PBR4B/wFqyJ4g7gCBGZAQwB5wBvax504adTfPf8KfCRukcNpU0rc8fKRSfVuuIPUqZekvl4jDRp5yM4MKgEANy+6a0uVNVdwHuB5cBdwHWqeqeIXC4iHZuUjGRYhRGfMtmYzcdjpEm7HsFAi2NtS5yq3gLcEtj3sYhzT2h3PyM5UREpAxPiz4NTJ8piYy5T78UoPu16BKucn2AUIvIuYHU2IhlpsnDeTBp9Yye9eeKpXbWPMikzZeq9GMWnnbP4QOBG4BmerfjnAPsAb1bVBzKXMIA5i5Mz6+O3smN47Lw35lg0jPrQsbNYVR8EXiMiJwIvcbtvVtUVKctoZMjjIUoAzE9gGIZH3EnnbgNuy1gWIyNs5KphGK2IPemcUV7Msdgb/AP3JvY3EPGmorYxGkbRMUVQA3o5JXNdCQ7c8/tkbNSvUXRMEdSEsoRFlpWwgXt+bGZXo8jEnXTOMIwWxHG8m3PeKCrWIzCMFIhyyAfP6YYqryhn5IspAiMxnVRIVa/Ewhzyfrp1zttso0aWtBxQVkRsQFm+hM1m2ugT9t9nPI8Ph0fItJoBtUqVWJZRQzbbqNEt3cw+ahijCHOKjuzWvVEyYS3VuiyLmaVD3iYPLBZV6+Gas9hIRJyKJ7iql1Vi3VP12UbLtNpas4c7tGMY5dnGT5FlbocpAiMRcSsefyVf9UqsF4QtZynAiUdNzUegFClbxZrXkqZZYorASERYhRSGv5Lv1TrMVWb+7EHOOm4Q/zyyCnx39VBhK8y4lK1irWIP13wEBaTI9sfgKOWBCQ2eeGoXI3ueDToIVvJlHtmcJC+yzrfb7t5OMLSjCr6WqAq0XThuXlRx7i5TBAWjDGGCQadonAqwjCObk+RFL/Ktii1RiK5YBS9dk5a1rKni3F1mGioYZesmg1fRrVx0EvctPq1S6yAnyYte5FtVfS0L581k7NJJnunLn35F8SVUcVEgUwQFo6qtvjKSJC9amTfSioKpqq9l/uzBMSavJv50LVIjqWqNH1MEBaOqrb4ykiQvWuVPWi3XKrZEmwzGSGtrJGWHKYKCUdVWXxlJkhftoqlatVyTxNBXrSXaJE5aWyMpO0wRFIwqt/rKRpK88J8bRVjLtSh277yJk9bWSMoOm2vIMFImybxANodQMooQNVRWbK4hw+ghJx41lW/dfv8oB2hUyzULu3eVK8syhiGXAVMEhpEiS9cM8d3VQ6OUgABnHRdegSUZnBSngi/DOBSjeJiPwDA6JMzJGxbiqHijgsOIa/eO60soUoilUR5MERhGB0RVzFHTIkSZeuI6pONW8BZiaXSCmYYMowOiKuY+EXaHBGC0CnGMY/eOW8FXcR6cIFX2geSFKYICYQW8PERVzLtV6W/0Rc5D02kex63gqzgPjh/zgWSDmYYKQpXiycu0yEinRLWwm6adMFNPN3kc15dQlnEonZaRNH0gdSincbEeQUGoynKOdWmxtWp5R5l6usnjJFN5Fz3EspsykpYPpC7lNC6mCApCL518WZqgqqLQ2tHJGgvd5nHRK/i4dFNG0vKB1KWcxsUUQUHolZMvTkto6ZohLlt2594F6SdNaHDp6cfE+kDKtshINyStmOvgyI1DNwoxLR9It0q5av488xEUgKVrhtj5zK4x+7Nw8rWzsS5dM8TC69ftVQIAj+0cYeEN62LZUKMqteYiI3Vm4byZNMaNnnm/MU4q48iNSzeTx6XlA+lGhir585qYIsiZZqF6bOfIqP0D/Y1MnHztWkJLlm8ctexkk5HdGsshF3eRkdoSTJywxKo43U4el8YMrJ3KsHTNEB++bl3lBu1lqghE5BQR2Sgim0RkUcjxD4nIBhH5tYj8REQOy1KeIhLWQgfYf9/xmXQ127WEWnWN43Sb4y4yUkeWLN/IyO7RqRNXwVaJIkQ2dSJDs9EWNk4Eyl2+M/MRiEgfcBVwMrAFuENElqnqBt9pa4A5qrpTRP4a+CSwICuZikivR4K2s7FG2bGbx+IwWGNbeJjtGDwlkHTUcbv7ltkmXQTHd1IZohptTcpcvrN0Fr8S2KSq9wKIyDXAmcBeRaCqt/nOvx14e4byFJJeOxDbRbssnDeThdevG2MeavTFt2UXZVBTlpVnVIUfdMQvvGEdKKHmtibt8tpCHYtBK4Vd9kF7WSqCQWCzb3sL8KoW578T+GHYARG5ELgQYNq0aWnJlxlJKqA8Ks1WLaHm/k6jhvz3yLMFm2XlGXXv/RrjxrQYg6agIHHyus6hjkm+pax7TVGNtj6RQg7aS0IhwkdF5O3AHOD1YcdV9WrgavAWpumhaIlJWgEVodKE0R/RxP4GIp4fs1N58u76Z1l5Rt27ldkgjMGYaVvXieQ6CXVukkWvKarRVnYlANkqgiHgUN/2IW7fKETkDcDFwOtV9ekM5ekJnVRAeVeawQ/O/1GV1QyRZeWZxj3irkC2dM0Q4zqYyC4N8vZLtPuWmqHOUWa3tHtNRWm0ZUGWiuAO4AgRmYGnAM4B3uY/QURmA/8GnKKqD2UoS88oY+utnRMsjQ+q15VKlr6Xif2NMS1Q8EJ+n961Z1RaNvok1Efw5NO79sadR6VLqyiVrM2H3ZjWwnqXO3aOJM73TkOd/QztGGbGoptTK3N5N9qyIrPwUVXdBbwXWA7cBVynqneKyOUicoY7bQnwHOB6EVkrIsuykqdXdDNQJS/iKKlul07s9QCcrBY6X7pmiCdDBv81xgmXnXHMmJDEJW99GUvOfhmTJjRGnb9jeISF169j4Q3rItMlSkH3wibd6eRuwbzeMTzCYztHOsr3bkKd/VRl0FeWZDqOQFVvUdUjVfVwVf17t+9jqrrM/X6Dqh6oqrPc3xmt71h8sqqAsiSOkupGkeWxalYwTnzShAb7jh/HB69d29VMk2FjAQCes9/4va3F4GCn+bMHmbDP2M73yB4dcy9/ukRVdHtUEymBTmbZ7LRnG7d3GYewbwlg5zNebyppmSz7oK8ssZHFKVOEwTJJifrgmnSryPIylzUr5U8vmMVTI3vYMdxZy9RPlMw7do41FcW5rtW53fYul64ZYtbHb+UD165N3Bvr9Nnd9i79SmvJ8o2cddwgA/2je1OP7Rzhou+t58Sjpo6ZsqObZ9cZUwQZkMYQ+E7ppPUXVF4D/Q0mTWikpsjyNpel2SPp9F2SvGvz3G56l00TTZgvI867d/rsbnqXYSbE764eQkLq+uGR3dx293aWnP2yUYpi0oQGn1kwi8ESmmjzpBDho0Y6dOPgy9IJlvcAszR7JJ2+S9h1jXFejK7fPOS/VzdRKu1MNO3evdNnh72nn1ZplTQsd+uO4ZbltgiDGsuCKYIK0W3sfFaRPXmF3TXfJyqupJPWYdS7AMxdvIKtO4YZmNBAFR4fHhspEzX9RFS6dKqg21X0cWf67GT8CNBR1FBSxdxuHWi/HFUK9cwCUwQVopuWb7cjcdspkV6H3QXfJ0g3rcPguwSf5Z9JNpiOrQYVpkmrOaPyHLneiiiZw8Jy47xDVUM9s8B8BBWiE/t106fwgWvXdmxHL+L87K1MI2k78NOMlEmDpWuG2LHzmdBj++9T3JGwUX6JsLDcor5DWbEeQYVIar9u12qGeL2JKJPUB65dy5LlG3PpkkfJLRBrRG8az0p6Thq0y9OBCfvsHZXbykzVyryVFe3MOXlX/HmPtM4SUwQVIqldtF1LFuLZkltVcnlNUdHLWV1bmWGajBNJdYRrFHGcxGFmwIXXrxvluG5l3sqSoppzqj4DrGjEIgtFZc6cObpq1aq8xUiNPFsZMxbdHOlIhfgTas1dvKJtRRh3bp20CGsZpzFBWFh+rfrDo3zz9vsT3SfpjK5xaZenzbDKTtaQ7nUeFomoMl6mNBGR1ao6J+yY9QhypFetjChl06olG3dmTGgfMgi9H8iTRdRIVH7tOz65q625DvRly+5M1fwSx0n8wWvXdnTvOg/GKuMcYkkwRZAjvZhnvpWySWtaXX+l22p1s173ftI2M6Q1/XSTkd26d8BXWo2AKKU80N/gsjO8HkirfGpFnQdj9XoBqV5jUUM50otWRjtlk1Y0RnM09WcWzAqN/DjxqKmFiyxKStatvzSii8Ly9DMLZrH20jfuzdew6JzGOPFmSo2g7oOxyjiHWBKsR5AjvWhltFM2abeao0wyVVhlKyq/Jk1o8NTIno57Bn7SUDbt8jTO4LaoqKEqR860ouoD1EwR5Egvpl7Io0sbVhFF2aXLZGONyq9LTz8GeNY0JrDXYTtpQoPTXnoQN63bFjrvT5BemRo6GdxW9ciZdhQ1oikNTBHkSC9aGZ0omyxafVWwsXYT537F/GNHpevAhAZPPLVr1MIqRTc1VKFXZ4Rj4aMpUeQuc9IFwLMKu6zqeq+dUuQyE0ZUaKoA9y0+rdfiGAmx8NGMKXqXOapLG1YRZdXqq7qNtRPKZmqoQq/OCMcUQQqUscscprw+eO3ayMFIvXBiGsUm7+nEg5StR1VkTBGkQBkHm4Qpr1ZGQmv1xaMolVMWchSpV1f0XnjZMEWQAmXsMidRUkV3YhaFolROWcpRlF5d1r3woij0XmEDylKgjINN4iopm/I3PmkuiVkFObIky154EadVzxpTBCmQ5gjdXtFuwXp4dkKtIr9HkSiKibAocmRJlutg10GRBjHTUEr4u8zNbuUHr11b2G5lcH4g/yAoKH6PpogUxURYFDmyJEvHdR0UaRBTBClTFDtxHMKUV11sollQlKiaPOVIWo46KXfNa4ZHdtMnwm7VRLPltqMOijSIKYKUKWMoKRTHCVhmWkXV9FLR5hXdk7QR1EmjKXjNbtW9Si6t9yuKQu8lNrI4ZWz0pRGkLqOq4yze4leI41xrvtX5nTwjDarYQ7aRxT2kjt1KozVl7SUmpZ1tPaw1n+Q+cZ6RFnXrIVvUUMoUOZR06Zoh5i5ewYxFNzN38YpKh8MViahKqpPFYYpMu0ieOGtkt7pPnGcYnWGKIGWKGkpax9joohBVSQlUKv3bNYLitNrbNZqK3NAqM2YayoAidivrYp4oIs11goOGEIVKpX87J3WU2bRPhD2qsWzxRZrmokqYIqgJdYyN9pOn82/+7EE+UIGFeeLQqhGUxhrZVXTiFgFTBDWhzk7stMd2dBIrHxyw16RX6V+ECrTb1nyZxuiUDVMEJaPTD7qOsdFN0jSLdVIZLVm+MTKkuFeDvIpSgSYxmwbL+s5ndpl5MyNsHEGJCItHB29d3EtPPyb2iMytO4aZ2N9ABHbsHKl8FzvNsR2dxLFHPb8pQzfpH6wsTzxqKrfdvX3MYkO9iL3vVOawd48q62GUaYxOnj2zVuMIMlUEInIK8FmgD/iSqi4OHN8X+DpwHPAIsEBVf9/qnp0ognaJH3X8kqXr+fYv7qe5rGx/YxxXvuWlodMyDExo8PTIbnaO7ImUI26F3eSSpev5zi82s1uVPhH2GS8MR9y/v9HHWccNjqkE5s8e5Lwv/pyV9zza8lmNccK4ccLTu7z7C3De8dPGrLU7sb/ByO49PPmM94EO9De47IxnF2/3P9u/r78xblTaCPCawydz59Y/7V3UPSx9gmlw7qsO5Yr5xwLPpv/QjuGWUw2kOQipVaUeNc1B1PP9+NM7LnEqy/5GX+TxTivQsHSf0BjH8K49+KuTYHosXTPEZcvu3JvffjnUnd9UZElDa6PSPvjMcQJ79NlnfW/1ltBvdtKEBqe99KAx39NVt/2O3z30ZMtnhynnm9ZtG/PeEN9HkoYCyUURiEgf8FvgZGALcAdwrqpu8J3zN8BLVfU9InIO8GZVXdDqvkkVQbtRnVHHXz5tYmjlOQ745wWzAGK3WPw0+oQlb31Z20y8ZOl6vnn7/YnuHTZx3CGT9htTcJMw9/DJ/Or+x1u+5zigr08Y2f3s0xt9Asqoxdnj4E+fqDR4+/HTmHPY5Mj0D35caY7sbVeph903butWgE8vmBVbpjgKBthbWQfpRBEmaanDs+kBnX0vSQjL94XXr0tcBrt5NiR/z3b5kFb5baUIshxH8Epgk6req6rPANcAZwbOORP4mvt9A/BnIiJpCtFuStmo41Et6D3umriDY4KM7NZY09l+5xebE987WNyHR3Z3pQQAVt7zaNv33AOjlABuu5MP0J8+UWnwnV9sbpn+wSmD0xzb0W767rDpioPPj6IZThqXuBFHzfl4/HTqH0pa7pvp0en3EmSgv8FghIM9mPZLlm/siRLwP7uT92yXj72YFjtLZ/Eg4P+StwCvijpHVXeJyOPA84CH/SeJyIXAhQDTpk1LJES7sMlOwve6DfmLc33U8Ps60EyfqDTYrdo2DYPH0xrbEZy+O86zg89v1ZJPUraiIsGCDPp8Bd3apvP4Xpr0N/q47AzPdBhlovM/qyjrQLSjXeRYL0K/SzGyWFWvVtU5qjpn6tSpia5tNyS9k/C9gwf6uwr7i3NtX8KOUardqJxppk9UGvSJtE3DLMMy588eZOWikyJbpu2evXDezMj8SiJ3nMWF/DNzrlx0EvctPq2rxYby+F5gbC8uzlQTeawDkfSZcXpmvZhWI0tFMAQc6ts+xO0LPUdExgMT8ZzGqdFuSHrU8bmHTw693zh3TZyPMIxGn8Tqkp/7qkND94dl2KQJDc47flroexzx/P0Ty+hn7uGT277nOJxPwEejT2iMS66e/OkTlQbnvurQlunfq7DYTqc7mD97kPOOnzZGGSSVO8zk9fbjp2U6vUnSct98p06/l/5GH59ZMGuM8oqT9gvnzeyoDHZCJ+850N+IlT+9mFYjS9PQHcARIjIDr8I/B3hb4JxlwDuAnwNvBVZoyt7rdoNYWh1vFzXkvy7tqKFm9EgwYmbOYZMj3yXqWKuoIf99L75x/d5ooCJEDUWlgT+yJk7UUFZ0M0DqivnHtszLJDL0Muw3aBpLEjXUvC6qjESFv4a9X5y0b/7uddRQ2Dv5o4aSRg/2YlqNrMNHTwU+gxc++hVV/XsRuRxYparLRGQ/4BvAbOBR4BxVvbfVPes8jsAwDKNTcluPQFVvAW4J7PuY7/dTwNlZymAYhmG0phTOYsMwDCM7TBEYhmHUHFMEhmEYNccUgWEYRs0p3eyjIrId+EOCS6YQGKlcIsoqe1nlBpM9L0z27DlMVUNH5JZOESRFRFZFhUwVnbLKXla5wWTPC5M9X8w0ZBiGUXNMERiGYdScOiiCq/MWoAvKKntZ5QaTPS9M9hypvI/AMAzDaE0degSGYRhGC0wRGIZh1JzKKAIROVtE7hSRPSIyx7d/uogMi8ha9/cF37HjRGS9iGwSkX9Je5nMbmV3xy5y8m0UkXm+/ae4fZtEZFHvpR6LiFwmIkO+tD7Vdyz0PYpEEdO0FSLye1d+14rIKrdvsoj8SER+5/5PyltOABH5iog8JCK/8e0LlVU8/sXlw69F5OX5SR4pe6nL+hhUtRJ/wIuBmcBPgTm+/dOB30Rc80vgeLzp8X8IvKlgsh8NrAP2BWYA9+BN6d3nfr8Q2Medc3QB8uAy4CMh+0PfI295AzIWMk3byPx7YEpg3yeBRe73IuAf85bTyfK/gJf7v8UoWYFT3fco7vv8RQFlL21ZD/urTI9AVe9S1dirOYvIQcBzVfV29XLw68D8rORrRQvZzwSuUdWnVfU+YBPwSve3SVXvVdVngGvcuUUl6j2KRNnSNIozga+5318jpzIdRFX/C2/NET9Rsp4JfF09bgcG3PeaCxGyR1GGsj6GyiiCNswQkTUi8p8i8jq3bxDY4jtni9tXJAaBzb7tpoxR+4vAe113/is+s0SR5W1SBhmDKHCriKwWkQvdvgNVdZv7/QBwYD6ixSJK1rLkRVnL+hgyXZgmbUTkx8ALQg5drKrfj7hsGzBNVR8RkeOApSJyTGZCRtCh7IWj1XsAnwc+gVdBfQL4FPCXvZOudrxWVYdE5PnAj0Tkbv9BVVURKUV8eJlkdVSqrJdKEajqGzq45mngafd7tYjcAxyJt47yIb5TD3H7MqET2fHk8a/g7pcxan+mxH0PEfkicJPbbPUeRaEMMo5CVYfc/4dE5EY8E8SDInKQqm5z5pSHchWyNVGyFj4vVPXB5u8SlvUxVN40JCJTRaTP/X4hcARwr+uS/lFEjnfRQucDRWuZLwPOEZF9RWQGnuy/BO4AjhCRGSKyD3COOzdXAnbcNwPNKIuo9ygShUzTKERkfxE5oPkbeCNeei8D3uFOewfFK9N+omRdBpzvooeOBx73mZAKQcnL+ljy9lan9YeXGVvwWv8PAsvd/rOAO4G1wK+A033XzMHLwHuAf8WNtC6K7O7YxU6+jfiimvAiK37rjl2cd/o7mb4BrAd+jfdBHNTuPYr0V8Q0bSHrC/GiU9a58n2x2/884CfA74AfA5PzltXJ9R08M+2IK+vvjJIVL1roKpcP6/FF0hVI9lKX9eCfTTFhGIZRcypvGjIMwzBaY4rAMAyj5pgiMAzDqDmmCAzDMGqOKQLDMIyaY4rAMBIiIk/kLYNhpIkpAsMwjJpjisAwOsSNfF0iIr9x6wIscPtPEJGfisgNInK3iHzLjV43jEJSqrmGDKNgvAWYBbwMmALcISL/5Y7NBo4BtgIrgbnAz3KQ0TDaYj0Cw+ic1wLfUdXd6k1C9p/AK9yxX6rqFlXdgze9yfR8RDSM9pgiMIxseNr3ezfW+zYKjCkCw+ic/wYWiEifiEzFW9Kw+DNNGkYAa6UYRufcCLwabwZQBf5OVR8QkaPyFcswkmGzjxqGYdQcMw0ZhmHUHFMEhmEYNccUgWEYRs0xRWAYhlFzTBEYhmHUHFMEhmEYNccUgWEYRs35/3qE7Ts/gyPXAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -1476,7 +4249,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -1501,14 +4274,14 @@ }, { "cell_type": "code", - "execution_count": 105, + "execution_count": 71, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 6/6 [00:10<00:00, 1.69s/it]\n" + "100%|██████████| 6/6 [00:10<00:00, 1.78s/it]\n" ] } ], @@ -1517,7 +4290,7 @@ "total_emissions = []\n", "total_changes = []\n", "for pct in tqdm(pcts):\n", - " result_df = perfect_heuristic.prescribe_land_use(pct, None, dataset.test_df.loc[2021][constants.CAO_MAPPING[\"context\"]])\n", + " result_df = perfect_heuristic.prescribe_land_use(dataset.test_df.loc[2021][constants.CAO_MAPPING[\"context\"]], pct=pct)\n", " eluc_df, change_df = perfect_heuristic.predict_metrics(result_df)\n", " result_df[\"ELUC\"] = eluc_df[\"ELUC\"]\n", " result_df[\"change\"] = change_df[\"change\"]\n", @@ -1529,7 +4302,7 @@ }, { "cell_type": "code", - "execution_count": 106, + "execution_count": 72, "metadata": {}, "outputs": [], "source": [ @@ -1544,7 +4317,7 @@ }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 73, "metadata": {}, "outputs": [ { @@ -1572,7 +4345,7 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": 74, "metadata": {}, "outputs": [ { From 027996279c327e0825838fa22a8f2ba813ad9aa6 Mon Sep 17 00:00:00 2001 From: Daniel Young Date: Wed, 15 May 2024 09:07:41 -0700 Subject: [PATCH 7/7] Removed warning from rf training. It's the same model as in the paper so it should be fine --- use_cases/eluc/experiments/predictor_experiments.ipynb | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/use_cases/eluc/experiments/predictor_experiments.ipynb b/use_cases/eluc/experiments/predictor_experiments.ipynb index 0bf1f46..85a1a12 100644 --- a/use_cases/eluc/experiments/predictor_experiments.ipynb +++ b/use_cases/eluc/experiments/predictor_experiments.ipynb @@ -200,8 +200,6 @@ "metadata": {}, "outputs": [], "source": [ - "# Note: The original paper trains from 1982 onwards but this is too slow and large for the\n", - "# purpose of this example.\n", "forest_year = 1982\n", "forest.fit(dataset.train_df.loc[forest_year:][constants.NN_FEATS], dataset.train_df.loc[forest_year:][\"ELUC\"])\n", "forest.save(\"predictors/sklearn/trained_models/no_overlap_rf\")" @@ -554,7 +552,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.10.11" } }, "nbformat": 4,